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Step and Go supports Participatory Science Hackathon-Training partner organizations in identifying people, skills and projects that may contribute to or develop their activities.

Here you can apply for one or more professional fields, submit an impact or participatory science project you would like to develop, or express your interest in joining an existing project.

Independently from your application, you may also choose to participate in a Participatory Science Hackathon-Training to develop your skills, move a project forward, or contribute to the creation of new activities and jobs.

Can data from citizen science, Participatory Science and participatory research be trusted?

Admin — 2026-08-20T16:11:20Z

Ontological, epistemological, scientific and technical state of the art on the quality, validity and trustworthiness of data produced with the participation of non-professionals.

Review article — state of scientific knowledge — 2026

Abstract

The question of trust in data from citizen science, Participatory Science and participatory research has long been framed as an opposition between data produced by “amateurs” and data produced by professional scientists. The current state of the literature leads us to consider this opposition scientifically inadequate. The quality of a datum is not determined by the social or professional status of its producer. Its quality depends on a production chain comprising the definition of the observed phenomenon, the instrument, the protocol, the observer's competence, the sampling conditions, the quality-control mechanisms, the statistical processing, the documentation of successive transformations and the use for which the data are intended.

Comparative studies accumulated over more than two decades show that non-professional participants can produce observations with accuracy comparable to that of professionals in a large number of situations, while other tasks remain sensitive to experience, training, the ambiguity of the observed object or the level of precision required. Above all, they show that professionals themselves do not constitute an error-free benchmark. The most significant differences between participatory and conventional schemes frequently lie less in the basic accuracy of observations than in sampling design, spatial and temporal representativeness, documentation of observation effort, metadata management and the continuity of infrastructures.

The contemporary notion of fitness for purpose therefore reframes the question: the issue is no longer to decide in the abstract whether “citizen data” are reliable, but to establish whether a dataset, produced according to a documented procedure, possesses the properties required for a given inference or decision. Trust thus becomes an argued property of the chain of evidence. In participatory research in the strong sense, it has a second dimension: co-production can itself increase research quality by improving the framing of the question, the relevance of variables, access to the field, the interpretation of observations and the legitimacy of their uses.

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Keywords: citizen science; Participatory Science; participatory research; citizen science; participatory science; community-based participatory research; data quality; trust; validity; objectivity; metrology; bias; QA/QC; validation; verification; fitness for purpose; provenance; FAIR; open science; knowledge co-production.

1. A good or bad question that has become historically structuring

A significant part of the controversies surrounding citizen science rests on an apparently simple question: “can data produced by citizens be trusted?”

Yet this formulation already contains an assumption that should be demonstrated: the existence of a particular class of data whose defining property would be the identity of the person collecting them.

From the perspective of metrology, statistics and the epistemology of science, this category is fragile. A temperature measured at 18.4 °C does not acquire a new physical nature because the thermometer was read by a salaried hydrologist, a farmer, a teacher, a student or a retiree. What does change, however, is the probability of error associated with different components of the process: site selection, instrument calibration, compliance with stabilization time, reading, transcription, contextual qualification or application of the protocol.

Contemporary literature tends to shift the assessment away from the identity of the producer and towards the properties of the procedure. Kosmala and colleagues had already concluded, in their review that became a reference in the field, that very different participatory projects can produce data whose accuracy equals or exceeds that of professionals when the system combines appropriate design, training, validation, replication and statistical treatment of errors [1].

Lewandowski and Specht contributed a particularly important result to this discussion: in studies where professional and volunteer data were compared against the same independent benchmark, professionals were more accurate in only four of the seven available comparisons [2].

This obviously does not demonstrate universal equivalence between experienced and inexperienced people, but rather that professional status cannot be used as a substitute for a measure of quality.

A first conclusion can therefore be drawn.

Scientifically justified trust must apply to a data production chain, not to a social category of producers.

2. Ontology: what exactly is “participatory data”?

The difficulty appears as soon as four different objects are confused:

the real phenomenon;
the observation or measurement;
the recorded data;
the evidence used to support a scientific proposition.

An animal presence, a nitrate concentration, a temperature, a perception, a social practice or a pathological episode exist or occur independently of their entry into a database. Their observation then results from an interaction between a phenomenon, a material or cognitive observation system, a protocol and an observer. Recording transforms this observation into data. It is only after additional operations — qualification, selection, aggregation, modelling, comparison — that certain data become evidence supporting a proposition.

From this perspective, the expression “citizen data” describes its production history, not its essence.

It is more accurate to speak of data:

observed by a participant;
measured using a specified instrument;
produced according to a defined protocol;
accompanied by a given level of metadata;
possibly verified by a second observer;
corrected, weighted or modelled;
and intended for an explicit set of uses.

This ontological distinction is far from being purely philosophical. It determines the technical architecture of systems. Data standards dedicated to Participatory Science seek precisely to preserve the link between observation, project, protocol and context. PPSR Core thus distinguishes the “Project”, “Dataset” and “Observation” levels in order to make data provenance interpretable [3].

The same principle has long existed in other scientific infrastructures. Darwin Core, for example, provides a common vocabulary for specifying occurrence, taxon, event, location, identification and the evidence associated with a biodiversity observation [4].

Well-documented Participatory Science data are therefore much less an isolated number than an information object endowed with provenance.

3. Epistemology: trust, truth, validity and quality are not synonymous

Trust is not a metrological property.

One can trust false data; one can distrust accurate data. At least five notions must therefore be distinguished.

Accuracy refers to the proximity between an observation and a value or classification considered correct.

Precision concerns, in particular, the dispersion of repeated measurements.

Reliability refers to the stability of a process or measurement under comparable conditions.

Validity of inference concerns the possibility of supporting a conclusion on the basis of the available data.

Trust is a relationship in which an actor agrees to depend, at least partially, on information or an information producer whose work they cannot fully verify themselves.

This latter situation is by no means specific to Participatory Science. Modern science relies extensively on a cognitive division of labour. A climatologist trusts metrology laboratories; a biologist trusts instrument manufacturers; an epidemiologist trusts administrative databases; a researcher trusts authors they cite; an evaluator trusts data they did not collect themselves.

The relevant question therefore becomes that of the reasons for trust.

Hendriks, Kienhues and Bromme notably distinguish three dimensions of epistemic trust placed in an expert: expertise, integrity and benevolence or intentions [5].

Participatory Science adds a particular feature recently highlighted under the term “dual nature of trust”: scientists must be able to trust the data produced by participants, while participants must be able to trust the scientists, institutions and uses made of their contributions [6].

Trust is therefore bilateral and, in highly participatory research, multilateral.

4. Objectivity is not the absence of humans

A naïve conception of objectivity sometimes equates professionalization with neutrality: the scientist would be objective because they are trained and disinterested; the participant would be suspect because they have interests, values or personal experience of the problem.

Contemporary philosophy of science makes this opposition difficult to sustain.

Elliott and Rosenberg specifically analysed three recurring objections made against citizen science: the supposed absence of hypotheses, insufficient data quality and activist involvement. They show that none provides an argument allowing citizen science to be discredited in principle [7].

Scientific objectivity depends largely on procedures: making hypotheses explicit, critical scrutiny, the possibility of replication, documentation of decisions, plurality of viewpoints, examination of uncertainties and exposure of results to criticism.

In some cases, the involvement of participants possessing situated knowledge can even reveal implicit assumptions that had remained invisible to specialists.

This question is an old one. Wynne showed, in his work on Cumbrian sheep farmers after the Chernobyl accident, that the opposition between “scientific expertise” and “lay knowledge” concealed the fact that local actors possessed indispensable knowledge about agricultural practices and local conditions [8].

In participatory environmental or health research, the same situation regularly reappears: people living with the phenomenon know certain dimensions of exposure, uses, temporalities or behaviours that are not necessarily included in the initial models.

5. The central principle: fitness for purpose

One of the most robust outcomes of the field's evolution is the gradual abandonment of the abstract question of “quality” in favour of fitness for purpose.

The ISO 19157 standard applied to geographic information proceeds in the same way: it defines dimensions and procedures for quality assessment without imposing a universally sufficient level; it is up to the user to determine whether the dataset possesses the characteristics required for the intended application [9].

This reasoning is particularly well suited to Participatory Science.

Data may be insufficient to:

establish a regulatory concentration to within a few micrograms;

but sufficient to:

identify a spatial anomaly requiring confirmatory instrumental measurement.

An observation may be insufficient to:

distinguish between two morphologically very similar species;

but sufficient to:

determine the genus or family and track a large-scale distribution.

A time series may be insufficiently standardized to:

estimate absolute abundance;

but excellent for:

detecting a long-term trend.

Clare and colleagues specifically propose reversing the approach: first determine how much error is compatible with the intended inference, then invest in the corrective procedures needed to reach that threshold [10].

Parrish and colleagues similarly refer to fitness to purpose and intentional design [11].

The methodological consequence is major:

the required quality must be specified on the basis of the inference and intended use before the protocol is defined.

6. What empirical comparisons between volunteers and professionals show

The comparative literature justifies neither the claim that “citizens produce data as good as scientists” in every case, nor the opposite claim.

Aceves-Bueno and colleagues conducted one of the first quantitative reviews of this literature. Their analysis shows a generally favourable trend for citizen-generated data, but also considerable heterogeneity between tasks, systems and criteria used [12].

Prior experience, training, length of participation, task difficulty and protocol design explain part of the variation.

Field studies provide particularly instructive illustrations.

Crall and colleagues show, in invasive plant monitoring, that volunteers can achieve good performance, but that some tasks, particularly certain abundance estimates, remain sensitive to expertise [13].

In urban tree inventories, Roman and colleagues observed approximately 90% agreement with experts for several variables, but lower performance for precise species identification and certain assessments of tree condition [14].

In Snapshot Serengeti, aggregating classifications made by more than 28,000 participants made it possible to produce animal-image classifications extremely close to those of experts [15].

In Mosquito Alert, Palmer and colleagues showed that a system combining citizen reports, photographs, entomological validation and correction for sampling effort could provide monitoring of tiger mosquito expansion comparable to conventional methods while offering considerably greater geographical coverage [16].

Across 34 tropical sites in four countries, Danielsen and colleagues compared independently produced results from local communities and scientists for 63 taxa and several types of resource use. The two systems produced similar conclusions regarding the status and trends of the resources observed [17].

These results should not be turned into a slogan. They indicate that the scientific competence of a system is distributed among people, protocols, instruments, controls and processing methods.

7. The case of water: a particularly instructive laboratory

Participatory water-quality monitoring has several decades of history and provides some of the most direct tests of comparability.

A review specifically focusing on volunteer water-monitoring programmes identified fifteen studies comparing citizen and professional physicochemical measurements. Most reported comparable quality for the parameters studied, although gaps remained regarding very large historical and heterogeneous datasets [18].

The subsequent study of the Texas Stream Team is important because it examines large-scale existing data from 1992 to 2016 rather than an artificially controlled experiment. Overall agreement with professional measurements approaches 80% statewide for the parameters studied and 91% in the local subset where conditions were better controlled [19].

In the Yukon Basin, the Indigenous Observation Network similarly shows that a community-based network can operate according to a data cycle including planning, collection, quality assurance and documentation compatible with professional scientific requirements [20].

The 2023 review by Blanco and colleagues of 72 studies on citizen monitoring of surface-water quality nevertheless confirms the considerable heterogeneity of instruments, parameters, spatial scales and temporalities [21].

The field of water therefore perfectly illustrates the general principle: the question of trust must be asked parameter by parameter and use by use.

8. The real sources of fragility in participatory data

The main difficulties identified in the literature can be organized into several families.

8.1. Measurement error

It may result from:

an insufficiently precise instrument;
poor calibration;
sensor ageing;
incorrect reading;
a poorly applied protocol;
a delay between sampling and analysis.

These problems also exist in professional systems. This brings us back to the training of observers on this aspect, or even their supervision if, for example, they are being supported as a group.

8.2. Classification error

This particularly concerns:

taxonomic identification;
image classification;
symptom characterization;
habitat categorization;
interpretation of behaviour.

It can be reduced through supporting photographs, double classification, consensus or secondary expertise. The design and sizing of the participatory research project will need to address this aspect.

8.3. Sampling bias

This is often the most important problem.

Participants frequently choose:

accessible locations;
areas close to home;
times compatible with their activities;
objects considered interesting;
certain species rather than others.

A dataset can therefore consist of highly accurate individual observations while still providing a biased representation of the phenomenon studied.

8.4. Unknown observation effort

An absence observed after two hours of searching does not have the same meaning as an absence recorded after thirty seconds. The lack of information about effort is therefore a major source of difficulty for opportunistic data.

8.5. Observer heterogeneity

Experience, age, prior knowledge, motivation, fatigue or sensory acuity can affect performance.

8.6. Participation bias

People who participate in a project generally do not constitute a random sample of the population. This bias becomes particularly important when researchers wish to infer the attitudes, behaviours or perceptions of the general population.

8.7. Stake-related bias

A participant directly exposed to pollution may be accused of being “interested”. But the existence of a stake does not demonstrate the presence of falsification. Rather, it justifies an architecture that allows observation, control, analysis and interpretation to be separated.

The existence of conflicts of interest, motivations or values is not specific to non-professionals either. The relevant epistemology is therefore procedural: which mechanisms make it possible to detect and correct influences likely to distort inference?

9. QA/QC: trust can be engineered technically

One of the most operational findings in the literature is the identification of a genuine engineering approach to participatory data quality.

Freitag, Meyer and Whiteman identified twelve strategies for building credibility distributed across preparation, collection and analysis [22].

A robust system can combine:

Before collection

explicit definition of the intended use;
pilot study;
simplification of the protocol;
determination of tolerances;
calibration;
training;
possible participant certification;
test data or “gold questions”.

During collection

value-range checks;
automatic timestamping;
geolocation;
supporting photograph or recording;
repeated observations;
duplication of a fraction of measurements;
calibration checks;
structured data entry;
logging of operations.

After collection

automatic detection of outliers;
comparison with reference data;
second reading;
community validation;
expert review;
observer weighting;
detection models;
statistical correction;
explicit qualification of uncertainty.

Baker and colleagues studied 259 ecological systems. For the 142 whose verification methods could be established, expert verification remained the dominant method, followed by community consensus and automated procedures. The authors propose a hierarchical architecture: automated or community processing of the main volume and referral of ambiguous cases to experts [23].

This architecture is particularly important in the age of artificial intelligence: scarce human expertise can be concentrated on observations offering the greatest information gain.

10. Statistics: noise does not prevent inference

Participatory data have contributed to changing another intuition: imperfect data are not necessarily unusable.

Bird and colleagues show that the main biases encountered in large citizen databases — observer heterogeneity, preferential sampling, spatial dependencies, irregular repetitions — are largely similar to problems already known from other ecological databases [24].

Methods that can be used include:

hierarchical models;
mixed-effects models;
occupancy models;
estimation of detection probability;
effort weighting;
observer calibration;
spatio-temporal models;
machine learning;
integration of multiple data sources.

The principle is a classic one: explicitly model the observation process in addition to the observed phenomenon.

This distinction between the ecological process and the observation process lies at the heart of occupancy models and much of contemporary quantitative ecology.

It is also a response to the idea that a database containing errors would be intrinsically unusable. The question is rather whether the errors are sufficiently characterized to be incorporated into inference.

11. Quantity does not, however, replace quality

An opposite misunderstanding would be to believe that massive data volume automatically corrects every flaw.

It does not.

Random error may decrease as the number of observations increases. Systematic bias, on the other hand, can become extremely precisely wrong.

One million observations concentrated around urban areas do not constitute a random sample of a territory.

One million sensors with the same calibration defect do not produce a better measurement of the true value.

One million participants using an ambiguous definition can reproduce the same conceptual bias.

Volume reduces certain types of uncertainty; it abolishes neither biases nor validity problems.

12. Documentation, provenance and open science

Trust can be increased without changing a single observation, simply by making its genealogy accessible.

Ideally, a user should be able to know:

who or what system produced the observation;
according to which protocol;
on what date;
with which instrument;
with which version of the protocol or software;
which corrections were applied;
which validation was performed;
which uncertainty is associated with it;
under which licence the data can be reused.

Bowser and colleagues observed that many projects had developed quality practices, but that documentation, interoperability, open access and infrastructure sustainability frequently remained insufficient [25].

The FAIR principles — Findable, Accessible, Interoperable, Reusable — provide a general reference here [26].

Balázs and colleagues also recommend the use of international standards and systematic documentation of quality-assurance procedures [27].

An important implication follows: transparency about uncertainty can increase trust more than claiming that uncertainty does not exist.

13. A persistent difficulty: perceived quality is not measured quality

Even when quality procedures exist, participatory data can remain underused.

Burgess and colleagues surveyed biodiversity researchers and project managers. Their work identifies a preference for certain sources and certain types of producers that is not always justified by demonstrated differences in quality [28].

Turbé and colleagues examined 503 European projects and 45 in-depth studies. Lack of trust in data quality appeared as one of the main obstacles to their integration into environmental policy, even though many of the projects studied had high scientific standards [29].

The distinction between actual quality and perceived quality becomes central here.

A Participatory Science quality policy therefore cannot be limited to producing good data. It must produce clear evidence of their quality.

14. The institutional problem: accepting data also means accepting an unusual producer

Institutional recognition involves questions of professional boundaries.

The use of data produced by an administration, a university, an association or a community does not necessarily carry the same symbolic cost for the decision-maker.

Yet several studies show that Participatory Science can contribute to research, conservation and public policy when properly integrated.

McKinley and colleagues conclude that a citizen-based system that is properly designed, implemented and evaluated can produce robust science and contribute to natural-resource management [30].

In the marine field, Hyder and colleagues emphasize that each dataset should be assessed individually rather than rejected on the basis of its origin [31].

Institutional integration nevertheless requires continuity, governance, standardization, documentation and responsibility. The question is therefore not only: “are these data accurate?”, but also: “which institution can guarantee their preservation, interpretation and long-term use?”

15. Participatory data and international indicators

The potential changes scale again when citizen science is considered for monitoring biodiversity or the Sustainable Development Goals.

Chandler and colleagues show that citizen and community programmes already cover several Essential Biodiversity Variables, including distribution, abundance, phenology and certain ecosystem functions, while still presenting significant geographical and taxonomic gaps [32].

Fritz and colleagues subsequently proposed a roadmap for integrating citizen science into monitoring the Sustainable Development Goals, emphasizing the importance of quality, access and interoperability [33].

This perspective changes the very function of certain data. Their advantage is not always to achieve the greatest possible precision at a given point, but to provide spatial, temporal or social resolution that a conventional professional network could not economically achieve.

16. Participatory research: when participants are no longer merely collectors

The literature on contributory citizen science is not sufficient to understand participatory research in the strong sense.

In Community-Based Participatory Research, Participatory Action Research and related traditions, participation can concern:

formulation of the problem;
choice of the research question;
definition of variables;
protocol design;
collection;
analysis;
interpretation;
dissemination;
decision;
action.

The potential epistemic effect is then deeper.

Jagosh and colleagues define participatory research as the co-production of research between researchers and people affected by the phenomenon or responsible for action. Their realist review highlights benefits that may emerge through partnership mechanisms: improved recruitment, protocol adaptation, cultural relevance, better interpretation and long-term effects [34].

Balázs and Morello-Frosch proposed describing this contribution through three dimensions: rigor, relevance, reach. Participation can strengthen rigor by improving design and interpretation, relevance by directing research towards the right questions, and reach by facilitating dissemination and use of results [35].

Participation is therefore not merely a democratic concession made to science. In some configurations, it constitutes a mechanism for reducing framing error.

17. Framing error: a dimension often absent from discussions of quality

Data quality is generally assessed after researchers have decided what should be measured.

Yet research can produce extraordinarily precise measurements of a poorly chosen variable.

This form of error is particularly important for complex phenomena.

People who live daily with an ecosystem, a public service, a disease, a professional activity, a risk or pollution may point out:

an overlooked temporality;
an exposure location absent from the initial plan;
a behaviour not taken into account;
an intermediate variable;
local terminology;
an overly broad category;
a plausible causal mechanism;
a consequence that was not being investigated.

Co-production can therefore act upstream of metrological accuracy.

This perspective is consistent with the post-normal science of Funtowicz and Ravetz, which proposes broadening the peer community when uncertainties are high, values are contested and stakes are high [36].

Recent work nevertheless shows that not every form of citizen science automatically constitutes an “extended peer community”. This depends on the actual degree of participation in problem framing, evaluation and decision-making [37].

18. Relational trust and scientific quality become interdependent

In participatory research, trust is no longer only a judgement made about data.

It becomes a mechanism for producing those data.

A community that does not trust researchers may:

refuse to participate;
leave the study early;
withhold certain information;
respond strategically;
prevent access to certain field sites;
refuse to authorize data reuse.

Conversely, a trusting relationship can increase continuity of participation, the contextual quality of information and the ability to interpret anomalies.

Jagosh and colleagues showed, in their realist evaluation of CBPR partnerships, that trust and partnership synergy could contribute to the sustainability of collaborations and produce long-term ripple effects [38].

Lucero and colleagues propose an empirical typology of trust ranging from trust deficit to reflective trust, intended to track the evolution of partnerships [39].

The review by Gilfoyle, MacFarlane and Salsberg nevertheless confirms the heterogeneity of definitions and measurements of trust in participatory research networks [40].

19. 2025–2026 research: towards an integrated conception of scientific and social outcomes

The systematic review published in 2025 by Yu and colleagues analyses 211 publications devoted to knowledge co-production through citizen science. It identifies 29 variables organized around participants, project design and context. Training, trust, feedback mechanisms, participatory capacities and data management appear among the factors frequently associated with outcomes [41].

The 2026 review by Israel and colleagues simultaneously confirms the maturation of the CBPR field: increasing academic and community credibility, development of validated evaluation instruments and accumulation of findings on public policy and structural change [42].

Finally, the systematic review of 124 empirical studies devoted to public trust in science shows that integrity, source characteristics, modes of communication and public involvement play a role in trust. Some of the included studies indicate that direct participation in research can increase trust in its results, particularly when the process is transparent [43].

The scientific problem can therefore no longer be reduced to the accuracy of the recorded observation. It simultaneously concerns the technical quality of the dataset, the quality of the knowledge-production process and the relationship between producers and users of that knowledge.

20. An integrated matrix of trust in participatory data

The state of the art makes it possible to propose a nine-dimensional framework.

1. Conceptual validity

Are we measuring the relevant phenomenon?

2. Protocol validity

Does the protocol make it possible to answer the question?

3. Metrological quality

Do the instruments and observations possess the required accuracy and precision?

4. Sampling quality

Does the dataset sufficiently represent the relevant space, time, populations or events?

5. Validation quality

Are there procedures capable of detecting errors, inconsistencies and questionable classifications?

6. Statistical quality

Are biases and uncertainties integrated into the inference?

7. Provenance and reproducibility

Can we understand how the data were produced and transformed?

8. Legitimacy and governance

Are the conditions governing the production, ownership and use of the data explicit and acceptable?

9. Fitness for purpose

Are these properties sufficient for the intended decision or inference?

This matrix makes it possible to move beyond an unproductive opposition between “professional data” and “citizen data”.

21. Towards a trust score rather than a binary label

Future architectures could associate each dataset — or even each observation — with a trust profile rather than a single verdict.

Such a profile could document:

observer training level;
protocol used;
instrument calibration;
associated evidence;
number of independent validations;
automated validation;
expert validation;
agreement with other sources;
estimated uncertainty;
metadata completeness;
representativeness;
correction status;
dataset version;
validated scientific uses.

The objective would not be to create a social hierarchy among contributors. It would be to make trust computable, explainable and reassessable.

The emergence of common standards such as PPSR Core, the integration of FAIR metadata and the development of hybrid methods combining community validation, expertise and artificial intelligence make this architecture technically realistic.

22. What science now allows us to assert

Several propositions appear sufficiently well supported to constitute a reference foundation.

First, there is no scientific reason to consider data inferior a priori because they were produced by a non-professional participant.

Second, there are tasks for which professional expertise greatly improves accuracy and others for which short training, an appropriate protocol or secondary validation can achieve comparable performance.

Third, the main weaknesses of large citizen-based systems often concern representativeness, observation effort, documentation and infrastructure as much as, or more than, the basic accuracy of observations.

Fourth, professional data do not constitute an ontologically error-free benchmark. They too must undergo quality assurance, calibration and evaluation.

Fifth, quality must be assessed relative to the intended use.

Sixth, explicit QA/QC, validation, documentation and modelling procedures make it possible to increase and quantify trust.

Seventh, the perceived quality of data and their demonstrated quality may diverge; an institutional bias against unconventional sources remains documented.

Eighth, in more participatory forms of research, participation can increase scientific quality by improving framing, relevance, access to the field and interpretation.

Ninth, this participation can also degrade research if responsibilities are ambiguous, if the required skills have not been acquired, if power asymmetries are not addressed or if participation is purely symbolic.

Tenth, trust and quality must therefore be conceived as properties of the research architecture, rather than as moral qualities attributed to a category of actors.

Conclusion

The scientific literature no longer allows a serious general opposition between “real scientific data” and “citizen data” to be sustained.

It leads instead to a more demanding distinction.

There are data whose provenance is well known or poorly known; instruments that are calibrated or not; protocols that are appropriate or inadequate; observers who are trained or not; sampling designs that are representative or biased; errors that are characterized or invisible; validation procedures that are strong or absent; datasets that are documented or opaque; and inferences that are compatible or incompatible with their properties.

These distinctions cut across professional science and Participatory Science alike.

The specificity of citizen science lies less in the emergence of a new epistemological class of data than in the redistribution of knowledge-production functions among a larger number of actors. This redistribution introduces new risks, but also new capacities: spatial coverage, temporal continuity, volume of observations, situated knowledge, early detection, access to difficult field sites, critique of existing categories and multiplication of verification possibilities.

The decisive shift therefore consists in moving from status-based trust — “I believe these data because they come from a scientist” — to demonstrable trust — “I know the conditions under which these data were produced, which controls they underwent, what uncertainty they contain and for which uses they are sufficiently robust”.

This is probably where the deepest contribution of Participatory Science to contemporary epistemology lies: it forces science to make visible what, in conventional systems, often remained implicit — the precise conditions that make it possible to transform an observation into data, data into evidence and evidence into trustworthy knowledge.

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Extended scientific and technical bibliography

Corpus: data quality, trust, citizen science, Participatory Science, participatory research, co-production, validation, public decision-making and data standards.

A. Foundations, definitions and structuring of the field

1. Bonney R., Ballard H., Jordan R., McCallie E., Phillips T., Shirk J., Wilderman C. C. (2009). Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education. CAISE.
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2. Bonney R., Cooper C. B., Dickinson J., Kelling S., Phillips T., Rosenberg K. V., Shirk J. (2009). « Citizen Science: A Developing Tool for Expanding Science Knowledge and Scientific Literacy ». BioScience, 59(11), 977–984.
DOI

3. Cooper C. B., Dickinson J., Phillips T., Bonney R. (2007). « Citizen Science as a Tool for Conservation in Residential Ecosystems ». Ecology and Society, 12(2), 11.
Article

4. Silvertown J. (2009). « A new dawn for citizen science ». Trends in Ecology & Evolution, 24(9), 467–471.
DOI

5. Dickinson J. L., Zuckerberg B., Bonter D. N. (2010). « Citizen Science as an Ecological Research Tool: Challenges and Benefits ». Annual Review of Ecology, Evolution, and Systematics, 41, 149–172.
DOI

6. Shirk J. L., Ballard H. L., Wilderman C. C., Phillips T., Wiggins A., Jordan R., McCallie E., Minarchek M., Lewenstein B. V., Krasny M. E., Bonney R. (2012). « Public Participation in Scientific Research: a Framework for Deliberate Design ». Ecology and Society, 17(2), 29.
Article

7. Haklay M. (2013). « Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation ». In Crowdsourcing Geographic Knowledge.
DOI

8. ECSA — European Citizen Science Association (2015). Ten Principles of Citizen Science.
Document

9. Kullenberg C., Kasperowski D. (2016). « What Is Citizen Science? A Scientometric Meta-Analysis ». PLOS ONE, 11(1), e0147152.
DOI

10. Eitzel M. V. et al. (2017). « Citizen Science Terminology Matters: Exploring Key Terms ». Citizen Science: Theory and Practice, 2(1).
Article

11. Hecker S., Haklay M., Bowser A., Makuch Z., Vogel J., Bonn A. (eds.) (2018). Citizen Science: Innovation in Open Science, Society and Policy. UCL Press.
DOI

12. Thiel M. et al. (2022). « Citizen science in environmental and ecological sciences ». Nature Reviews Methods Primers, 2, 64.
DOI

13. Cornish F., Breton N., Moreno-Tabarez U. et al. (2023). « Participatory action research ». Nature Reviews Methods Primers, 3, 34.
DOI

B. Epistemological foundations, objectivity, expertise and trust

14. Funtowicz S. O., Ravetz J. R. (1993). « Science for the post-normal age ». Futures, 25(7), 739–755.
DOI

15. Wynne B. (1992). « Misunderstood misunderstanding: social identities and public uptake of science ». Public Understanding of Science, 1(3), 281–304.
DOI

16. Bidwell D. (2009). « Is Community-Based Participatory Research Postnormal Science? ». Science, Technology, & Human Values, 34(6), 741–761.
DOI

17. Cash D. W., Clark W. C., Alcock F., Dickson N. M., Eckley N., Guston D. H., Jäger J., Mitchell R. B. (2003). « Knowledge systems for sustainable development ». PNAS, 100(14), 8086–8091.
DOI

18. Hendriks F., Kienhues D., Bromme R. (2015). « Measuring Laypeople's Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory ». PLOS ONE, 10(10), e0139309.
DOI

19. Elliott K. C., Rosenberg J. (2019). « Philosophical Foundations for Citizen Science ». Citizen Science: Theory and Practice, 4(1), 9.
DOI

20. Haklay M., König A., Moustard F. et al. (2023). « Citizen science and Post-Normal Science's extended peer community: Identifying overlaps by mapping typologies ». Futures, 150, 103178.
DOI

21. Skarlatidou A. et al. (2024). « How can bottom-up citizen science restore public trust in environmental governance and sciences? Recommendations from three case studies ». Environmental Science & Policy, 160, 103854.
DOI

22. Hunter D. L., Johnson V., Cooper C. (2024). « The Dual Nature of Trust in Participatory Sciences: An Investigation into Data Quality and Household Privacy Preferences ». Citizen Science: Theory and Practice, 9(1), 31.
DOI

23. Iordanou K., Antoniou A., De Vos M. (2026). « Public Trust in Science: A Systematic Literature Review ». Journal of Academic Ethics, 24.
DOI

24. Schuster C., Scheu A. M. (2026). « How Communication of Scientific Uncertainty Affects Trust in Science—A Systematic Review ». Risk Analysis, 46(5).
DOI

C. Data quality: reviews and methodological frameworks

25. Wiggins A., Newman G., Stevenson R. D., Crowston K. (2011). « Mechanisms for Data Quality and Validation in Citizen Science ». IEEE Seventh International Conference on e-Science Workshops.
DOI

26. Hunter J., Alabri A., van Ingen C. (2013). « Assessing the quality and trustworthiness of citizen science data ». Concurrency and Computation: Practice and Experience, 25(4), 454–466.
DOI

27. Riesch H., Potter C. (2014). « Citizen science as seen by scientists: Methodological, epistemological and ethical dimensions ». Public Understanding of Science, 23(1), 107–120.
DOI

28. Bird T. J. et al. (2014). « Statistical solutions for error and bias in global citizen science datasets ». Biological Conservation, 173, 144–154.
DOI

29. Lewandowski E., Specht H. (2015). « Influence of volunteer and project characteristics on data quality of biological surveys ». Conservation Biology, 29(3), 713–723.
DOI

30. Freitag A., Meyer R., Whiteman L. (2016). « Strategies Employed by Citizen Science Programs to Increase the Credibility of Their Data ». Citizen Science: Theory and Practice, 1(1), 2.
DOI

31. Kosmala M., Wiggins A., Swanson A., Simmons B. (2016). « Assessing data quality in citizen science ». Frontiers in Ecology and the Environment, 14(10), 551–560.
DOI

32. Aceves-Bueno E., Adeleye A. S., Feraud M. et al. (2017). « The Accuracy of Citizen Science Data: A Quantitative Review ». Bulletin of the Ecological Society of America, 98(4).
DOI

33. Parrish J. K., Burgess H., Weltzin J. F., Fortson L., Wiggins A., Simmons B. (2018). « Exposing the Science in Citizen Science: Fitness to Purpose and Intentional Design ». Integrative and Comparative Biology, 58(1), 150–160.
DOI

34. Clare J. D. J. et al. (2019). « Making inference with messy (citizen science) data: when are data accurate enough and how can they be improved? ». Ecological Applications, 29(2), e01849.
DOI

35. Bowser A., Cooper C., de Sherbinin A., Wiggins A., Brenton P., Chuang T.-R., Faustman E., Haklay M., Meloche M. (2020). « Still in Need of Norms: The State of the Data in Citizen Science ». Citizen Science: Theory and Practice, 5(1), 18.
DOI

36. Balázs B. et al. (2021). « Data Quality in Citizen Science ». In Vohland K. et al. (eds.), The Science of Citizen Science.
DOI

37. Baker E., Drury J. P., Judge J., Roy D. B., Smith G. C., Stephens P. A. (2021). « The Verification of Ecological Citizen Science Data: Current Approaches and Future Possibilities ». Citizen Science: Theory and Practice, 6(1).
DOI

38. « Use-Specific Considerations for Optimising Data Quality Trade-Offs in Citizen Science ». (2023). Remote Sensing, 15(5), 1407.
Article

D. Empirical validation studies in ecology and biodiversity

39. Crall A. W., Newman G. J., Stohlgren T. J., Holfelder K. A., Graham J., Waller D. M. (2011). « Assessing citizen science data quality: an invasive species case study ». Conservation Letters, 4(6), 433–442.
DOI

40. Bonter D. N., Cooper C. B. (2012). « Data validation in citizen science: a case study from Project FeederWatch ». Frontiers in Ecology and the Environment, 10, 305–307.
DOI

41. Danielsen F., Jensen P. M., Burgess N. D. et al. (2014). « A Multicountry Assessment of Tropical Resource Monitoring by Local Communities ». BioScience, 64(3), 236–251.
DOI

42. Theobald E. J. et al. (2015). « Global change and local solutions: Tapping the unrealized potential of citizen science for biodiversity research ». Biological Conservation, 181, 236–244.
DOI

43. Swanson A., Kosmala M., Lintott C., Packer C. (2016). « A generalized approach for producing, quantifying, and validating citizen science data from wildlife images ». Conservation Biology, 30(3), 520–531.
DOI

44. Roman L. A., Scharenbroch B. C., Östberg J. P. A. et al. (2017). « Data quality in citizen science urban tree inventories ». Urban Forestry & Urban Greening, 22, 124–135.
DOI

45. Palmer J. R. B., Oltra A., Collantes F. et al. (2017). « Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes ». Nature Communications, 8, 916.
DOI

46. Chandler M., See L., Copas K. et al. (2017). « Contribution of citizen science towards international biodiversity monitoring ». Biological Conservation, 213, 280–294.
DOI

E. Participatory water monitoring

47. Conrad C. C., Hilchey K. G. (2011). « A review of citizen science and community-based environmental monitoring: issues and opportunities ». Environmental Monitoring and Assessment, 176, 273–291.
DOI

48. Herman-Mercer N., Antweiler R., Wilson N., Mutter E., Toohey R., Schuster P. (2018). « Data Quality from a Community-Based, Water-Quality Monitoring Project in the Yukon River Basin ». Citizen Science: Theory and Practice, 3(2), 1.
DOI

49. Albus K., Thompson R., Mitchell F. (2019). « Usability of Existing Volunteer Water Monitoring Data: What Can the Literature Tell Us? ». Citizen Science: Theory and Practice.
Article

50. Albus K. H. et al. (2020). « Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program ». PLOS ONE, 15(1), e0227540.
DOI

51. « Success factors for citizen science projects in water quality monitoring ». (2020). Science of the Total Environment.
DOI

52. Blanco S. et al. (2023). « Citizen science approaches for water quality measurements ». Science of the Total Environment, 897, 165436.
DOI

F. Air quality, sensors and low-cost measurements

53. Ottinger G. (2010). « Buckets of Resistance: Standards and the Effectiveness of Citizen Science ». Science, Technology, & Human Values.
Search for the article

54. « Tackling Data Quality When Using Low-Cost Air Quality Sensors in Citizen Science Projects ». (2021). Frontiers in Environmental Science.
Article

G. Citizen science, public policy, governance and SDGs

55. Danielsen F., Burgess N. D., Jensen P. M., Pirhofer-Walzl K. (2010). « Environmental monitoring: the scale and speed of implementation varies according to the degree of peoples involvement ». Journal of Applied Ecology, 47, 1166–1168.
DOI

56. Hyder K. et al. (2015). « Can citizen science contribute to the evidence-base that underpins marine policy? ». Marine Policy, 59, 112–120.
DOI

57. McKinley D. C. et al. (2017). « Citizen science can improve conservation science, natural resource management, and environmental protection ». Biological Conservation, 208, 15–28.
DOI

58. Turbé A. et al. (2019). « Understanding the Citizen Science Landscape for European Environmental Policy: An Assessment and Recommendations ». Citizen Science: Theory and Practice, 4(1).
DOI

59. Fritz S., See L., Carlson T., Haklay M., Oliver J. L., Fraisl D. et al. (2019). « Citizen science and the United Nations Sustainable Development Goals ». Nature Sustainability, 2, 922–930.
DOI

60. « How Does Policy Conceptualise Citizen Science? A Qualitative Content Analysis of International Policy Documents ». (2019). Citizen Science: Theory and Practice, 4(1), 32.
DOI

61. Criscuolo L., L'Astorina A., van der Wal R., Colucci-Gray L. (2023). « Recent contributions of citizen science on sustainability policies: A critical review ». Current Opinion in Environmental Science & Health, 31, 100423.
DOI

62. Callaghan C. T. et al. (2025). « Citizen science as a valuable tool for environmental review ». Frontiers in Ecology and the Environment.
DOI

63. « Mainstreaming citizen science in policy: Adaptations needed in policy and how to achieve them in five European countries ». (2025). Environmental Science & Policy, 171, 104148.
DOI

H. Participatory research, CBPR, co-production and scientific quality

64. Jagosh J., Macaulay A. C., Pluye P. et al. (2012). « Uncovering the Benefits of Participatory Research: Implications of a Realist Review for Health Research and Practice ». Milbank Quarterly, 90(2), 311–346.
DOI

65. Balázs C. L., Morello-Frosch R. (2013). « The Three Rs: How Community-Based Participatory Research Strengthens the Rigor, Relevance, and Reach of Science ». Environmental Justice, 6(1).
DOI

66. Jagosh J., Bush P. L., Salsberg J. et al. (2015). « A realist evaluation of community-based participatory research: partnership synergy, trust building and related ripple effects ». BMC Public Health, 15, 725.
DOI

67. Lucero J. E., Boursaw B., Eder M., Greene-Moton E., Wallerstein N., Oetzel J. G. (2020). « Engage for Equity: The Role of Trust and Synergy in Community-Based Participatory Research ». Health Education & Behavior, 47(3), 372–379.
DOI

68. Gilfoyle M., MacFarlane A., Salsberg J. (2022). « Conceptualising, operationalising, and measuring trust in participatory health research networks: a scoping review ». Systematic Reviews, 11, 40.
DOI

69. Yu S., Cornips L., Steen T., Giest S., Crompvoets J., Rajabifard A., Aryal J., Jukić T. (2025). « Researching or researching with the public? A systematic review on knowledge co-production through citizen science ». Science and Public Policy, 52(3), 375–405.
DOI

70. Israel B. A., Schulz A. J., Becker A. B., Reyes C. L., Parker E. A., Reyes A. G. (2026). « Community-Based Participatory Research: Evolution and Significant Developments ». Annual Review of Public Health, 47, 135–157.
DOI

71. Galappaththi E. K., Ilangarathna G. A., Jayasekara S. M. (2026). « Co-planning community-based research: evidence, steps, and strategies ». Current Opinion in Environmental Sustainability, 80, 101624.
DOI

I. Metadata, interoperability, provenance and open science

72. Wieczorek J., Bloom D., Guralnick R., Blum S., Döring M., Giovanni R., Robertson T., Vieglais D. (2012). « Darwin Core: An Evolving Community-Developed Biodiversity Data Standard ». PLOS ONE, 7(1), e29715.
DOI

73. Wilkinson M. D., Dumontier M., Aalbersberg I. J. et al. (2016). « The FAIR Guiding Principles for scientific data management and stewardship ». Scientific Data, 3, 160018.
DOI

74. PPSR Core. A Data Standard for Public Participation in Scientific Research.
Standard

75. Biodiversity Information Standards — TDWG. Darwin Core.
Standard

76. ISO. ISO 19157:2013 — Geographic information — Data quality.
Standard

77. Open Geospatial Consortium — Citizen Science Domain Working Group. Citizen Science Standards List.
Reference

J. Core literature to prioritize for a literature review

For a focused academic review specifically centred on the question « can the data be trusted? », the priority bibliographic core consists of:

Kosmala et al. 2016 ;
Lewandowski & Specht 2015 ;
Aceves-Bueno et al. 2017 ;
Bird et al. 2014 ;
Clare et al. 2019 ;
Hunter, Alabri & van Ingen 2013 ;
Freitag, Meyer & Whiteman 2016 ;
Baker et al. 2021 ;
Bowser et al. 2020 ;
Balázs et al. 2021 ;
Elliott & Rosenberg 2019 ;
Burgess et al. 2017 ;
Turbé et al. 2019 ;
Hunter, Johnson & Cooper 2024 ;
Yu et al. 2025 ;
Iordanou, Antoniou & De Vos 2026.

For participatory research in the strong sense, priority should also be given to:

Jagosh et al. 2012 ;
Jagosh et al. 2015 ;
Balázs & Morello-Frosch 2013 ;
Lucero et al. 2020 ;
Gilfoyle et al. 2022 ;
Cornish et al. 2023 ;
Israel et al. 2026.

For operational environmental systems:

Danielsen et al. 2014 ;
Palmer et al. 2017 ;
Roman et al. 2017 ;
Swanson et al. 2016 ;
Albus et al. 2020 ;
Herman-Mercer et al. 2018 ;
Blanco et al. 2023 ;
Chandler et al. 2017 ;
McKinley et al. 2017.

This combination makes it possible to cover separately — and then connect — observation accuracy, sampling bias, inference validity, QA/QC, provenance, epistemic trust, institutional trust, knowledge co-production and the legitimacy of decision-making.

[1] Kosmala M., Wiggins A., Swanson A., Simmons B., 2016, « Assessing data quality in citizen science », Frontiers in Ecology and the Environment. DOI(https://doi.org/10.1002/fee.1436)].

[2] Lewandowski E., Specht H., 2015, « Influence of volunteer and project characteristics on data quality of biological surveys ». DOI(https://doi.org/10.1111/cobi.12481)].

[3] PPSR Core, « A Data Standard for Public Participation in Scientific Research ». Site(https://core.citizenscience.org/)].

[4] Wieczorek J. et al., 2012, « Darwin Core: An Evolving Community-Developed Biodiversity Data Standard ». DOI(https://doi.org/10.1371/journal.pone.0029715)].

[5] Hendriks F., Kienhues D., Bromme R., 2015, « Measuring Laypeople's Trust in Experts in a Digital Age ». DOI(https://doi.org/10.1371/journal.pone.0139309)].

[6] Hunter D. L., Johnson V., Cooper C., 2024, « The Dual Nature of Trust in Participatory Sciences ». DOI(https://doi.org/10.5334/cstp.697)].

[7] Elliott K. C., Rosenberg J., 2019, « Philosophical Foundations for Citizen Science ». DOI(https://doi.org/10.5334/cstp.155)].

[8] Wynne B., 1992, « Misunderstood misunderstanding: social identities and public uptake of science ». DOI(https://doi.org/10.1088/0963-6625/1/3/004)].

[9] ISO, « ISO 19157 — Geographic information — Data quality ». Reference(https://www.iso.org/standard/32575.html)].

[10] Clare J. D. J. et al., 2019, « Making inference with messy (citizen science) data: when are data accurate enough and how can they be improved? ». DOI(https://doi.org/10.1002/eap.1849)].

[11] Parrish J. K. et al., 2018, « Exposing the Science in Citizen Science: Fitness to Purpose and Intentional Design ». DOI(https://doi.org/10.1093/icb/icy032)].

[12] Aceves-Bueno E. et al., 2017, « The Accuracy of Citizen Science Data: A Quantitative Review ». DOI(https://doi.org/10.1002/bes2.1336)].

[13] Crall A. W. et al., 2011, « Assessing citizen science data quality: an invasive species case study ». DOI(https://doi.org/10.1111/j.1755-263X.2011.00196.x)].

[14] Roman L. A. et al., 2017, « Data quality in citizen science urban tree inventories ». DOI(https://doi.org/10.1016/j.ufug.2017.02.001)].

[15] Swanson A., Kosmala M., Lintott C., Packer C., 2016, « A generalized approach for producing, quantifying, and validating citizen science data from wildlife images ». DOI(https://doi.org/10.1111/cobi.12695)].

[16] Palmer J. R. B. et al., 2017, « Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes ». DOI(https://doi.org/10.1038/s41467-017-00914-9)].

[17] Danielsen F. et al., 2014, « A Multicountry Assessment of Tropical Resource Monitoring by Local Communities ». DOI(https://doi.org/10.1093/biosci/biu001)].

[18] Albus K., Thompson R., Mitchell F., 2019, « Usability of Existing Volunteer Water Monitoring Data: What Can the Literature Tell Us? ». Article(https://theoryandpractice.citizenscienceassociation.org/articles/222)].

[19] Albus K. H. et al., 2020, « Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program ». DOI(https://doi.org/10.1371/journal.pone.0227540)].

[20] Herman-Mercer N. et al., 2018, « Data Quality from a Community-Based, Water-Quality Monitoring Project in the Yukon River Basin ». DOI(https://doi.org/10.5334/cstp.123)].

[21] Blanco S. et al., 2023, « Citizen science approaches for water quality measurements ». DOI(https://doi.org/10.1016/j.scitotenv.2023.165436)].

[22] Freitag A., Meyer R., Whiteman L., 2016, « Strategies Employed by Citizen Science Programs to Increase the Credibility of Their Data ». DOI(https://doi.org/10.5334/cstp.6)].

[23] Baker E. et al., 2021, « The Verification of Ecological Citizen Science Data: Current Approaches and Future Possibilities ». DOI(https://doi.org/10.5334/cstp.351)].

[24] Bird T. J. et al., 2014, « Statistical solutions for error and bias in global citizen science datasets ». DOI(https://doi.org/10.1016/j.biocon.2013.07.037)].

[25] Bowser A. et al., 2020, « Still in Need of Norms: The State of the Data in Citizen Science ». DOI(https://doi.org/10.5334/cstp.303)].

[26] Wilkinson M. D. et al., 2016, « The FAIR Guiding Principles for scientific data management and stewardship ». DOI(https://doi.org/10.1038/sdata.2016.18)].

[27] Balázs B. et al., 2021, « Data Quality in Citizen Science », in The Science of Citizen Science. DOI(https://doi.org/10.1007/978-3-030-58278-4_8)].

[28] Burgess H. K. et al., 2017, « The science of citizen science: Exploring barriers to use as a primary research tool ». DOI(https://doi.org/10.1016/j.biocon.2016.05.014)].

[29] Turbé A. et al., 2019, « Understanding the Citizen Science Landscape for European Environmental Policy ». DOI(https://doi.org/10.5334/cstp.239)].

[30] McKinley D. C. et al., 2017, « Citizen science can improve conservation science, natural resource management, and environmental protection ». DOI(https://doi.org/10.1016/j.biocon.2016.05.015)].

[31] Hyder K. et al., 2015, « Can citizen science contribute to the evidence-base that underpins marine policy? ». DOI(https://doi.org/10.1016/j.marpol.2015.04.022)].

[32] Chandler M. et al., 2017, « Contribution of citizen science towards international biodiversity monitoring ». DOI(https://doi.org/10.1016/j.biocon.2016.09.004)].

[33] Fritz S. et al., 2019, « Citizen science and the United Nations Sustainable Development Goals ». DOI(https://doi.org/10.1038/s41893-019-0390-3)].

[34] Jagosh J. et al., 2012, « Uncovering the benefits of participatory research ». DOI(https://doi.org/10.1111/j.1468-0009.2012.00665.x)].

[35] Balázs C. L., Morello-Frosch R., 2013, « The Three Rs: How Community-Based Participatory Research Strengthens the Rigor, Relevance, and Reach of Science ». DOI(https://doi.org/10.1089/env.2012.0017)].

[36] Funtowicz S. O., Ravetz J. R., 1993, « Science for the post-normal age ». DOI(https://doi.org/10.1016/0016-3287\(93\)90022-L)].

[37] Haklay M. et al., 2023, « Citizen science and Post-Normal Science's extended peer community ». DOI(https://doi.org/10.1016/j.futures.2023.103178)].

[38] Jagosh J. et al., 2015, « A realist evaluation of community-based participatory research: partnership synergy, trust building and related ripple effects ». DOI(https://doi.org/10.1186/s12889-015-1949-1)].

[39] Lucero J. E. et al., 2020, « Engage for Equity: The Role of Trust and Synergy in Community-Based Participatory Research ». DOI(https://doi.org/10.1177/1090198120918838)].

[40] Gilfoyle M., MacFarlane A., Salsberg J., 2022, « Conceptualising, operationalising, and measuring trust in participatory health research networks ». DOI(https://doi.org/10.1186/s13643-022-01910-x)].

[41] Yu S. et al., 2025, « Researching or researching with the public? A systematic review on knowledge co-production through citizen science ». DOI(https://doi.org/10.1093/scipol/scae053)].

[42] Israel B. A. et al., 2026, « Community-Based Participatory Research: Evolution and Significant Developments ». DOI(https://doi.org/10.1146/annurev-publhealth-082224-022223)].

[43] Iordanou K., Antoniou A., De Vos M., 2026, « Public Trust in Science: A Systematic Literature Review ». DOI(https://doi.org/10.1007/s10805-026-09732-5)].

Tutorial — Best Practices for Media Relations

Admin — 2026-07-23T07:33:41Z

This tutorial helps organizations within the 2% for Future ecosystem and users of the Step and Go website contact the media in a simple, useful and professional manner.

Media relations do not consist of sending a press release to a large number of journalists. They consist of becoming a reliable source for a few carefully selected journalists.

A press release sent to a thousand journalists often produces zero articles. A useful phone call to one carefully selected journalist can lead to a genuine story being covered by the media.

To read all the content, log in for free to the website.

1. The Right Reflex: Help the Journalist

A journalist is short on time. They are looking for information that is clear, verifiable and interesting to their audience.

Before contacting them, ask yourself:

What is the news?
Why now?
Who is concerned?
What issue does the subject help people understand?
What concrete solution, action or experience can be shown?
What facts, figures, images or testimonials can be provided?
Why might this specific media outlet be interested?

If you do not have a clear answer to these questions, it is better to refine the angle before sending anything.

2. What Deserves Media Outreach

A media story must contain genuine news or useful information.

Good media story	Story that is too weak
Launch of a programme, event or call for participation	Internal activity with no external consequence
Result, review, new data, field experience	Vague intention or project that is still unclear
Strong testimonial, concrete solution, useful learning	Institutional message without evidence
Local, educational, scientific, social or environmental issue	Communication focused solely on the organization

A good story may be small, but it must be clear.

3. Build the Angle in One Sentence

Before making any contact, formulate the main information in a single sentence.

Example:

[Name of organization] is bringing together stakeholders from [sector] on [date] at [location] to transform [concrete problem] into [action, solution or expected result].

This sentence then serves as a guide for the press release, phone call, email and follow-up.

4. Choose the Right Journalists

A good media list is not a large list. It is a qualified list.

For each contact, note:

the media outlet;
the section;
the journalist's name;
their direct email;
their phone number, if available;
the topics they usually cover;
the date of the last exchange;
what interests them;
the next step to take.

Keep this file up to date after every exchange. One well-documented direct contact is more valuable than a massive unqualified database.

5. Adapt the Approach to the Type of Media

Media	Useful angle	Indicative lead time
Daily newspaper, radio, TV	Upcoming news, event, fieldwork, testimonial	10 days to 3 weeks in advance
Weekly publication	Prepared subject, clear angle, resources ready	3 to 4 weeks in advance
Monthly publication	In-depth feature, trend, profile, report	3 to 6 months in advance
Quarterly publication	Long-form subject, investigation, thematic feature	3 to 6 months in advance

These lead times are not absolute rules. They are intended to help you contact the journalist while they can still make a decision.

6. Phone First, Then Email: the Most Effective Method

For priority media outlets, begin with a short call.

Purpose of the call:

check that the subject fits the section;
state the news in one sentence;
propose a concrete angle;
ask whether the journalist would like to receive the materials;
agree on a next step: email, interview, visit, video call, photos, press kit.

After the call, send a short email with the press release in the body of the message. The PDF may be attached, but it should never replace text that can be read directly.

7. Short Email Template

Subject:
[Main information in one line]

Hello [First name],

I am contacting you because you cover topics related to [theme, territory or section].

[Name of organization] is announcing [clear news] on [date] at [location]. The subject may be of interest to your readers because [concrete reason].

I can send you the press release, press kit and visuals, and arrange an interview with [name / role].

Kind regards,

[Signature]
[Mobile]
[Email]
[Link to press resources]

8. The Press Release

The press release announces the news. It must be short, clear and directly usable.

It must answer very quickly:

Who?
What?
When?
Where?
Why?
How?
For whom?

The first sentence must provide the essential information. Avoid general introductions such as: “In a changing world...”

Prefer:

[Name of organization] is launching on [date] at [location] a programme intended for [audience] to address [concrete problem].

The press release must contain:

an informative title;
a short standfirst;
three very clear opening paragraphs;
a useful quote;
practical information;
a press contact;
a link to the resources.

9. The Press Kit

The press kit supplements the press release. It must not overwhelm the journalist.

It is used to provide:

the context;
key figures;
dates;
confirmed partners;
spokesperson biographies;
available quotes;
photos, videos, logos and credits;
useful links;
answers to sensitive questions.

The press kit must remain a resource. The main message must always be conveyed through direct contact, the email and the press release.

10. The Media Kit

Prepare a simple online folder containing:

the press release in copyable text;
the press kit in PDF;
high-resolution photos;
logos;
portraits;
captions;
credits;
usage rights;
press contacts.

Do not overload the email with large files; provide a clear link to the resources, unless they amount to only 2 attachments, in which case it is preferable to provide everything as attachments.

11. Preparing a Journalist's Field Visit

Before a journalist visits, clarify the subject with them.

Prepare:

the exact subject you want them to understand;
the people to interview;
the interesting scenes to observe;
the schedule;
permissions for images and quotations;
the exact name of the organization to be mentioned;
the correct website and public contact number.

Make a simple moral agreement:

The field offers several angles. For us, the important point is [central subject]. I therefore suggest that you meet [person / group] in order to cover this aspect properly.

The journalist remains free to choose their angle. Your role is to help them avoid missing the point.

Of course, all this work will have been pointless if your on-site team talks about another subject, so speak directly with the colleagues who will receive the journalist.

12. Radio, Television, Print Media: Useful Reflexes

Radio

Prefer a telephone interview when travelling adds nothing.
Have a quick discussion before going on air about the planned questions.
Prepare three simple messages.
Speak in short sentences.

Television

Propose visual scenes, not explanations alone.
Show people in action.
Plan the locations, sounds, gestures, objects and images.
Anticipate what the camera can actually film.

Print Media

Provide facts, figures, tellable stories, quotes and photos.
Freelance journalists (paid per article) can be good contacts because they actively look for stories.
For local media, always connect the subject to the territory.

13. Asking for a Review Without Antagonizing the Journalist

Do not ask to review the article in order to control the style or point of view.

You may request a factual check:

As the subject includes scientific elements and issues requiring precision, could we review only the technical facts, names, figures and quotations? We will not intervene in the tone or journalistic angle.

This wording protects accuracy without challenging the journalist's independence.

14. Following Up Without Being Overly Insistent

A follow-up must provide useful information.

Good reasons to follow up:

a date is approaching;
a result has just been obtained;
someone is available for an interview;
photos or videos are ready;
the journalist had shown interest.

Avoid:

“Did you receive my press release?”
“When are you going to publish?”
“Our management is waiting for your response.”
repeated follow-ups with no new information.

15. After the Event: Do Not End the Relationship

Once the event has taken place, the angle can become:

the results achieved;
the lessons learned;
participation figures;
testimonials;
the next steps;
the local or sectoral impact;
the opening to other partners.

Then propose an interview by video call or telephone with someone who experienced or led the action.

16. Becoming a Regular Source

The best media relationships are built over time.

To become a useful contact:

respond quickly;
provide reliable information;
suggest experts;
share resources even when they are not exclusively about you;
point out the limitations of the subject;
sometimes direct journalists toward other serious actors;
simply thank them after publication.

A journalist returns to people who genuinely help them.

17. The Monthly or Quarterly Press Release

A monthly or quarterly press release is not used solely to request an article.

It can position Step and Go, 2% for Future or your organization as a regular source of ideas for journalists.

In one page, it can present:

emerging subjects;
upcoming events;
projects to follow;
people available for interviews;
field locations that can be visited;
useful data or trends;
important deadlines.

It is a story-sourcing tool: it helps newsrooms identify subjects before they become urgent.

18. AI and Document Production

AI can help prepare a press release, press kit or list of questions.

However, all generated text must be reviewed by a responsible person before distribution.

Systematically check:

names;
roles;
dates;
locations;
figures;
partners;
quotations;
links;
impact claims;
wording that is overly promotional.

Never send AI-generated text without human review.

19. What to Avoid

Poor practice	Why avoid it
Send the same message to every journalist	The subject appears untargeted
Oversell with adjectives	This reduces credibility
Hide limitations	The journalist may lose trust
Send a large PDF without text in the email	The message becomes difficult to process
Be unreachable after sending	The opportunity may disappear
Confuse media coverage with advertising	The journalist retains their independence
Demand a particular angle or title	This damages the relationship
Forget photo credits	The media outlet may refuse the image
Fail to update the media list	The team loses its memory of contacts

20. Measure What Matters

Do not measure only the number of articles.

Also consider:

the quality of the angle;
the accuracy of the information reproduced;
the presence of the important messages;
the quotes used;
the media outlets that are genuinely relevant;
the requests received after publication;
the journalist relationships strengthened;
the lessons for the next action.

After each campaign, update the shared file.

Checklist Before Sending

The news can be expressed in one sentence.
The targeted media outlet is genuinely concerned.
The right journalist has been identified.
The email subject announces the information.
The press release is in the body of the email.
The PDF is light and useful.
The visuals are available through a link.
The photo credits are clear.
The spokespersons are ready.
The quotations have been approved.
The figures have been verified.
The press contact is reachable.
The planned follow-up provides genuine value.
The media list will be updated after the exchange.

Phrase to Remember

Good media relations do not seek to force an article. They provide the journalist with clear, verifiable and useful information, at the right time, with the right people available.

PROMPTS

Press Release Prompt

Hold an internal meeting or interview and record it
Provide the existing documents, the recording, and YOUR MANUAL COMMENTS in the prompt
Generate the Press Release using the prompt
Read it again and correct it systematically; you have saved time, so in return, provide genuine value, reality and authenticity.

You are a senior consultant in

You are a senior consultant in media relations, institutional communication, impact strategy, journalistic writing and news storytelling. Your mission is to generate a professional, ready-to-use press release based on three sources of information: 1. The complete history of this chat concerning the project; 2. The documents attached to this chat; 3. The clarification provided below by the operator regarding what must be communicated. OPERATOR'S CLARIFICATION REGARDING WHAT MUST BE COMMUNICATED [Paste the precise instruction here: announcement, launch, result, event, call for contributions, partnership, publication, report, appointment, review, response to a news event, etc.] FINAL OBJECTIVE Produce a press release that can be used directly by the organization, without excessive promotional language, without invention, with a clear journalistic structure, a strong media angle, verifiable facts, usable quotations and all the information a journalist needs. The press release must capture attention immediately. Journalists receive too many emails and have very little time. The text must therefore announce the news in the first sentence, make the angle obvious from the opening lines, and enable the reader to understand the essentials effortlessly. The press release must tell a news story, not merely present a project. It must set out: - the problem; - the context; - the issue at stake; - what is changing now; - the proposed solution; - the actors taking action; - the concrete next steps. WORKING METHOD TO APPLY 1. Analyse the complete chat history You must reread and use all relevant information already contained in the project history: - origins of the project; - objectives; - actors involved; - partners; - dates; - locations; - figures; - results; - issues; - audiences concerned; - contextual elements; - previously approved vocabulary; - strategic positioning; - important wording; - key messages already produced; - risks of misunderstanding; - messages to avoid; - level of project maturity; - expected call to action. 2. Analyse the attached documents You must use the attached documents to extract: - factual information; - figures; - exact names; - official titles; - dates; - locations; - partners; - important quotations or wording; - the official description of the project or organization; - useful contextual elements; - evidence, data, appendices or resources that may interest the media. If information in the documents contradicts the chat history, you must briefly flag this before proposing a harmonized version. 3. Identify the journalistic angle Before writing, you must determine the most relevant angle for journalists. You must explicitly formulate: - the main news; - why this information deserves to be communicated now; - who is taking action; - what is being announced; - when it is happening; - where it is happening; - why it matters; - what is new; - what is concrete; - what is verifiable; - which problem is being addressed; - which solution is being proposed; - which type of media outlet may be interested: local, national, specialist, business, institutional, scientific, environmental, social, international press, etc. 4. Build a clear journalistic narrative The press release must follow a simple, readable and effective narrative progression: 1. The news immediately. 2. The problem or tension that makes this news important. 3. The context explaining why this is happening now. 4. The issue at stake for the people, organizations, territories or sectors concerned. 5. The solution or action being announced. 6. The evidence: figures, dates, partners, results, verifiable facts. 7. The quotation that provides human or strategic meaning. 8. The concrete next steps. 9. Practical information and the press contact. The text must not begin with a general introduction, an abstract vision, an institutional formula or an overly broad contextual sentence. The first sentence must announce the essential information. Examples of effective opening sentences: - “[Organization] is launching on [date] in [location] a programme designed to [concrete objective].” - “[Organization] today publishes [report / study / call] to address [concrete problem].” - “[Organization] is bringing together [actors concerned] on [date] in order to [concrete action].” - “[Organization] today opens [call / programme / event] to [audience concerned].” Examples of opening sentences to avoid: - “In a rapidly changing world…” - “For several years, issues relating to…” - “Faced with contemporary challenges…” - “Innovation is now at the heart of…” - “True to its values, the organization…” 5. Answer the key journalistic questions quickly The key questions must be answered within the first three paragraphs: - Who? - What? - When? - Where? - Why? - How? - For whom? - With whom? - What is changing in concrete terms? The first paragraph must announce the essential information. The second paragraph must set out the problem, context and issue at stake. The third paragraph must present the solution, concrete action, beneficiaries, partners, data or next steps. 6. Follow the rules of a professional press release The press release must: - begin with the essential information; - use the inverted-pyramid structure; - answer the key journalistic questions within the first three paragraphs; - remain factual; - avoid slogans, superlatives and advertising language; - limit jargon; - provide elements that a journalist can reuse directly; - contain one or two credible quotations; - include the important data; - include practical information; - include an “About” section; - include a press contact; - be publishable as written. 7. Write with action verbs You must replace passive formulations with active constructions wherever possible. Avoid: - “An initiative is being launched by…” - “An event will be organized…” - “A reflection will be conducted…” - “A contribution is expected…” - “A dynamic will be established…” Prefer: - “[Organization] launches…” - “[Organization] organizes…” - “[The partners] bring together…” - “[The programme] supports…” - “[The call] invites…” - “[The initiative] enables…” - “[The participants] will build…” - “[The project] responds to…” 8. Replace nominal style with verbs You must avoid overly nominal, abstract or administrative sentences. Avoid: - “The launch of a process to structure collaborations…” - “The establishment of support for stakeholders…” - “The creation of a space for dialogue…” - “The contribution to improving governance…” - “The development of an impact dynamic…” Prefer: - “[Organization] structures collaborations…” - “[The programme] supports stakeholders…” - “[The event] brings together decision-makers and practitioners…” - “[The project] improves governance…” - “[The partners] develop an impact dynamic…” 9. Prioritize concrete, concise and evocative writing The text must be lively without becoming promotional. It must prioritize: - concrete facts; - visible actions; - human subjects; - precise verbs; - short sentences; - short paragraphs; - useful figures; - concrete consequences; - understandable examples. Avoid: - long abstract sentences; - empty institutional formulas; - accumulations of concepts; - endless lists; - promotional adjectives; - abstract nouns without action; - internal expressions that an external reader cannot understand. 10. Invent nothing You must not invent: - figures; - names; - dates; - partners; - attributed quotations; - results; - amounts; - contacts; - legal statuses; - links; - institutional commitments; - impact promises. If information is missing, use a clear bracketed field: [to be completed: name of press contact] [to be completed: telephone number] [to be completed: exact figure] [to be completed: link to the media kit] [to be verified: exact date] [to be verified: partner confirmed for public communication] 11. Distinguish facts, objectives and projections You must clearly distinguish: - what has already been completed; - what has been confirmed; - what is under way; - what is planned; - what still requires funding; - what constitutes an objective; - what constitutes a hypothesis; - what constitutes a projection; - what depends on future partners or funding. Never present an objective as a result that has already been achieved. 12. Managing quotations If quotations exist in the documents or chat history, you may reuse them or improve them slightly while preserving their meaning. If no approved quotation exists, propose quotations ready for approval, clearly marked as proposals: “[Proposed quotation to be approved by Name, position]” Quotations must: - be short; - be human; - not repeat the title; - provide meaning, responsibility, vision or interpretation; - be reusable by a journalist; - contain an action verb or concrete image where possible; - avoid institutional expressions of satisfaction. Avoid: “We are very pleased to launch this innovative initiative.” Prefer: “This programme responds to a very concrete difficulty: stakeholders want to cooperate, but they often lack a common framework for transforming their ideas into fundable and measurable actions.” 13. Target length Produce a press release of between 300 and 600 words. If the subject is highly institutional or complex, you may write up to 700 words, but only if this improves clarity. The text must remain dense, readable and immediately usable. 14. Expected tone The tone must be: - journalistic; - clear; - restrained; - credible; - professional; - active; - concrete; - evocative; - institutional when necessary; - accessible to a journalist who is not yet familiar with the project. Avoid: - “revolutionary”; - “unique in the world” unless explicitly proven; - “exceptional”; - “incredible”; - repeated use of “innovative” without justification; - repeated use of “ambitious” without concrete evidence; - “systemic transformation” without a simple explanation; - overly long sentences; - abstract paragraphs; - passive formulations; - excessive nominalizations; - internal vocabulary that the media cannot understand. 15. Mandatory self-review before final output Before delivering the final press release, you must silently review it using the following checklist: - Does the first sentence announce the news immediately? - Do the first three paragraphs answer Who? What? When? Where? Why? How? - Is the problem clear? - Is the context understandable? - Is the issue at stake concrete? - Does the solution appear quickly? - Have passive sentences been replaced with active constructions wherever possible? - Have abstract nouns been replaced with action verbs wherever possible? - Does the title genuinely communicate the news? - Can a journalist understand the press release in less than one minute? - Is unverified information placed in brackets? - Does the text avoid slogans and superlatives? - Does the quotation add something beyond an expression of satisfaction? EXPECTED OUTPUT FORMAT Begin with a short diagnostic section, then provide the ready-to-use press release. Exact output structure: I. DIAGNOSTIC BEFORE WRITING 1. Main news selected [Formulate in 2 to 4 lines. The sentence must clearly state what is happening.] 2. Recommended journalistic angle [Formulate in 3 to 6 lines. Explain why this information may interest a journalist now.] 3. Problem, context, issue at stake, solution Problem: [Formulate in 1 to 2 lines] Context: [Formulate in 1 to 2 lines] Issue at stake: [Formulate in 1 to 2 lines] Announced solution: [Formulate in 1 to 2 lines] 4. Priority media audiences [Short list] 5. Missing information or information to verify [Short list only if necessary] II. READY-TO-USE PRESS RELEASE FOR IMMEDIATE RELEASE [Clear, informative, news-oriented title, using an action verb where possible] [Subtitle / standfirst: a short sentence summarizing the issue, scope or key figure] [City], [date] — [First sentence: immediately announce the essential information. State who is doing what, when and where where possible.] [End of the first paragraph: explain very quickly why and for whom.] [Second paragraph: set out the problem, context and issue at stake. Use concrete sentences with action verbs.] [Third paragraph: present the solution, the announced action, the method, beneficiaries, partners, data or next steps.] “[Short, human and reusable quotation],” says [Name, position]. “[Optional second sentence giving the meaning, responsibility or scope of the announcement].” [Next paragraph: operational details, timetable, call for participation, event, report, registration, access, next steps.] [Additional paragraph if necessary: partners, territorial, scientific, economic, social or international dimension.] About [Name of organization] [Short presentation in 4 to 6 lines: mission, status, history, field of action and key figures if available. Use action verbs and avoid overly abstract institutional wording.] Press contact [Name] [Position] [Telephone] [Email] [Website] [Link to media kit / visuals / reference page] III. SHORT VERSION FOR EMAILS TO JOURNALISTS Proposed subject: [Clear, informative and news-oriented email subject] Hello, [First sentence: immediately explain why you are writing and what the news is.] [Second sentence: explain why this may interest the journalist or their media outlet.] [Third sentence: state what is available: press release, press kit, visuals, interview, figures, report.] [Sentence indicating availability for an interview or further information.] Kind regards, [Signature] IV. TITLE VARIATIONS Propose 5 title variations: 1. Institutional title 2. General-public title 3. Specialist-media title 4. Impact / society-oriented title 5. Event or call-for-participation-oriented title Each title must: - clearly announce the news; - avoid slogans; - use an action verb where possible; - remain understandable out of context. V. CHECKLIST BEFORE SENDING Provide a short checklist of the elements to verify before distribution: - the first sentence immediately announces the news; - the first three paragraphs answer Who? What? When? Where? Why? How?; - the problem is clear; - the context is useful; - the issue at stake is concrete; - the solution appears quickly; - passive sentences have been reduced; - action verbs replace nominal formulations; - names are correct; - positions are correct; - dates are correct; - locations are correct; - figures have been verified; - quotations have been approved; - links are correct; - press contacts are complete; - visuals are available; - photo rights have been clarified; - any embargo is indicated; - any required translation has been planned. FINAL CONSTRAINT The press release must be directly copyable and usable by the operator after validation of any fields placed in brackets. The text must be self-contained, understandable without knowing the chat history, and sufficiently precise to be reused by a journalist. The press release must prioritize information, action and clarity. It must avoid a slow introduction, generalities, passive formulations, nominal abstractions and institutional sentences that delay access to the news.

Press Kit Prompt

Same quality and authenticity methodology.

WARNING: a press kit will often not be necessary and could have the opposite effect (making things complicated and reducing the number of media outlets covering the story to zero).

You are a senior consultant in

You are a senior consultant in media relations, institutional communication, impact strategy, journalistic writing and press kit design. Your mission is to generate a professional, ready-to-use PRESS KIT based on six sources of information: 1. The complete history of this chat concerning the project; 2. The documents attached to this chat; 3. The clarification provided by the operator regarding what must be communicated; 4. The previously generated press release; 5. The corrected / approved press release; 6. The document or instructions describing the differences between the initially generated press release and the corrected press release. OPERATOR'S CLARIFICATION REGARDING WHAT MUST BE COMMUNICATED [Paste the precise instruction here: announcement, launch, result, event, call for contributions, partnership, publication, report, appointment, review, response to a news event, etc.] INITIALLY GENERATED PRESS RELEASE [Paste the initial press release here or indicate the corresponding attached document] CORRECTED / APPROVED PRESS RELEASE [Paste the corrected press release here or indicate the corresponding attached document] DIFFERENCES BETWEEN THE INITIAL PRESS RELEASE AND THE CORRECTED PRESS RELEASE [Paste the differences, comments, corrections or annotations here, or indicate the corresponding attached document] FINAL OBJECTIVE Produce a press kit that can be used directly by the organization, complements the corrected press release, uses no excessive promotional language, invents nothing, and provides a clear journalistic structure, verifiable facts, usable quotations, useful figures, media resources, contextual information and everything a journalist needs. The press kit must enable a journalist to: - understand the announcement quickly; - verify the facts; - place the project in context; - identify the actors; - access figures, dates, resources and quotations; - know whom to contact; - reuse passages directly in an article; - access visuals, logos, portraits, infographics or reference documents. WORKING METHOD TO APPLY 1. Analyse the complete chat history You must reread and use all relevant information already contained in the project history: - origins of the project; - objectives; - actors involved; - partners; - dates; - locations; - figures; - results; - issues; - audiences concerned; - contextual elements; - previously approved vocabulary; - strategic positioning; - important wording; - key messages already produced; - risks of misunderstanding; - messages to avoid; - level of project maturity; - expected call to action; - practical information; - previously approved communication style. 2. Analyse the attached documents You must use the attached documents to extract: - factual information; - figures; - exact names; - official titles; - dates; - locations; - partners; - important quotations or wording; - the official description of the project or organization; - useful contextual elements; - evidence, data, appendices or resources that may interest the media; - any limitations, precautions or information that must not be overinterpreted. If information in the documents contradicts the chat history, you must briefly flag this before proposing a harmonized version. 3. Use the corrected press release as the primary source The corrected / approved press release is the priority source for: - the main angle; - the level of language; - the facts retained; - sensitive wording; - vocabulary choices; - approved quotations; - the information to emphasize; - the information to minimize or avoid. The initial press release must not be reused mechanically. It must serve only to understand how the writing evolved, which mistakes must be avoided and which choices were made in the corrected version. 4. Use the differences between the initial and corrected press releases You must analyse the differences between the initial version and the corrected version to understand: - what was removed; - what was reworded; - what was added; - what was considered too promotional; - what was imprecise; - what was too long; - what was too institutional or too vague; - what lacked evidence; - what risked being misleading; - the tone ultimately preferred; - the operator's editorial decisions. These differences must guide the writing of the press kit. The press kit must extend the corrected version, not return to the flaws of the initial version. 5. Identify the exact role of the press kit The press kit must not repeat the press release. It must supplement it. It must provide: - additional context; - useful explanations; - key figures; - a project fact sheet; - spokesperson biographies; - additional quotations; - a timetable; - practical information; - the partners and their roles; - media resources; - visual usage rights; - a clear presentation of the organization; - press contacts. 6. Determine the journalistic angle of the press kit Before writing, you must explicitly formulate: - the main news; - why this information deserves to be communicated now; - what the press kit adds to the press release; - who is concerned; - what is new; - what is concrete; - what is verifiable; - which media outlets may be interested: local, national, specialist, business, institutional, scientific, environmental, social, international press, etc. 7. Invent nothing You must not invent: - figures; - names; - dates; - partners; - attributed quotations; - results; - amounts; - contacts; - legal statuses; - links; - institutional commitments; - impact promises; - nonexistent media resources. If information is missing, use a clear bracketed field: [to be completed: name of press contact] [to be completed: telephone number] [to be completed: exact figure] [to be completed: link to the media kit] [to be completed: photo credit] [to be completed: link to HD visuals] [to be completed: exact position] [to be verified: partner confirmed for public communication] 8. Distinguish facts, objectives and projections You must clearly distinguish: - what has already been completed; - what has been confirmed; - what is under way; - what is planned; - what still requires funding; - what constitutes an objective; - what constitutes a hypothesis; - what constitutes a projection; - what is conditional on future partnerships or funding. Never present an objective or ambition as a result that has already been achieved. 9. Managing quotations If approved quotations exist in the corrected press release, you must reuse them as a priority. If additional quotations exist in the history or documents, you may propose them if they are consistent with the corrected press release. If no approved additional quotation exists, propose quotations ready for approval, clearly marked as proposals: “[Proposed quotation to be approved by Name, position]” Quotations must: - be short; - be human; - be directly usable; - not repeat the title; - provide meaning, responsibility, vision or interpretation; - remain consistent with the tone of the corrected press release. 10. Expected style The tone of the press kit must be: - journalistic; - clear; - restrained; - credible; - professional; - institutional when necessary; - accessible to a journalist who is not yet familiar with the project; - more explanatory than the press release, without becoming a complete report. Avoid: - “revolutionary”; - “unique in the world” unless explicitly proven; - “exceptional”; - “incredible”; - repeated use of “innovative” without justification; - overly long sentences; - abstract paragraphs; - endless lists; - internal vocabulary that the media cannot understand; - unmeasured impact promises; - wording that is more promotional than journalistic. 11. Target length Produce a complete but readable press kit. Indicative length: - short version: 6 to 8 pages; - standard version: 10 to 15 pages; - long version: 15 to 20 pages only if the subject is highly institutional, international, scientific or complex. In all cases, the press kit must be structured into clear sections, with headings, boxed content and directly reusable material. EXPECTED OUTPUT FORMAT Begin with a short diagnostic section, then provide the ready-to-use press kit. Exact output structure: I. DIAGNOSTIC BEFORE WRITING 1. Main news selected [Formulate in 2 to 4 lines] 2. Recommended journalistic angle [Formulate in 3 to 6 lines] 3. What the press kit adds to the press release [Formulate in 3 to 6 lines] 4. Lessons learned from the corrections to the press release [Short list: tone, wording, information removed, precautions, vocabulary to prioritize or avoid] 5. Priority media audiences [Short list] 6. Missing information or information to verify [Short list only if necessary] II. READY-TO-USE PRESS KIT PRESS KIT [Main title of the press kit] [Subtitle: announcement, issue, date, territory or scope] [Lead organization] [Date] [Link to press area or reference page: to be completed if necessary] ------------------------------------------------------------ 1. AT A GLANCE [Very short summary in no more than 5 to 8 lines] Key points: • [Main fact] • [Date / location] • [Number of participants / countries / organizations if available] • [Audiences concerned] • [Result already achieved or clearly identified objective] • [Next step] • [Useful link] Press contact: [Name] [Position] [Telephone] [Email] ------------------------------------------------------------ 2. PRESS RELEASE Insert the corrected / approved press release here. FOR IMMEDIATE RELEASE [Title of the corrected press release] [Standfirst] [City], [date] — [Complete text of the corrected press release] About [organization] [Approved boilerplate] Press contact [Contact details] ------------------------------------------------------------ 3. WHY THIS ANNOUNCEMENT NOW? [Explain the immediate context] [State why the announcement is being made now] [Present the problem, opportunity or need to which it responds] [Clarify what is changing today] [Avoid generalities and remain connected to the announced news] ------------------------------------------------------------ 4. THE PROJECT / INITIATIVE Official name: [Name] Lead organization: [Name, status, country] Objective: [Main objective] Audiences concerned: [Audiences] Method: [How it works] Results already achieved: [Confirmed results only] What is under way: [Elements under way] Next steps: [Timetable] What remains to be built: [Elements not yet finalized, if relevant] ------------------------------------------------------------ 5. CONTEXT AND ISSUES [Present the general context useful to the journalist] [Explain the problem or need addressed by the project] [Provide the available trends or contextual elements] [Connect the project to social, scientific, economic, environmental, educational, institutional or territorial issues, as appropriate] [Do not turn this section into an advocacy document or manifesto] ------------------------------------------------------------ 6. WHAT IS NEW OR DISTINCTIVE [Explain what distinguishes the announcement] [Clarify the genuine novelty] [Present what the project contributes in concrete terms] [Do not use “unique”, “first” or “unprecedented” without evidence] ------------------------------------------------------------ 7. KEY FIGURES • [Figure 1 + source or origin] • [Figure 2 + source or origin] • [Figure 3 + source or origin] • [Figure 4 + source or origin] • [Figure 5 + source or origin] If the figures are projections, state this clearly: • [Projection / objective: cautious wording] ------------------------------------------------------------ 8. TIMETABLE [Date] — [Completed / confirmed / planned stage] [Date] — [Completed / confirmed / planned stage] [Date] — [Completed / confirmed / planned stage] [Date] — [Completed / confirmed / planned stage] Clearly distinguish: - past stages; - confirmed stages; - planned stages; - deadlines that remain indicative. ------------------------------------------------------------ 9. PARTNERS AND ACTORS INVOLVED [Partner 1] — [Confirmed role] [Partner 2] — [Confirmed role] [Partner 3] — [Confirmed role] Note: mention only partners approved for public communication here. If some partners are being considered but have not been confirmed, use cautious wording or exclude them. ------------------------------------------------------------ 10. AVAILABLE QUOTATIONS Main quotation from the corrected press release: “[Approved quotation]” — [Name], [position], [organization] Proposed additional quotation: “[Proposed quotation to be approved]” — [Name], [position], [organization] Partner / expert / field quotation, if available: “[Quotation]” — [Name], [position], [organization] ------------------------------------------------------------ 11. AVAILABLE SPOKESPERSONS [Name] Position: Organization: Expertise: Languages: Available for: Contact via: [Name] Position: Organization: Expertise: Languages: Available for: Contact via: ------------------------------------------------------------ 12. QUESTIONS / ANSWERS FOR JOURNALISTS Question 1: [Likely question from a journalist] Answer: [Short, factual and cautious answer] Question 2: [Likely question] Answer: [Answer] Question 3: [Sensitive question or risk of misunderstanding] Answer: [Clear and controlled answer] Question 4: [Question about financing, impact, partners or governance] Answer: [Factual answer, without extrapolation] ------------------------------------------------------------ 13. AVAILABLE MEDIA RESOURCES HD photos: [Link to be completed] Logos: [Link to be completed] Spokesperson portraits: [Link to be completed] Infographics: [Link to be completed] Videos: [Link to be completed] Reference documents: [Link to be completed] Reference webpage: [Link to be completed] Conditions of use: [Indicate any rights, credits and restrictions] Photo credits: [Credits to be completed] ------------------------------------------------------------ 14. ABOUT [ORGANIZATION] [Presentation in no more than 8 to 12 lines] Include only verified elements: - mission; - status; - history; - field of action; - presence; - key figures if available; - institutional recognition if verified; - website. Website: [Link] Social media: [Links] ------------------------------------------------------------ 15. PRESS CONTACT [Name] [Position] [Mobile telephone] [Email] [Availability] [Organization] [Website] [Link to press area] III. SHORT VERSION OF THE PRESS KIT FOR EMAILS TO JOURNALISTS Proposed subject: [Clear and informative subject] Hello, [Short accompanying message, in no more than 6 to 10 lines, explaining that the press release is accompanied by a press kit, why the subject may interest the journalist, which resources are available and who can be contacted.] The press kit includes: - the complete press release; - key figures; - the context; - spokespersons; - media resources; - available visuals; - press contacts. Kind regards, [Signature] IV. TITLE VARIATIONS FOR THE PRESS KIT Propose 5 variations: 1. Institutional title 2. General-public title 3. Specialist-media title 4. Impact / society-oriented title 5. Event or call-for-participation-oriented title V. RECOMMENDED STRUCTURE FOR THE ONLINE MEDIA KIT Propose a media kit folder structure: /01_Press-release /02_Press-kit-PDF /03_HD-Images /04_Logos /05_Portraits /06_Infographics /07_Videos /08_Reference-documents /09_Spokesperson-bios /10_Credits-and-rights For each folder, briefly indicate what it should contain. VI. CHECKLIST BEFORE DISTRIBUTION Provide a short checklist of the elements to verify before distribution: - names; - positions; - dates; - locations; - figures; - approved quotations; - approved partners; - links; - press contacts; - visuals; - photo credits; - usage rights; - PDF file size; - any English version; - consistency with the corrected press release; - removal of elements from the initial press release that were corrected or discarded. FINAL CONSTRAINT The press kit must be directly copyable and usable by the operator after validation of any fields placed in brackets. The text must be self-contained, understandable without knowing the chat history, and sufficiently precise to be reused by a journalist. The corrected press release is authoritative. The press kit must expand upon it, place it in context and provide supporting resources, without contradicting it or reintroducing the flaws of the initial press release.

EXEMPLES

Exemple de Communiqué de Presse Genève Capitale de l'Impact

Sample Press Release Geneva Impact Capital

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Best Practices for Media Relations With a Quarterly Press Release

Admin — 2026-07-23T07:33:38Z

A quarterly press release is not intended to request an article. It is intended to help you become a useful source for journalists.

Its role is simple: to announce in advance the subjects, field opportunities, spokespersons and resources that may interest editorial teams over the next three months.

A good quarterly press release does not say “talk about us.” It says: “here are useful subjects you can cover.”

To read all the content, log in for free to the website.

1. Think Like an Editorial Team

Before writing, ask a single question:

What subject could help a journalist prepare an article, interview, report or feature?

A good subject must have:

a date or period;
a clear angle;
a reason to cover it now;
people available for interview;
verifiable facts;
available resources.

Avoid:

the organization's complete agenda;
internal news with no public interest;
vague announcements;
promises without evidence;
texts that talk only about the organization.

2. Select Only a Few Subjects

The quarterly press release must remain short.

Choose 3 to 6 subjects maximum.

For each subject, retain only what helps the journalist:

why the subject is timely;
what story they can tell;
what is visible or verifiable;
who can speak;
which resources are ready.

A weak subject should be removed or kept for later.

In exceptional cases, for topics that are of long-term significance, a previously major topic may reappear as a minor topic in a subsequent quarterly press release.

3. Send It Before the Quarter Begins

The quarterly press release is intended to anticipate.

A good rhythm:

prepare the following quarter during the preceding month;
send it before the beginning of the quarter;
follow up according to the deadlines;
take media lead times into account.

Type of media	Useful lead time
Daily newspaper, radio, TV	Approximately 10 days to 3 weeks in advance
Weekly publication	3 to 4 weeks in advance
Monthly publication	3 to 6 months in advance
Quarterly publication	3 to 6 months in advance

Avoid:

sending it after the subject has already passed;
contacting a monthly publication as though it were a daily outlet;
waiting until everything is perfect;
forgetting media production deadlines.

4. Use a Useful Title

The title must announce the content of the document.

Good examples:

Subjects to Follow From October to December on Learning Through Impact Projects
Media Agenda: Field Opportunities, Projects and Spokespersons Available This Quarter
3 Subjects to Follow This Quarter on Impact Projects

Avoid:

Our News This Quarter
An Exceptional Dynamic Serving Impact
Step and Go Revolutionizes Training

The journalist must immediately understand that they are receiving story ideas, not a newsletter.

5. Present Each Subject as a Mini Fact Sheet

Simple structure:

Subject 1 — [Clear title]

Why now:
[One sentence about the news, date or context.]

Possible angle:
[What the journalist can cover.]

What is concrete:
[Event, field opportunity, figures, people, result, experiment.]

Available to the media:
[Interview, visit, photos, data, press kit, contact.]

This structure avoids long paragraphs and requires precision.

6. Adapt the Angle to the Media Outlet

The same subject may interest several media outlets, but not for the same reasons.

Media	Possible angle
Local press	What is happening in the territory
Education press	What this changes for learners
Business press	Skills, employment, entrepreneurship
Environmental press	Climate, biodiversity, transition
Society press	Young people, engagement, inclusion
Innovation press	Method, experimentation, tools

Avoid:

sending the same angle to everyone;
contacting a section without checking the subjects it covers;
assuming that an “impact” subject will automatically interest every media outlet.

7. Speak as a Source, Not as a Requester

The right tone:

We are bringing these subjects to your attention because they may inform your editorial choices.

The wrong tone:

Thank you for sharing our information.

Do:

propose;
provide insight;
provide contacts;
supply resources;
allow the journalist to choose their angle;
remain available.

Avoid:

demanding an article;
imposing a title;
applying pressure;
following up without new information.

8. Create Clear Deadlines

A journalist can make a decision more easily when a date exists.

Examples:

public presentation on 12 October;
field visit available from 20 to 24 November;
registration open until 15 September;
results available from 3 December;
spokesperson available during the week of 10 December.

Avoid:

“soon”;
“shortly”;
“in the coming months”;
“under way” without a date;
no concrete appointment.

9. Prepare the Resources Before Sending

Before distributing the release, check that everything is ready:

reachable press contact;
exact names and positions;
available spokespersons;
verified figures;
usable photos;
photo credits;
usage rights;
links to useful pages;
clarified sensitive information.

Avoid:

proposing an unconfirmed interview;
citing an unapproved partner;
announcing an uncertain figure;
sending a temporary link;
providing images without credits.

10. Put the Text in the Body of the Email

The journalist must be able to read the essentials without opening an attachment.

Good practice:

main text in the email;
lightweight PDF as a supplement;
link to press resources;
visible direct contact.

Avoid:

“please find the press release attached”;
PDF only;
a large file;
a link without a summary;
sending a Word document without prior contact.

11. Follow Up for a Genuine Reason

A follow-up must add something.

Good follow-ups:

“The presentation takes place on Friday, and it is still possible to come and film.”
“The results are now available.”
“A spokesperson can respond tomorrow morning.”
“The HD photos are ready.”
“Two participants come from your region.”

Avoid:

“did you receive my email?”;
“when are you going to publish?”;
following up every two days;
calling to force a response;
insisting without any new information.

12. State Clearly What Is Confirmed

A quarterly press release can announce future subjects, but it must remain reliable.

Distinguish between:

confirmed;
planned;
in preparation;
subject to confirmation;
result achieved;
target objective.

Avoid:

presenting an ambition as a result;
announcing an unconfirmed partner;
promising an uncertain event;
using “unique”, “first” or “unprecedented” without evidence.

13. Write Briefly and Actively

Prefer action verbs.

Good examples:

Step and Go brings together...
Participants design...
The programme supports...
The partners test...
The presentation will showcase...

Avoid:

A dynamic will be implemented...
A reflection will be conducted...
The promotion of the activities will be carried out...

The style must be clear, concrete and quick to read.

14. Establish a Regular Appointment

The quarterly press release works when it becomes a useful habit.

Do:

always send it during the same period;
maintain a stable structure;
record journalists' reactions;
update the media list;
simply thank them after publication;
prepare the following quarter as soon as the current release has been sent.

Avoid:

sending it once and then abandoning it;
changing the format every time;
losing the feedback received;
forgetting interested journalists.

Short Template

FOR MEDIA INFORMATION

[Title]
Subjects to Follow From [month] to [month] [year] on [main theme]

During the next quarter, [organization] will make several subjects, field opportunities, spokespersons and resources available to journalists concerning [issue].

Subject 1 — [Clear title]

Why now:
[One sentence.]

Possible angle:
[One sentence.]

What is available:
[Interview / figures / field opportunity / visuals / press kit.]

Subject 2 — [Clear title]

Why now:
[One sentence.]

Possible angle:
[One sentence.]

What is available:
[Interview / figures / field opportunity / visuals / press kit.]

Press Resources
[Link to media kit / photos / webpage.]

Press Contact
[Name]
[Position]
[Mobile]
[Email]

Checklist Before Sending

The document remains short.
Each subject has a date or period.
Each subject proposes a clear angle.
The information has been verified.
Uncertain subjects are clearly identified.
The spokespersons are available.
The visuals are ready.
The photo credits are indicated.
The text is in the body of the email.
The media list is segmented.
The follow-up provides genuine value.
The next release is already planned.

Phrase to Remember

A successful quarterly press release gives journalists a useful head start on the subjects they may cover.

Prompt

Here is a prompt to help you draft the basic outline of your quarterly press release. It's up to you to ensure the accuracy and authenticity of the information (in exchange for saving time, deliver quality content).

You are a senior consultant in

You are a senior consultant in media relations, institutional communication, editorial strategy, journalistic writing and the design of quarterly press releases. Your mission is to generate a professional, ready-to-use QUARTERLY PRESS RELEASE based on the information available in: 1. the complete history of this chat concerning the project, the organization, the events, the actions, the partners and the audiences concerned; 2. the documents attached to this chat; 3. any clarifications provided below by the operator. OPERATOR'S CLARIFICATION [Paste the specific instructions here: quarter concerned, organization, subjects to highlight, events to announce, priority media audiences, countries or territories, links, constraints, desired tone, information to avoid, etc.] QUARTER CONCERNED [Example: October-November-December 2026] ORGANIZATION / PROGRAMME CONCERNED [Name of the organization, programme, initiative or ecosystem concerned] OBJECTIVE OF THE QUARTERLY PRESS RELEASE The quarterly press release must not be a standard press release. It is not intended solely to secure an immediate article. It is intended to position the organization as a useful, reliable and regular source for journalists. It must tell journalists: “Here are the subjects that will become interesting over the next three months, here is why, here are the possible angles, here are the people available for interview, and here are the available resources.” The press release must help an editorial team prepare: - an article; - an interview; - a report; - a feature; - a radio segment; - a television story; - a column; - local, sector-specific or national coverage. It must not resemble an institutional newsletter, an internal agenda or a promotional brochure. WORKING METHOD 1. Analyse the chat history You must identify within the history: - ongoing projects; - upcoming events; - recent results; - calls for participation; - final presentations; - field locations available for visits; - available people; - confirmed partners; - useful figures; - important dates; - possible media angles; - previously approved contextual elements; - wording to prioritize; - sensitive or uncertain information. 2. Analyse the attached documents You must extract from the documents: - factual information; - dates; - locations; - exact names; - partners; - events; - results; - figures; - available press resources; - contacts; - links; - any visuals; - useful contextual elements. If information is missing or appears uncertain, do not invent it. Place it in brackets: [to be completed: exact date] [to be completed: press contact] [to be verified: confirmed partner] [to be completed: link to visuals] [to be completed: exact figure] 3. Select the subjects Select only subjects that may interest a journalist. Choose a maximum of 3 to 6 subjects. For each subject, check that it contains at least several of the following elements: - a news item; - a date or period; - a public, local, educational, scientific, economic, social or environmental issue; - a concrete angle; - a person available to speak; - a visible field location, event or experience; - a figure or verifiable fact; - an available media resource; - a next step. Exclude subjects that are too internal, too vague or too promotional. 4. Build each subject as a mini press fact sheet Each subject must be presented briefly and usefully. Mandatory structure for each subject: Subject [number] — [Clear title] Why now: [One sentence explaining the date, deadline, context or reason for discussing it this quarter.] Possible angle: [One sentence explaining what the journalist can cover.] What is concrete: [Event, field location, result, figures, people, experiment, presentation, call, publication.] Available to the media: [Interview, visit, visuals, figures, press kit, spokesperson, report, webpage, contact.] 5. Adapt the media angles For each subject, propose several angles where possible according to the media: - local press; - national press; - specialist press; - education press; - business press; - environmental press; - society press; - innovation press; - radio; - television; - international press where relevant. Do not provide every angle if it is not useful. Prioritize the most realistic ones. 6. Create clear deadlines The press release must help journalists make decisions quickly. Clearly indicate: - event dates; - periods when field visits are possible; - presentation dates; - dates when results will be published; - registration deadlines; - spokesperson availability; - relevant times for filming, interviewing or publishing. Avoid vague wording: - “soon”; - “in the next few months”; - “upcoming”; - “under way” without further details. 7. Write as a useful source, not as a requester The tone must be: - informative; - restrained; - useful; - professional; - journalistic; - concrete; - non-promotional. The press release must encourage the journalist to retain the organization as a regular source. Absolutely avoid: - “thank you for sharing”; - “we are counting on your support”; - “revolutionary initiative”; - “exceptional event”; - “unique in the world” unless explicitly proven; - “we are delighted to”; - lengthy institutional presentations; - unproven superlatives; - unmeasured impact promises. 8. Write briefly and actively Use short sentences. Prioritize action verbs: - brings together; - launches; - publishes; - presents; - tests; - supports; - opens; - invites; - reports back; - organizes; - makes available; - documents. Avoid passive and nominal formulations: - “a dynamic will be implemented”; - “a reflection will be conducted”; - “the promotion will be carried out”; - “the establishment of support”. 9. Distinguish what is confirmed from what is planned You must clearly distinguish: - confirmed; - planned; - in preparation; - subject to confirmation; - result achieved; - target objective; - projection; - hypothesis. Never present an ambition as a result. Never cite an unconfirmed partner as though they were committed. 10. Provide for press resources The press release must indicate the available resources or those to be completed: - press contact; - telephone; - email; - webpage; - media kit; - HD photos; - photo credits; - usage rights; - logos; - portraits; - spokespersons; - reports; - figures; - FAQ; - reference documents. If the resources are not available, indicate: [to be completed: link to media kit] [to be completed: HD photos] [to be completed: photo credits] EXPECTED OUTPUT FORMAT Begin with a short diagnostic, then provide the ready-to-use quarterly press release. Exact output structure: I. DIAGNOSTIC BEFORE WRITING 1. Quarter concerned [Indicate the selected quarter] 2. Role of the quarterly press release [Explain in 2 to 3 lines why this press release serves as an editorial resource for journalists] 3. Subjects selected [List the 3 to 6 selected subjects, with one sentence explaining the reason for each] 4. Subjects excluded or postponed [Short list only if necessary, with the reason: too vague, insufficiently dated, unconfirmed, too internal, lack of evidence] 5. Priority media outlets [Short list: local press, specialist press, radio, TV, business press, education press, etc.] 6. Missing information or information to verify [Short list only if necessary] II. READY-TO-USE QUARTERLY PRESS RELEASE FOR MEDIA INFORMATION [Clear title] Subjects to Follow From [month] to [month] [year] on [main theme] [Short standfirst] During the next quarter, [organization] will make several subjects, field opportunities, spokespersons and resources available to journalists concerning [main issue]. Subject 1 — [Clear title] Why now: [One sentence] Possible angle: [One sentence] What is concrete: [One or two sentences] Available to the media: [Interview / field visit / visuals / figures / press kit / contact] Subject 2 — [Clear title] Why now: [One sentence] Possible angle: [One sentence] What is concrete: [One or two sentences] Available to the media: [Interview / field visit / visuals / figures / press kit / contact] Subject 3 — [Clear title] Why now: [One sentence] Possible angle: [One sentence] What is concrete: [One or two sentences] Available to the media: [Interview / field visit / visuals / figures / press kit / contact] [Add Subject 4, Subject 5 or Subject 6 only if necessary] Press resources [Media kit / photos / reports / webpage / useful links] Available spokespersons [Name, position, subject on which the person can speak] [Name, position, subject on which the person can speak] Press contact [Name] [Position] [Mobile] [Email] [Website] [Link to press area] III. SHORT EMAIL VERSION FOR SENDING TO JOURNALISTS Proposed subject: [Clear, useful and informative subject] Hello [First name], [First sentence: announce that the organization is making several subjects available for the quarter.] [Second sentence: state the general theme in one sentence and explain why it may interest the media outlet.] [Sentence including the 2 or 3 subjects most relevant to this journalist.] [Sentence indicating the available resources: interviews, field visits, visuals, figures, press kit.] I remain available should you wish to receive a more targeted angle, arrange an interview or prepare a story. Kind regards, [Signature] IV. EMAIL SUBJECT VARIATIONS Propose 5 subjects: 1. Subject for local press 2. Subject for national press 3. Subject for specialist press 4. Subject for radio / TV 5. General subject Each subject must be short, clear and focused on the story, not promotional. V. FOLLOW-UP PLAN Propose a simple follow-up plan: - follow-up 1: when and why; - follow-up 2: only if a new element exists; - field or event follow-up: if a date is approaching; - results follow-up: after an event or presentation. Never propose an empty follow-up such as “did you receive my email?”. VI. CHECKLIST BEFORE SENDING Check: - the press release remains short; - each subject has a date or period; - each subject has a journalistic angle; - the subjects are confirmed or identified as planned; - the partners cited have been approved; - the figures have been verified; - the spokespersons are available; - the press resources are ready; - the photo credits are indicated; - the text is in the body of the email; - any PDF is lightweight; - the media list is segmented; - the follow-up provides genuine value; - the information in brackets is completed before sending. FINAL CONSTRAINT The result must be directly usable by the operator after the fields in brackets have been checked. The text must remain concise, clear, concrete, free of repetition and without promotional language. The quarterly press release must give journalists a useful head start on the subjects they may cover, rather than asking them to relay institutional communication.

Exemples de Communiqués de Presse Trimestriels

Exemple Com Press Europe Mars Avril 2009

Exemple Com Press Europe Mai 2009

Exemple Com Press Trim Canada Mai 2009

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Stakeholders in the ecological transition (non-profit and private sectors)

Tiphaine Riaux — 2026-07-23T07:25:15Z

🌊"Waves of Change" Hackathon Program

Modules for Ecological Transition Stakeholders (Associative and Private Sectors)

Réunion Island, 2–6 November 2026

As part of the exceptional edition of the Participatory Science Hackathon for the SDGs on Réunion Island, several stand-alone modules are available for ecological transition professionals->https://www.training-for-development.com/En-Novembre-Hackathon-Vagues-de-changement-a-la-Reunion].

Environmental transition stakeholders, however diverse they may be, all face the same challenges: difficulties in engaging people around the ecological transition; existing data that is fragmented, incomplete, or disconnected from local realities; and decisions that often lack territorial grounding and scientific legitimacy...

To overcome these challenges, participatory science provides a powerful solution.

The "Waves of Change" Participatory Science Hackathon offers dedicated modules specifically designed to help ecological transition stakeholders address these issues.

As an ecological transition stakeholder, join these modules and leave with:
(Free participation upon mandatory registration)

Practical methods to structure and improve the reliability of local environmental data collection
Effective techniques for engaging communities over the long term in biodiversity monitoring and field observation programs
Strategies for grounding your environmental transition projects in a recognized and collaborative scientific approach
Case studies and firsthand experiences from organizations that have successfully integrated participatory science into their initiatives
A deeper understanding of current trends and best practices in citizen science applied to environmental challenges
Opportunities to connect and exchange ideas with other environmental transition stakeholders, NGOs, and local authorities
A firsthand look at the projects developed during the Hackathon during the final showcase, providing inspiration and practical models for your own initiatives

Economic actors in development

Tiphaine Riaux — 2026-07-23T07:23:38Z

🌊"Waves of Change" Hackathon Programme

Modules for Economic Development Stakeholders

As part of the exceptional edition of the Participatory Science Hackathon for the SDGs on Réunion Island, several stand-alone modules are available for economic development professionals->https://www.training-for-development.com/En-Novembre-Hackathon-Vagues-de-changement-a-la-Reunion].

As environmental, social, and economic transformations reshape our territories, economic development stakeholders are facing major challenges: supporting businesses through their transitions, strengthening territorial attractiveness, anticipating changes across economic sectors, developing new skills, and fostering more resilient economic models.

Meeting these challenges requires new approaches based on collaboration, knowledge sharing, and the active involvement of all stakeholders.

This is where integrating participatory science activities becomes especially valuable.

In this context, the Participatory Science Hackathon is far more than a meeting point for researchers, citizens, project leaders, and economic stakeholders: it is a space for collective exploration to identify new opportunities, share solutions, and build new synergies around impact-driven innovation.

The "Waves of Change" Participatory Science Hackathon offers dedicated modules specifically designed to help economic development stakeholders address these challenges.

As an economic development stakeholder, join these modules and leave with:
(Free participation upon mandatory registration)

Practical methods for identifying economic opportunities emerging from participatory science projects
Strategies for integrating local scientific and environmental data into your territorial development initiatives
A better understanding of emerging economic models related to the blue economy, sustainable finance, and impact-driven innovation
Case studies and feedback from project leaders who have successfully transformed scientific initiatives into economic activities
Practical guidance for supporting or financing impact projects emerging from participatory approaches
Opportunities to connect and exchange with other economic stakeholders, funders, and impact project leaders
A firsthand look at the projects developed during the Hackathon's final presentation, offering inspiration and potential investment opportunities

Tourism stakeholders (public, non-profit, and private)

Tiphaine Riaux — 2026-07-23T07:23:25Z

🌊 "Waves of Change" Hackathon Programme

Modules for Tourism Stakeholders (Public, Non-profit and Private Sectors)

Réunion Island, 2–6 November 2026

As part of the exceptional edition of the Participatory Science Hackathon for the SDGs on Réunion Island, several stand-alone modules are open to tourism professionals->https://www.training-for-development.com/En-Novembre-Hackathon-Vagues-de-changement-a-la-Reunion].

Over the past few years, the tourism sector has undergone profound changes, driven by evolving traveller expectations. Increasingly, visitors are seeking experiences that are environmentally responsible, socially meaningful and respectful of the destinations they visit.

To meet these new expectations, tourism professionals face a dual challenge: diversifying their offers while contributing to the development of genuinely sustainable tourism. It is no longer enough to promote sustainability through marketing messages alone. Concrete, measurable and coherent actions are now essential to address today's sustainable development challenges and contribute to the Sustainable Development Goals (SDGs).

Tour guides, tour operators and tourism organisations have a unique opportunity to play a key role in this transition. Their daily presence in the field, privileged access to natural environments (beaches, lagoons, forests, etc.) and close relationship with visitors position them as valuable contributors to the understanding and preservation of local ecosystems.

Participatory science provides a practical way to turn this potential into action.

The "Waves of Change" Participatory Science Hackathon offers dedicated modules for sustainable tourism stakeholders, specifically designed to address these challenges.

As a tourism professional, join these modules and leave with:
(Free participation upon mandatory registration)

Practical methods for integrating participatory science protocols into your tours, excursions and tourism activities
Techniques for engaging your visitors as active contributors to scientific data collection (biodiversity, oceans and natural environments)
Ideas for developing a distinctive tourism offer based on genuine and verifiable scientific contributions
Case studies and feedback from tourism operators who have already integrated participatory science into their activities
A better understanding of current visitor expectations regarding responsible and sustainable tourism
Networking opportunities with other sustainable tourism professionals and environmental conservation stakeholders
First-hand insights into the projects developed during the Hackathon through the final project presentations, providing inspiration for your own initiatives

Low-tech and participatory sciences: two complementary approaches

Admin, Tiphaine Riaux — 2026-07-23T07:22:41Z

Low-tech empowers people to do. Participatory sciences empower them to understand, document and share what they do. Together, they transform a hands-on activity into a knowledge project — structured, testable and transmissible.

🔧 What participatory sciences add to a low-tech activity

🗂️A method for moving from a "workshop" to a genuine "project"

A low-tech training can teach participants how to build a solar oven, a water filter, an irrigation system, a simple sensor, a repaired object or a lightweight housing solution.

Participatory sciences allow us to go further and invite participating audiences to contextualise their designs and take an interest in the effects they produce. Integrating a participatory sciences approach into a low-tech activity means asking:

✅ what problem do we want to solve?
✅ for which audience?
✅ how do we verify that the solution works?
✅ with what success criteria?
✅ how do we document the results?

The activity thus no longer limits itself to producing an object, but allows us to contextualise its role as well as its effects within a broader environment. By integrating participatory sciences, low-tech activities are then transformed into structured, testable and replicable projects.

🎓An expanded pedagogical stance

Technical training in the low-tech field provides both the practical expertise specific to the discipline and the learning methods specific to it.

The Participatory Sciences Step One training operates at a different level. It helps supervisors, facilitators, trainers, teachers, researchers, project leaders and advanced participants to design activities in which audiences are not merely beneficiaries, but progressively become:

✅ observers;
✅ investigators;
✅ contributors;
✅ transmitters;
✅ and sometimes even co-authors of the project.

This makes it possible to act on participant engagement and not simply offer training "for them", but to progressively build an approach "with them".
With a participatory sciences approach, the person is not merely "trained", they are recognised as a holder of useful knowledge. Combining participatory sciences and low-tech is also an opportunity to recognise the knowledge of communities, indigenous knowledge and ancestral practices as fully-fledged scientific knowledge.

🌱Skills development and participant empowerment

Low-tech activities welcome different people with different ambitions.
In a low-tech activity, some people come to discover, others to meet an immediate need, and others quickly show a desire to go further.
Participatory sciences make it possible to create differentiated pathways.

For example, among participants in a low-tech activity, some may become:

✅ workshop leads;
✅ facilitators for other groups;
✅ peer trainers;
✅ co-designers of new prototypes;
✅ links between several communities;

The practical autonomy that low-tech initially offers is complemented by participatory sciences, which organise the growing responsibility of participants.
Indeed, participatory sciences add another dimension: they enable participants to understand, explain, document and transmit.
From an individual, personal and professional standpoint, the benefits of this approach are numerous. They strengthen:

✅ self-confidence;
✅ self-image;
✅ the ability to speak up;
✅ the ability to train others;
✅ access to associative, professional or entrepreneurial opportunities.

The dimension of simple technical facilitation is transcended and transformed into a genuine capacity-building pathway.

📊A resource for producing useful data

A low-tech activity can be very concrete, yet difficult to evaluate if what it actually produces is not documented. By integrating a citizen science or participatory research dimension, low-tech workshops can become spaces for collecting data that is useful both to the organisation itself and to society at large. Integrating a "participatory sciences dimension" into one's activity allows for collectively asking concrete questions such as:

✅ what are the actual uses of the manufactured object?
✅ what is its lifespan?
✅ which materials work best?
✅ what are the actual costs?
✅ what local adaptations are needed?
✅ what are the impacts on autonomy, comfort, health, energy, water or food?

An enormous amount of useful, open-source material can emerge from combining low-tech activities with participatory sciences: improved prototypes, technical sheets, explanatory videos...
Ultimately, the improvement of low-tech can be made possible by field experience, and not solely by initial technical expertise.

🌍A link between science, technology and society

Low-tech often responds to concrete needs: water, energy, food, housing, mobility, health, material autonomy... Universal needs, often urgent ones.

The Participatory Sciences Step One training makes it possible to connect these everyday realities to broader challenges: climate adaptation, public health, territorial resilience, social inclusion, SDGs...

This goes beyond simply giving the low-tech workshop a deeper dimension; it ensures that it is not viewed merely as a technical space, but also as a venue for dialogue among citizens, organizations, local governments, researchers, engineers, funders, and institutions.
By breaking down the barriers between science, technology, and society, participatory science enables low-tech projects to emerge as as genuine impact projects.

👥A training that is equally useful for supervisors and advanced participants

The Step One training can be aimed at two levels.

First, at supervisors : facilitators; low-tech trainers; social workers; mediators; teachers; association managers; engineers; researchers; project coordinators.
It enables them to better design, facilitate, document and promote their activities.

But it can also be aimed at the most engaged participants.
For example, members of a low-tech programme or laboratory can take the Step One training in order to in turn become:

✅ links;
✅ co-facilitators;
✅ trainers;
✅ workshop coordinators;
✅ project leaders;
✅ social entrepreneurs;
✅ documentation managers;
✅ community mediators.

This is an important distinction: participatory sciences do not only serve to improve the low-tech activity; they can enable participants to become actors in its development.

✨In brief

The complementarity between low-tech and participatory sciences is therefore not merely technical. It is first and foremost methodological and pedagogical.

Low-tech poses the question: How do we do better, simpler, more sober, more repairable, more accessible?

Participatory sciences add: How do we work with the people concerned, how do we learn together, how do we produce useful knowledge, how do we document results, how do we improve over time, how do we pass it on to others?

It is this combination that creates the power of the model.
Together, they can transform a technical activity into a project of learning, autonomy, action research, inclusion and impact.

Low-tech provides concrete solutions.
Participatory sciences provide the method for testing, improving, documenting, transmitting and scaling them up with the people concerned.

Study of Trends and Best Practices in Learning Through Hands-On Impact Projects

Admin — 2026-07-14T15:36:13Z

Creation, Development, Management, Evaluation and Scaling Up

Strategic Version — 14 July 2026

Scope and Framing Assumptions

This study focuses on programmes in which people learn by effectively contributing to the creation, development or management of a project aimed at generating a positive social, environmental, educational, scientific, territorial, economic or institutional impact.

It covers in particular:

initial and continuing education;
higher education;
vocational training;
hackathons and innovation laboratories;
incubation and pre-incubation;
non-profit, scientific, entrepreneurial and citizen-led projects;
career transition programmes;
leadership and governance development programmes;
programmes led by companies, local authorities, NGOs, foundations or international organizations;
projects conducted in intercultural or multi-stakeholder contexts.

The analysis pays particular attention to possible applications within the ecosystem formed around Objectif Sciences International, Step & Go, KEMENESI, 2% for the Future, Geneva Foundation for the Future and the Global Impact Projects.

The geographical scope is international, with priority given to Europe, Switzerland, France and transnational programmes.

Participatory science and teaching

Tiphaine Riaux — 2026-07-13T15:29:29Z

🌊“Waves of Change” Hackathon - Modules available specifically to teachers

Réunion Island, from 2 to 6 November 2026

As part of a partnership with the Rectorat, several modules are available individually to teachers throughout the week-long Hackathon.

In the classroom, raising awareness of scientific and environmental issues must of course succeed in providing information, but also in fostering a comprehensive understanding and lasting engagement.

In the same way, we all face the same challenges in learning more generally: to ensure that it does not take a top-down format, and thus avoid limiting the appropriation of knowledge, we all use our imagination and original techniques to capture students' involvement. The objective is for them not only to understand the concepts, but also to make them their own.

To successfully meet these everyday challenges, Participatory Science is a powerful lever.

The “Waves of Change” Participatory Science Hackathon offers modules dedicated to teachers, specifically designed to address these issues.

As a teacher, attend these modules and leave with:
(Free participation, registration required)

Methods for using Participatory Science in support of the school curriculum
Facilitation techniques and methods for managing classroom dynamics around scientific projects
Ways to integrate interdisciplinary skills (science, humanities, arts, digital technology...)
Case studies and feedback from teachers who have already carried out this type of project
Keys to understanding current issues in science education and public awareness
Practical guidance on empowering young people through Participatory Science
A network for exchanging with other teachers and stakeholders in science education
Direct access to the projects developed during the Hackathon at its final presentation, ready to use and also able to serve as models for your own initiatives.

Training for Development

Applications — Careers, Impact Projects & Participatory Science

Can data from citizen science, Participatory Science and participatory research be trusted?

1. A good or bad question that has become historically structuring

2. Ontology: what exactly is “participatory data”?

3. Epistemology: trust, truth, validity and quality are not synonymous

4. Objectivity is not the absence of humans

5. The central principle: fitness for purpose

6. What empirical comparisons between volunteers and professionals show

7. The case of water: a particularly instructive laboratory

8. The real sources of fragility in participatory data

9. QA/QC: trust can be engineered technically

10. Statistics: noise does not prevent inference

11. Quantity does not, however, replace quality

12. Documentation, provenance and open science

13. A persistent difficulty: perceived quality is not measured quality

14. The institutional problem: accepting data also means accepting an unusual producer

15. Participatory data and international indicators

16. Participatory research: when participants are no longer merely collectors

17. Framing error: a dimension often absent from discussions of quality

18. Relational trust and scientific quality become interdependent

19. 2025–2026 research: towards an integrated conception of scientific and social outcomes

20. An integrated matrix of trust in participatory data

21. Towards a trust score rather than a binary label

22. What science now allows us to assert

Conclusion

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Extended scientific and technical bibliography

A. Foundations, definitions and structuring of the field

B. Epistemological foundations, objectivity, expertise and trust

C. Data quality: reviews and methodological frameworks

D. Empirical validation studies in ecology and biodiversity

E. Participatory water monitoring

F. Air quality, sensors and low-cost measurements

G. Citizen science, public policy, governance and SDGs

H. Participatory research, CBPR, co-production and scientific quality

I. Metadata, interoperability, provenance and open science

J. Core literature to prioritize for a literature review

Tutorial — Best Practices for Media Relations

1. The Right Reflex: Help the Journalist

2. What Deserves Media Outreach

3. Build the Angle in One Sentence

4. Choose the Right Journalists

5. Adapt the Approach to the Type of Media

6. Phone First, Then Email: the Most Effective Method

7. Short Email Template

8. The Press Release

9. The Press Kit

10. The Media Kit

11. Preparing a Journalist's Field Visit

12. Radio, Television, Print Media: Useful Reflexes

13. Asking for a Review Without Antagonizing the Journalist

14. Following Up Without Being Overly Insistent

15. After the Event: Do Not End the Relationship

16. Becoming a Regular Source

17. The Monthly or Quarterly Press Release

18. AI and Document Production

19. What to Avoid

20. Measure What Matters

Checklist Before Sending

Phrase to Remember

PROMPTS

Press Release Prompt

You are a senior consultant in

Press Kit Prompt

You are a senior consultant in

EXEMPLES

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Best Practices for Media Relations With a Quarterly Press Release

1. Think Like an Editorial Team

2. Select Only a Few Subjects

3. Send It Before the Quarter Begins

4. Use a Useful Title

5. Present Each Subject as a Mini Fact Sheet

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