What are the Policy Challenges for the Development of Research Infrastructures for Citizen Science in Europe?
* Results and lessons learned from the project
* Recommendations for follow up actions
* Bringing the identified policy interventions to implementation
Methodology to produce the roadmap
Interim Policy Objectives and Related Gaps
Policy Objective 1: to support the development and maintenance of seamless open access to free of charge services, resources and expertise for all researchers and citizens scientists
* Relevant gap: specific to the use of citizen science within research infrastructures, research and policy reflection is limited and niche, and as such, citizen science experts report that the policy challenges identified in citizen science in general also apply to the use of citizen science in research infrastructures (Cartas, 2022). Therefore, the most important gaps to be covered to this end are related to: their openness level not only for scientific organizations, but also for citizens as scientists; sustainability; interoperability; etc.
Policy Objective 2: to support the development of open and cloud-based solution for advanced computing and data analytics in research and innovation
* Relevant gap: development of tools for data gathering, management and for knowledge extraction is fundamental to gain advantages from the large quantity of data that CS can provide. However, it implies the strict collaboration among scientists-citizens-sw developers to achieve solution that are data-centric, usable from the citizens as scientists, affordable from the economic point of view and sustainable
Policy Objective 3: to support the establishment and enlargement of an open-data space for scientists and citizens scientists
* Relevant gap: data openness to all, including citizens as scientists is an important issue to be addressed in CS. This is also related to data ownership, data traceability, data transparency, data quality, etc. This also include issues related to the development of low-cost tools and system of incentives for data gathering and sharing, as well as for data elaboration and for knowledge extraction
Policy Objective 4: to support definition of standards for both technological tools for data collection, data quality, and data sharing in CSs initiatives
* Relevant gap: this gap will be covered mainly as consequences of the policy actions foreseen for PO1-PO2-PO3. However, dedicated effort to this end it is necessary to accelerate the achievement of the policy objective
Policy Objective 5: to facilitate collaboration among researchers and citizens scientists to conduct world-class research and innovation better addressing societal goals
* Relevant gap: this is fundamental in case of frontier research due to its complexity for non-experts. Additionally, large research infrastructures governance is a complex network which constitutes another challenge for scientists-citizen scientists collaboration. This gap has to be tackled from two direction: on one side it requires significant effort to support the learning processes of the citizens scientists through capacity building strategies aimed at leveraging their knowledge and understanding on the research contents and on the way to conduct research activities; on the other side it requires to train the trainers as well as the researchers on how to approach CS initiatives and the interaction with the citizens. Benefits in closing this gap are several such as: empowerment and better engagement of citizens as scientists; more inclusivity of all categories of population; more quality and quantity data from scientific point of view; increase of trust in CS from both the scientific community and citizens point of views
Policy Objective 6: to increase the AI literacy and IT capabilities of citizens interested in science
* Relevant gap: several initiatives to cover the ICT readiness and literacy gap have been organized till now to increase inclusivity of people that are low skills. However, to support CS development and scale up it is needed a specific effort in this direction to allow all segments of population to be part of the CS initiatives This is especially visible in large research infrastructures and frontier research as technical language and tools are often more demanding than in other cases.
Policy Objective 7: to facilitate the citizens in contributing to produce of new knowledge addressing societal problems
* Relevant gap: The characteristics of large research infrastructures -namely, the advanced knowledge-base they work with, the advanced state of research they conduct, and the vast research programmes they work with- make this objective crucial for future development of CS in large research infrastructures. A Capacity buildings action plan to address this objective would be of great importance to give citizens capabilities and knowledge to explain their societal needs into research initiatives in collaboration with scientific communities. Several benefits can be gained in covering this gap which include among the others: scientifically sound evidence-based research on societal problems closer to the needs of citizens; more effective social policies; increase of citizens participation of the public debate on societal changes and SDGs
Policy Objective 8: to make citizens science more inclusive and promoting gender balance
* Relevant gap: education and training, together with empowerment strategies will help to close this gap. Several initiatives are already funded to this end, some more are needed to increase the number of citizens which can experience CS initiatives
Policy Objective 9: to support Citizens Scientists in contributing closing the gap between Science and Society
* Relevant gap: this gap will be covered mainly as consequences of the policy actions foreseen for PO5-PO6-PO7-PO8-PO10. This is also related to PO12 and with the definition of education frameworks and pathways helping citizens to increase their knowledge and capabilities in more structured ways, and, at the same time, facilitating researchers who practice CS to conduct research initiatives in more effective way. Citizen science has a proven role in strengthening research infrastructures. The European Strategy Forum on Research Infrastructures recommends the use of participatory methods - such as citizen science - to bring science and citizens closer together (ESFRI, 2020)
Policy Objective 10: to instill the culture of democratization in science and to increase society’s science capital
* Relevant gap: this gap will be covered mainly as consequences of the policy actions foreseen for PO5-PO6-PO7-PO8-PO9
Policy Objective 11: to support the definition and establishment of New Governance models and model of operation making CS a sustainable institutional practice
* Relevant gap: this is an important gap, and it is one of the most difficult to be closed. To support CS development and scale up, scientific communities need to change their behaviour and increase the trust about the value added of CS data from the scientific point of view. However, without a significant change in the governance models of the research organizations as well as in their operation processes these goals would be rather difficult to achieve. This change encompasses the development of an infrastructure for CS that establishes capacity for CS initiatives and affirms CS as a resource for scientists; the consideration of different goals of CS initiatives and how they can benefit the research programmes and the research infrastructure. It also includes the definition of career pathways for scientists who want to develop research though CS initiatives
Policy Objective 12: to support the development of Impact Assessment framework showing effectiveness of CS in evidence-based research initiatives especially for societal challenges
* Relevant gap: in a scientific community there is an initial attempt to define IA framework for CS initiatives. This is also evident in some EC funded initiatives on going. However, a clear policy effort to close this gap is fundamental for several reasons: increasing the evidence that CS results are valuable for research objectives as well as for policy objectives; increase the quantitative data available for research which use AI tools; increase trust in science of the citizens as well as the trust of scientific community in citizens as scientist; etc.
Policy Objective 13: to raise awareness among citizens as scientists and scientific communities about the significant contribution which citizens can provide in collecting valuable evidence for measuring impacts’ indicators (e.g. SDGs indicators)
* Relevant gap: this is consequence of the previous objectives with particular reference to PO12. However, dedicated communication and awareness creation strategies need to be designed to this end
Policy Objective 14: to facilitate the establishment of a Community of Citizens Scientists extending from early-school classes to senior citizens
* Relevant gap: community of citizens have been in place since years. Some other are growing thanks to EC and other initiatives. However, it is important to define clear strategies to support their establishment as well as their scale up and sustainability over the time
Policy Objective 15: to maximising the relevance and excellence of citizen science and scaling up citizen science
* Relevant gap: this gap will be covered mainly as consequences of the policy actions foreseen for PO12-PO13-PO14
Policy Objective 16: Increase the maturity level of CS in policy making processes at National level and develop an EU common approach to CS initiatives
* Relevant gap: this is a fundamental gap to be covered to make CS effective approach to address societal problems closer to the needs of the citizens. Each EU MSs has at the moment a different level of maturity in perceiving CS as valuable assets to address SDGs goals. However, increasing such level for all MSs and to reach a common understanding on what CS is and to what extent it can provide valuable contribution to society through evidence-based data and knowledge is an important step to establish a common approach to develop CS at EU level. This objective is of utmost relevance for large research infrastructures and fundamental research due to the difficulty of grasping the practical relevance of this research for non-experts
Do you agree with such policy objectives and gaps? Do you want to change/add any?
Interim Policy Challenges
Data quality and management
* Large research infrastructures and domains such as astrophysics are characterised by the production and use of a massive amount of data. The creation of large datasets, thanks to activities like monitoring, observing, and crowdsourcing, create a series of implications both for citizens and for professionals
* Citizens often might not have the necessary training, and much of the work falls on the professional figures (data scientists especially)
* Data harmonisation and collected for specific purposes
Administration and governance
* Fostering a supportive ecosystem for citizen science is a key task and challenge for policymakers
* In relation to funding, citizen science projects have different funding needs to traditional scientific projects
* Depending on the topic, there are different level of barriers to participation in citizen science projects. This is especially true for minorities and underserved communities
* The development and regulation of citizen science could help to improve equity of access and participation in both science and education in informal learning environments
* Different actors may have different goals (students, teachers, researchers, institutions)
* Tensions may arise due to the dissimilar interests of scientific and public stakeholder groups in the wider field of public participation in scientific research
* Moving beyond gathering specimens and analysing data, citizens have the capacity to be immersed in the entire scientific process in citizen science projects
* The three types of citizen science are contributory, collaborative and co-created, with differing levels of citizen involvement and responsibility in each (Bonney et al., 2009)
* Co-created citizen science involves the highest degree of citizen participation and requires two-way dissemination to succeed
* Not many projects reflect on the use of citizen science, but just on the challenges of the topic they are investigating from time to time
* Terminology fundamental here: “citizen science” should incorporate more aspects of public engagement in science and not be described as only “individual measurement and data collection”
* Topic is very important, too. Some topics are more suitable than others for citizen science frameworks
* Citizen science should encourage individuals to take an active role in their communities - especially on projects focusing on environmental activism and climate change
Formal and informal learning environments
* In learning environments, the learner acquires pre-determined knowledge and values
* In citizen science he/she learns continuously through active citizenship, which may result in social transformations
* In citizen science activities, practitioners, and participants may not be able to retain their usual roles in some learning environments
* Informal learning environments are still somewhat underestimated
* Not many projects reflect on the use of citizen science, but just on the challenges of the topic they are investigating from time to time
* Terminology fundamental here: “citizen science” should incorporate more aspects of public engagement in science and not be described as only “individual measurement and data collection”
* Topic is very important, too. Some topics are more suitable than others for citizen science frameworks
Do you agree with such policy challenges? Do you want to change/add any?
Interim Policy Recommendations
1-Introducing citizen science in educational strategy
* Support the harmonization of educational strategies developed by research organizations across EU Member States, and continue to downstream resources to EU Member States and Regions on related policy domains and provide funding schema for educational pathways on CS
* Promote a system that values the impact of research organisations and scientists on society encompassing the engagement in CS initiatives and the collaboration with other institutions for CS initiatives, such as schools
2-Boosting evaluation and monitoring of citizen science
* Ensure the alignment between actions taken on CS impact assessment and EU policy domains, such as environmental policy, science and technology, digital transformation, and regional development
* Define the primary goal of the CS initiative and monitor and evaluate the initiative accordingly
3-Including educators in program design
* Design and implement training activities aimed at training the trainers of citizens interested in CS. Encourage co-design of educational programs for citizens which are interested in CS. Support inclusive educational programme for CS initiatives
4-Community establishment, scale-up, sustain and engagement
* Support the harmonization of initiatives aimed at establishing, scaling-up, sustaining, and engaging communities taken by research organizations across EU Member States. Ensure the collaboration between said initiatives toward a EU-wide community. Support the development and collection of guidelines and good practices
* Focus on understanding the background knowledge needed by citizen scientists and implement adaptive approaches to CS projects to facilitate and sustain the engagement, such as scaffolding
* Follow adaptive approaches to ensure sustained engagement and ensure collaboration with local communities to co-define how to improve the research organisation's presence in society
5-Boost digital technology
* Promote the development or adoption of standards and good practices on the development of digital solutions for CS. Incentivize the development of guidelines for the development of digital solutions for CS, such as accessibility guidelines. Encourage innovation in the development of digital solutions for CS, such as new business models. Encourage the development of digital solutions for CS that are interoperable between them and with existing portals to streamline data workflows
6-Support the adoption of technical instruments
* Support initiatives increasing the level of use of technology by citizens scientists. Support awareness activities and incentives for motivating citizens interested in science in using technological instruments in CS projects. Promote actions reducing cost of technical instruments used in CS initiatives. Support initiatives increasing ICT literacy of citizens interested in science projects. Support the increase of readiness level of citizens and facilitating ICT inclusion initiatives
* Develop training frameworks on data-sharing tools for citizen scientists, seeking funding opportunities also among digital skills programmes. Support and incentivize continuous learning among scientists focusing on using technical instruments to disseminate data in an inclusive way, for instance making use of multi-sensoriality
7-Prioritising STEM in education
* Support initiatives introducing STEM in education. Promoting exchange of best practices of STEM in education. Increase the funding programme for STEM in education initiatives which are co-developed for supporting CS projects. Encourage the monitoring and assessment of STEM in education impacts. Design awareness and incentives for STEM in education initiatives providing contribution to CS scale-up. Foster the development of STEM educational resources that centre around the engagement of minorities and inclusivity
8-Networks and community platforms
* Stimulate collaborations in networks and communities through platforms allowing to address mutual benefits, expand capacity and leverage expertise and resources. Facilitate access to and re-use of resources on interoperability and accessibility from other domains for CS platforms
* Enhance the role of networks and community platforms for CS by seeking to establish it as key research infrastructures and attracting funds accordingly
9-New rules of attribution of scientific discoveries and merits
* Define IPR guidelines for CS projects. Promote best practices and knowledge exchange of rules and guidelines for involving citizen scientists in whole CS project life cycle. Encourage the organization of prizes and other initiatives to acknowledge the conjoint active participation of scientists and citizens interested in science in successful CS projects. Encourage the establishment of CS scientific journals
* Strive to include citizen scientists in the definition of guidelines on scientific recognition to allow for different mechanisms, such as closer relationships with scientists and/or research infrastructures as a form of recognition
* Strive to include citizen scientists in the process to include their perspectives on how they prefer to be acknowledged and recognized for their contribution
10-Incentives to open data on the side of research infrastructures
* Support the definition of incentive schemas for data sharing and opening. Support the acknowledgement of citizen scientists’ data and encourage their provision and sharing. Support the maintenance of open data infrastructure and their interoperability degree. Support the co-design and co-development of Apps for data gathering, sharing and managing that are truly adopted by the citizen scientists
11-Boost the European Open Science Cloud
* Support the establishment of an open cloud data space for CS data at EU level. Support the development of AI and ML tools for mining and interpreting CS data available in open cloud infrastructures
* Develop programs that encourage scientists to take the lead in bringing citizens closer to EOSC, such as CS projects that work with API to make citizen scientists access experiment data
* Ensure that suitable funds are harnessed by research organisations to boost EOSC, for instance facilitating access to open-data and digital skills related funds by research organisations seeking to develop training material for EOSC
12-Boosting skills on citizen science
* Develop career pathways for scientists interested in CS initiatives. Include CS topics in university curricula. Foreseen governance models of CS initiatives which are in line with the rules and regulation of the research organization in charge of the CS initiative
* Establish appropriate funding mechanisms, for instance including agile evaluation of CS programs and citizen observatories. Facilitate the connection to alternative funding opportunities suitable to specific CS projects’ domains. Align regional, national, and EU funding for CS on specific science and policy domains
* Align funding schema and CS initiative's primary goal
14-Involve policymakers throughout the project life cycle
* Seek to engage with CS projects throughout their life-cycle to ensure that CS projects’ outcomes are aligned with science and innovation policy. Develop programs to guide research organizations in the creation of CS projects that are in line with mission-based innovation. Establish or use existing frameworks to ensure that CS projects are iteratively designed and evaluated against mission-based innovation objectives
15-Continuing to pursue and encourage inclusion and diversity
* Encourage and support the development, collection, use, and dissemination of guidelines and good practices on inclusive CS. Support knowledge sharing initiatives on inclusive CS, for instance by partnering with stakeholders seeking to pursue this goal in the organization of events
* Develop tools that foster inclusion and multidimensional data analysis as a resource to enrich and augment data exploration and data analysis and train scientists for these tools
* Allocate resources with a medium- to long-term focus to ensure continuity in the development of programmes on inclusion as they need to develop new tools, gather a wide range of documentation and resources for future uses, and train both citizen scientists and scientists to approach scientific research from this perspective
16-Foster experience design to ensure motivation, sustained engagement, and inclusivity
* Support the development of training for CS experience design. Liaise communities of practice to foster knowledge exchange between the CS and the designers communities. Provide support for capability building on CS experience design, for instance allocating fundings for specific initiatives in this field
* Foster the development of initiatives that create or enhance a continuous improvement culture among CS stakeholders. Support initiatives for the meta-evaluation of CS impact assessment frameworks and tools. Ensure that the fitness-for-purpose criteria for CS impact assessment frameworks and tools include elements regarding social innovation and other relevant policies
Feasibility Analysis
The feasibility analysis provides a short qualitative description of the achievement of each policy objective and assessment of REINFORCE’s contribution toward this goal, as well as a level of feasibility.
PO1: to support the development and maintenance of seamless open access to free of charge services, resources and expertise for all researchers and citizens scientists
* Recommendations: 1, 10, 11
Short Qualitative Assessment:
REINFORCE stakeholders act as a gateway for access to expertise with a focus on large research infrastructures. The development of an infrastructure for scientific data open to citizens creates a space for scientists and citizens to access services and resources. Seamless access to expertise is still challenging and its completion relies on other POs as well.
PO2: to support the development of open and cloud-based solution for advanced computing and data analytics in research and innovation
* Recommendations: 10, 11
Short Qualitative Assessment:
The development of an open infrastructure for data in research and innovation provides the basis. Models such as SonoUno’s sonification as a service pave the way for the development of open data analytics solutions.
PO3: to support the establishment and enlargement of an open-data space for scientists and citizens scientists
* Recommendations: 5, 10, 11
Short Qualitative Assessment:
A streamlined data flow from research infrastructures to an open-data space like EOSC provides the basis. Effective use of the open-data space is tied to interoperability, skills, and acceptance of CS data by science (PO4, PO6, PO13, PO15), REINFORCE is at the forefront in linking CS and scientists in frontier research.
PO4: to support definition of standards for both technological tools for data collection, data quality, and data sharing in CS initiatives
* Recommendations: 5, 10, 11
Short Qualitative Assessment:
Benefits from international efforts in the same direction. Standardisation in CS kept relevant in the agenda by REINFORCE stakeholders. Open data platforms like EOSC take the role of facilitators.
PO5: to facilitate collaboration among researchers and citizens scientists to conduct world-class research and innovation better addressing societal goals
* Recommendations: 10, 11, 12, 13, 16
Short Qualitative Assessment:
REINFORCE stakeholders lead the endeavour within large research infrastructures, they rely on the supporting and enabling role of community platforms (Zooniverse) and open data (EOSC), and they adopt innovative and collaborative approaches to scientific research and CS itself. The nature of societal goals makes collaboration particularly challenging hence continuous adjustments are foreseen.
PO6: to increase the AI literacy and IT capabilities of citizens interested in science
* Recommendations: 6, 7, 12
Short Qualitative Assessment:
Collaborative approaches are used to develop educational projects and programmes. Continuous learning is encouraged such as EGO’s senior citizen science course.
PO7: to facilitate the citizens in contributing to produce of new knowledge addressing societal problems
* Recommendations: 5, 6, 12, 15, 16
Short Qualitative Assessment:
Solutions like SonoUno widen the basis of citizens contributing to the production of new knowledge while enriching data exploration capabilities. Platforms like EOSC grant access to data to multiple stakeholders facilitating collaboration for the creation of new knowledge. The recognition and acceptance of non-professionals’ contribution still impacts the complete achievement of this objective (PO12, 13, 15).
PO8: to make citizens science more inclusive and promoting gender balance
* Recommendations: 7, 15, 16
Short Qualitative Assessment:
Solutions like SonoUno’s sonification shows the effort needed to improve inclusivity and the possibility for great results. REINFORCE shows good practices of continuous monitoring and evaluation, this allows to adjust engagement activities for bias. Science in general still has a long way to go in achieving gender balance and inclusivity and complementary actions are needed (such as within PO6).
PO9: to support Citizens Scientists in contributing closing the gap between Science and Society
* Recommendations: 4, 12, 15, 16
Short Qualitative Assessment:
Muon detector exemplifies CS initiatives that link together society and science by recognising citizen scientists’. Recognising the merits of citizen scientists does not guarantee the achievement of the objective and outreach activities like senior citizen science at EGO may contribute, as well as collaborative approaches to CS and/or to bring the large research infrastructure activities closer to the community, as it is exemplified by Pierre Auger.
PO10: to instill the culture of democratisation in science and to increase society’s science capital
* Recommendations: 4, 10,11
Short Qualitative Assessment:
Scientists bring citizen science closer to schools. REINFORCE leads the way by showing scientists the value of CS in large research infrastructure.
PO11: to support the definition and establishment of New Governance models and model of operation making CS a sustainable institutional practice
Short Qualitative Assessment:
REINFORCE stakeholders establish a pool of scientists expert in CS among large research infrastructures to lead the adoption of CS in frontier research. This asset offers other scientists the knowledge base to engage with CS at a lower cost. The institutionalisation of CS depends on other achievements like the broader recognition of CS as a resource for science (PO12, 13, 15).
PO12: to support the development of Impact Assessment framework showing effectiveness of CS in evidence-based research initiatives especially for societal challenges
Short Qualitative Assessment:
Precedent efforts provide building blocks for effective impact assessment. REINFORCE retains the knowledge capital to lead the endeavour further in the establishment of a widely accepted framework focusing on large research infrastructures.
PO13: to raise awareness among citizens as scientists and scientific communities about the significant contribution which citizens can provide in collecting valuable evidence for measuring impacts’ indicators (e.g. SDGs indicators)
* Recommendations: 1, 2, 4, 8, 9, 11
Short Qualitative Assessment:
REINFORCE leads the way toward the acknowledgment and proof of CS as an asset for the scientific community. REINFORCE stakeholders like Zooniverse and EOSC constitute essential enablers to centralise access to distributed resources and act as repositories.
PO14: to facilitate the establishment of a Community of Citizens Scientists extending from early-school classes to senior citizens
* Recommendations: 1, 2, 4, 8, 9, 11
Short Qualitative Assessment:
REINFORCE stakeholders are in an excellent position to facilitate the connection between science and citizens through CS. Large research infrastructures mediate interaction with schools and other institutions while stakeholders such as Zooniverse provide the infrastructure. The sustainability of the community is highly delicate as it relies on engagement and funding for CS initiatives and the infrastructure.
PO15: to maximising the relevance and excellence of citizen science and scaling up citizen science
* Recommendations: 1, 2, 11, 15
Short Qualitative Assessment:
REINFORCE acts as a scale-up for CS in that it brings it within large research infrastructures. The achievement still depends on continuous improvement of CS (PO12).
PO16: Increase the maturity level of CS in policy making processes at National level and develop an EU common approach to CS initiatives
* Recommendations: 2, 14,17
Short Qualitative Assessment:
The relevance of CS for policy making benefits from examples like CERN and Deep Sea Explorers. REINFORCE stakeholders bring together international actors for a common approach to CS in large research infrastructures that goes beyond the EU. The achievement depends on the amount and quality of data gathered on the impact of CS in society (PO12).
Do you agree with such policy recommendations? Do you want to change/add any?
* What are the bottlenecks and gaps (policy and organizational) that should be considered and addressed for mainstreaming the implementation of citizen science in research infrastructures?
* What kind of instruments and incentives are necessary to tackle these gaps?
* What are the policy measures that should exist to foster the implementation of citizen science in research infrastructure?
* What actions should be put in place in order to implement such recommendations?
A Making Speeches Talk Joint!
