Periodic Reporting for period 2 - CS-Track (Expanding our knowledge on Citizen Science through analytics and analysis)
Okres sprawozdawczy: 2021-03-01 do 2023-01-31
CS Track was funded in the SwafS segment of Horizon 2020. It was launched in December 2019 with the purpose of broadening the knowledge on Citizen Science (CS) and its activities and projects – joint endeavors of scientists and non-scientists in pursuit of a scientific advance. CS Track sought to increase that knowledge using web-based analytics (computational analyses based on projects’ manifestations on the web and social media), questionnaires and interviews, combined in a multi-perspective analysis. Our data analytics and analysis targeted both individual and social aspects of CS, with the aim to understand complex processes and formulate policy recommendations intended to optimize CS for the society and the economy. After a 2-month extension of its original 3-year duration, on 31.1.23 CS Track reached its end as a research and innovation project.
The importance of the project for society lies on the value of the information produced for different stakeholders and policymakers. The unique mix of methods and sources used in the project has brought innovation in the content of that information, resulting in an increased added value for its users and an enhanced quality of the ensuing policy recommendations.
The project’s objectives were the following (abridged):
1. Further our understanding of the ways CS activities can have an impact on society, locally and globally.
2. Explore and characterize the interplay of CS with official science.
3. Gain understanding through the effective utilization of analytics in combination with social research methods.
4. Identify factors to characterize the specific types of discourse and approaches found in CS projects (knowledge building strategies, targets of action, etc.).
5. Translate the knowledge and findings above into recommendations for actors at all levels – policy makers, companies, NGOs, educational institutions – to raise the value of CS for science awareness and literacy and for society in general.
Already at the proposal stage, some guiding questions were set to help the project realize these objectives: Where are the relevant, interesting topics of CS activities?, What are the characteristics of participation in CS activities?, How can successful examples of CS activities be characterized?, How can CS activities be enhanced using analytics results? During the project, additional questions and emphases were adopted, focusing on subjects such as the development of a database of CS platforms and projects; devising a large survey of CS participants and interviewing experts; deciding on the ways our results should be presented to best suit the needs of our stakeholder community; how to approach CS policy; broadening the scope of our inquiry to include, e.g. CS in times of crisis and pandemic; CS and education; etc.
The project achieved its objectives, bringing important contributions: a conceptualization and categorization of CS activities; a large database (more than 50 CS platforms, almost 5,000 CS projects), used for research; several analytics tools supporting network and content analysis, developed or adapted for their novel utilization in CS research; a large survey (over 1,000 respondents); several analysis undertakings, addressing many facets of CS; the steadily improved project's website, including the eMagazine; the engagement with the target community via social media and campaigns promoting our deliverables and results, along with webinars and other dissemination events, notably the CS Track symposium organized as part of the ECSA conference in October 2022. The last portion of the project concentrated mainly on our analysis and publication of research findings and on the formulation of policy recommendations for CS practitioners and stakeholders.
The importance of the project for society lies on the value of the information produced for different stakeholders and policymakers. The unique mix of methods and sources used in the project has brought innovation in the content of that information, resulting in an increased added value for its users and an enhanced quality of the ensuing policy recommendations.
The project’s objectives were the following (abridged):
1. Further our understanding of the ways CS activities can have an impact on society, locally and globally.
2. Explore and characterize the interplay of CS with official science.
3. Gain understanding through the effective utilization of analytics in combination with social research methods.
4. Identify factors to characterize the specific types of discourse and approaches found in CS projects (knowledge building strategies, targets of action, etc.).
5. Translate the knowledge and findings above into recommendations for actors at all levels – policy makers, companies, NGOs, educational institutions – to raise the value of CS for science awareness and literacy and for society in general.
Already at the proposal stage, some guiding questions were set to help the project realize these objectives: Where are the relevant, interesting topics of CS activities?, What are the characteristics of participation in CS activities?, How can successful examples of CS activities be characterized?, How can CS activities be enhanced using analytics results? During the project, additional questions and emphases were adopted, focusing on subjects such as the development of a database of CS platforms and projects; devising a large survey of CS participants and interviewing experts; deciding on the ways our results should be presented to best suit the needs of our stakeholder community; how to approach CS policy; broadening the scope of our inquiry to include, e.g. CS in times of crisis and pandemic; CS and education; etc.
The project achieved its objectives, bringing important contributions: a conceptualization and categorization of CS activities; a large database (more than 50 CS platforms, almost 5,000 CS projects), used for research; several analytics tools supporting network and content analysis, developed or adapted for their novel utilization in CS research; a large survey (over 1,000 respondents); several analysis undertakings, addressing many facets of CS; the steadily improved project's website, including the eMagazine; the engagement with the target community via social media and campaigns promoting our deliverables and results, along with webinars and other dissemination events, notably the CS Track symposium organized as part of the ECSA conference in October 2022. The last portion of the project concentrated mainly on our analysis and publication of research findings and on the formulation of policy recommendations for CS practitioners and stakeholders.
The project has focused on data gathering and analysis mostly at the level of selected platforms, individual projects and their participants, covering many variables and indicators. The following are examples of studies we conducted and topics we explored: learning dimensions associated with participation in CS activities (a view from project descriptions triangulated with survey results and Twitter data); CS and emerging challenges in COVID times; effects of crises on CS participation; analytics-based assignment of research areas and SDGs to CS projects based on their project descriptions; educational usage of CS data; participation patterns in project forums or talk pages (role changes, interaction, moderation, rewards and incentives); insights from the CS Track survey (learning and knowledge building, ways of participation modes, motivation); learning about citizen scientists’ motivation by triangulating a computational analysis of Zooniverse forums with survey results; CS Track database – insights into the question of what types of information are usually missing in online CS platforms, and into issues of inter-platform metadata incompatibility.
Exploitation of project’s results: Besides the many publications and organized data and information we have left on the open platform Zenodo, we built our legacy on some tangible outcomes of the project that can be transferred to others for their continuation, operation and further development:
- the large database of CS platforms and projects, together with algorithms to classify CS data with analytics methods;
- technical knowledge and resources including algorithms and scripts that facilitate data gathering and anonymization;
- our website with the embedded eMagazine, with the infrastructure for its future expansion;
- the Analytics Workbench featuring a tool suite that can be accessed by different players for the study of CS projects or collections of projects;
- the knowledge base that emerged from the analysis of our large survey;
- datasets created for the various studies conducted by CS Track research teams.
Indeed, the transfer of some of the above has already been done to, and formalized in a Memorandum of Understanding with, ECSA, the European Citizen Science Association. This MoU was signed by both parties and came into effect in January 2023.
Exploitation of project’s results: Besides the many publications and organized data and information we have left on the open platform Zenodo, we built our legacy on some tangible outcomes of the project that can be transferred to others for their continuation, operation and further development:
- the large database of CS platforms and projects, together with algorithms to classify CS data with analytics methods;
- technical knowledge and resources including algorithms and scripts that facilitate data gathering and anonymization;
- our website with the embedded eMagazine, with the infrastructure for its future expansion;
- the Analytics Workbench featuring a tool suite that can be accessed by different players for the study of CS projects or collections of projects;
- the knowledge base that emerged from the analysis of our large survey;
- datasets created for the various studies conducted by CS Track research teams.
Indeed, the transfer of some of the above has already been done to, and formalized in a Memorandum of Understanding with, ECSA, the European Citizen Science Association. This MoU was signed by both parties and came into effect in January 2023.
Several directions of progress beyond state of the art showed in the project.
(1) Most literature on CS consists of individual case studies. An overview of the issues across a broader range of CS projects is still missing. CS Track developed a detailed classification of CS and CS activities along various dimensions based on a literature review, analyzing conceptualizations, definitions, categorizations and typologies of CS and its activities.
(2) CS Track’s approach of applying web-based analytics to CS is innovative and original. It goes beyond existing studies that apply more classical bibliometric measures in the analysis of the scientific productivity of CS projects, both in scope and richness of methods.
(3) A question that has received considerable attention is the identification of research areas related to specific CS projects. So far, this task has been primarily based on human coding. We have adapted the technique of “explicit semantic analysis” (ESA) to facilitate an automatic extraction of research areas using the Web of Science taxonomy as a target framework. Also, the Twitter analysis using the Lynguo tool is an original contribution to meta-level studies in CS.
(4) The study of the contribution of CS to achieving or monitoring SDG advance considerably progressed in CS Track.
(1) Most literature on CS consists of individual case studies. An overview of the issues across a broader range of CS projects is still missing. CS Track developed a detailed classification of CS and CS activities along various dimensions based on a literature review, analyzing conceptualizations, definitions, categorizations and typologies of CS and its activities.
(2) CS Track’s approach of applying web-based analytics to CS is innovative and original. It goes beyond existing studies that apply more classical bibliometric measures in the analysis of the scientific productivity of CS projects, both in scope and richness of methods.
(3) A question that has received considerable attention is the identification of research areas related to specific CS projects. So far, this task has been primarily based on human coding. We have adapted the technique of “explicit semantic analysis” (ESA) to facilitate an automatic extraction of research areas using the Web of Science taxonomy as a target framework. Also, the Twitter analysis using the Lynguo tool is an original contribution to meta-level studies in CS.
(4) The study of the contribution of CS to achieving or monitoring SDG advance considerably progressed in CS Track.