Abstract
Citizen Science (CS) is a prominent field of application for Open Science (OS), and the two have strong synergies, such as: advocating for the data and metadata generated through science to be made publicly available [ 1 ]; supporting more equitable collaboration between different types of scientists and citizens; and facilitating knowledge transfer to a wider range of audiences [ 2 ]. While primarily targeted at CS, the EU-Citizen. Science platform can also support OS. One of its key functions is to act as a knowledge hub to aggregate, disseminate and promote experience and know-how; for example, by profiling CS projects and collecting tools, resources and training materials relevant to both fields. To do this, the platform has developed an information architecture that incorporates the public participation in scientific research (PPSR)—Common Conceptual Model ① . This model consists of the Project Metadata Model, the Dataset Metadata Model and the Observation Data Model, which were specifically developed for CS initiatives. By implementing these, the platform will strengthen the interoperating arrangements that exist between other, similar platforms (e.g., BioCollect and SciStarter) to ensure that CS and OS continue to grow globally in terms of participants, impact and fields of application.
Highlights
The Citizen Science (CS) landscape is growing rapidly, gaining new actors and expanding into more diverse fields
This model consists of the Project Metadata Model, the Dataset Metadata Model and the Observation Data Model, which were developed for CS initiatives
The European Union (EU)-Citizen.Science platform does not serve as a repository for data that have been generated by citizens participating in CS initiatives, it is worth noting that the PPSR Dataset Metadata Model (DMM) does provide a schema for describing how observations are collected, how those data may be used, and other information on the data as a whole; and the PPSR Observation Data Model (ODM) provides a schema for describing the structure of individual observations including: location, date, observer, and attributes specific to the research
Summary
The Citizen Science (CS) landscape is growing rapidly, gaining new actors and expanding into more diverse fields. In keeping with the FAIR principles (findable, accessible, interoperable, and reusable) for data handling and processing, and to ensure the interoperability of the platform with other CS platforms, and to enable the exchange of information about projects and resources via an application programming interface (API), EU-Citizen.Science has implemented: (1) the Project Metadata Model to describe CS projects, (2) the Digital Documents ontology from Schema.org (with vocabulary from Dublin Core) to describe CS resources, and (3) the Courses ontology from Schema.org to describe CS training materials This information architecture supports such network collaborations; it greatly aids the platform’s search functions for users. Through EU-Citizen.Science, Sally and James can connect with other CS projects, providing them with a wealth of experience and knowledge to build upon This helps to kick-start their own initiative and they use the open-access tools, which have been tested by others, to start collecting data on odours in their region. Once their own NGO has been set up, they add it as a new project to EU-Citizen.Science, using relevant metadata to ensure that others can find them in the same way they found D-NOSES
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