The Rationale for FAIR Open Research Data
Research activities provide unlimited amounts of data that could have an impact on achieving the objectives of a number of seamless research processes. With all the information and data available, it is important that your data are valuable and properly managed. By taking care of these matters at an early stage, your research will stand out and foster new promising integrative scientific approaches and studies.
In this context, FAIR Data Principles (Findable, Accessible, Interoperable, Reusable) can help you create, share and re-use quality, valuable, and responsible data. Only by leveraging and applying the evidence about FAIR data impact we can help data live up to its long-term potential.
FAIR open data will be able to support both quality and smooth research workflow for the sciences and new discoveries and reproducibility of findings based on data interoperability, harvest and analysis of multiple datasets.
Addressing the challenge of interoperability of findable and accessible data is essential to unlocking the full potential of re-usable research data. Basically, interoperability requires the use of open shared standards (community agreements) to enable horizontal platforms to become communicable, operable, and programmable across services. This vision reflects the strategic directions recently provided by : COAR Next Generation Repositories (report, 2017), Knowledge Exchange “The evolving landscape of Federated Research Data Infrastructures” (report, 2017), OECD Global Science Forum and CODATA “Business Models for Sustainable Research Data Repositories” (report, 2017).
The good news is that more and more research organizations enable interoperability through open-source applications and common guidelines/recommendations/agreements. Nevertheless, the reality remains that data interoperability and re-use are still largely hampered by a technological framework with proprietary gates and by data silos.
To facilitate open data creation, integrations, interoperability, re-use, engagement and new knowledge discoveries, a well-known initiative European Open Science Cloud (EOSC) encourages all stakeholders to work together in an inclusive, transparent and accountable way on the implementation of a digital platform inspired by the FAIR principles, to uptake unprecedented insight of FAIR open data promises.
TOWARDS FAIR RESEARCH PROCESSES IN AGRICULTURE & RELATED SCIENCES
To address issues, challenges and opportunities connected with “FAIR principles to all elements of the research process in agricultural sciences and related disciplines”, the Interest Group on Agricultural Data (IGAD) of the Research Data Alliance (RDA) had a IGAD Pre-conference meeting that held on March 19-20, 2018, in Berlin, Germany.
This pre-event took place before the 11th RDA Plenary Meeting, March 21-23, 2018, Theme: "From Data to Knowledge". The 2.5-day RDA Plenary meeting provided the ideal, neutral and trustworthy forum to discuss the opportunities and challenges of a global data ecosystem of best practices, standards and interoperable data infrastructures fostering cross-disciplinary knowledge and innovation. |
In the frame of the IGAD pre-meeting, all IGAD Working Groups (WGs) reported about their activities undertaken during the last six months. In particular, March 20, 2018 was dedicated to the WGs already associated to IGAD and to those under evaluation, such as “Capacity Development”:
6. Capacity Development (under evaluation) | |
IGAD highlights : | |
The two-day IGAD pre-meeting helped all participants to better envision the range of actual applications and potential roadblocks for managing, describing and making research data findable, accessible, interoperable and reusable, - in view of emerging innovations, trends and technologies.
In this context, the IGAD pre-meeting mapped use-cases (that are either underway or in the process of being developed) of FAIR principles, their strengths to uncover new opportunities for collaboration to promote Open Science and foster international FAIR research data networks.
The pre-meeting was an opportunity to exchange views and share experience on the challenges and perspectives in expanding the current vision of data-driven research into Open Science landscape fully driven by the FAIR data principles.
Co-chairs of the Interest Group on Agriculture Data (IGAD) Research Data Alliance (RDA)
PUTTING INTEGRATED RESEARCH DATA & KNOWLEDGE TO PRODUCE FAIR OPEN SCIENCE
FROM INSPIRATION TO ACTION :
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With gratitude,
AIMS Team
