Some of the recent FAIRsFAIR landscape analysis deliverables are available for consultation alongside a vision for the components of a FAIR Ecosystem.
The following deliverables are now open for comments by using the Google Drive version provided below.
This document is the first iteration of three annual reports on the state of FAIR in European scientific data by the FAIRsFAIR project. The interpretation of the FAIR data principles and their implications for services are now under intense scrutiny across Europe with multiple possible outcomes. The report is based on studies of public information, especially EOSC infrastructure efforts, and on limited surveying and interviews. The focus has been on understanding the usage of persistent identifiers and semantic interoperability. This study highlights the rapidity of change in technical solutions and wide variation across scientific domains in the uptake. More efforts are needed to guide researchers in best practices.
► We are seeking wide feedback on this draft which will inform other areas of work within the FAIRsFAIR project. Comments and suggestions can be added at https://docs.google.com/document/d/1LPMpuDSyIhzYT6S3bG2KPecdDXn-af4bJxzX2r_xLIs/edit
FAIRsFAIR carried out an analysis of the current data policy landscape at various levels (national, funder, publisher, institutional) to provide a snapshot of the situation in 2019 and to identify policy elements that support or hinder FAIR data practice. To provide a comparative baseline for reviewing the data policies of various stakeholders, the priority and supporting actions presented in the Turning FAIR into Reality (TFiR) action plan were employed. To assess how well the policies of different stakeholders currently reflect TFiR’s action plan, we carried out desk research to characterise policies, undertook an analysis of responses to an open consultation, and conducted a small number of interviews. This report presents the findings of these landscape assessment activities and provides an evidence base for FAIRsFAIR to build upon as work begins to define a set of practical recommendations to support policy enhancement (D3.3). We will share a link to the draft policy enhancement recommendations later this month and would be grateful your feedback.
► We are seeking wide feedback on this draft which will inform other areas of work within the FAIRsFAIR project. Comments and suggestions can be added at https://docs.google.com/document/d/1EaPCF_9ir9bNg9MPBe3heT1wNuDuS8tJ/edit?dls=true
This document provides an analysis of practices to support FAIR data production within a broad selection of research disciplines and research data repositories. It aims to inform the priorities of stakeholders interested in embedding those practices in research communities. Those stakeholders include policy makers, data librarians and others providing data services to research communities, as well as champions of FAIR principles in those communities. It also identifies priority themes for initial work in FAIRsFAIR to support ESFRI cluster and EOSC projects in FAIR culture change. These include developing a self-assessment framework for research infrastructures and institutions on their progress to support FAIR enabling practices in the communities they serve. This will underpin further work to build capabilities, describe good practice and address the highly uneven awareness of FAIR principles and the lack of information on research community implementation.
We will share a link to the draft document in Zenodo later this month and would be grateful to get your feedback.
The primary focus of work package four in FAIRsFAIR is (trusted) repositories that enable the curation of (FAIR) objects. But to be integrated into an operational European Open Science Cloud (EOSC) a wider vision of FAIR ecosystem dependencies and interconnections is required. Data users and stewards of all kinds must be empowered to find, store and access data and metadata designed for interoperability and reuse. This draft presents a vision for the FAIR ecosystem components required to ensure FAIRness across the full data lifecycle.
This report provides an analysis of the landscape of available competence centres with a focus on gaps in disciplines and features. In addition, we will present the expectations of the FAIRsFAIR project for the project’s Competence Centre and needs raised by the community in surveys, interviews and workshops. Based on these results, we provide recommendations on advisory services, harmonisation and dissemination of outputs that the FAIRsFAIR Competence Centre could offer which will be the foundation for any future work carried out in work package WP6.
FAIRsFAIR has a Zenodo community where you can access these and other project outputs. Visit the community here.