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
This document is the first iteration of recommendations for making semantic artefact FAIR. These recommendations result from initial discussions during a brainstorming workshop organised by FAIRsFAIR as co-located event with the 14th RDA Plenary meeting in Helsinki. We are proposing 17 preliminary recommendations related to one or more of the FAIR principles and 10 best practice recommendations to improve the global FAIRness of semantic artefacts. These initial recommendations should not be considered as a gold standard but rather as a basis for discussion with the various stakeholders of the semantic community.
► We are seeking wide feedback on this draft. Comments and suggestions can be added at
This report presents the results of the first year of Task 2.3 from the FAIRsFAIR project. It gives guidelines to enable features for repositories which allow them not only to host FAIR digital objects, but also to be FAIR themselves. The recommendations were collected in the workshop “Building the data landscape of the future: FAIR Semantics and FAIR Repositories” (22 October 2019, Espoo Finland) that was hosted by this task together with the FAIRsFAIR task 2.2. It derived input from more than 70 participants from 6 communities: the European Life Sciences Infrastructure for Biological Information (ELIXIR), the European Incoherent Scatter Scientific Association (EISCAT), the Social Sciences and Humanities (SSH), the Integrated Carbon Observation System (ICOS), the European network of Long-Term Ecosystem Research sites (eLTER), and the Data Publisher for Earth & Environmental Science ( Pangea). The background of participants lied in infrastructures, research and libraries.
► 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/1sjps6KXmb9sa1iNnzp9antq5RPO36x84oVj_1Fxttfg/edit?usp=sharing
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 are seeking wide feedback on this draft. Comments and suggestions can be added at this google doc now available:
FAIRsFAIR’s analysis of the data policy landscape in 2019 (D3.1 FAIR Policy Landscape Analysis) has shown that the priority and supporting actions outlined in the Turning FAIR into Reality (TFiR) report are being reflected in the policies of funding bodies, publishers/journals and Research Performing Organisations (RPOs) to some extent. However, as crucial components in the FAIR ecosystem, there is still much that needs to be done to foster and harmonise policies to support the aims of the European Open Science Cloud and realise the vision of TFiR. Based on this initial landscape assessment and the work of related initiatives, FAIRsFAIR has prepared a series of practical recommendations for policy enhancement to support the realisation of a FAIR ecosystem. These recommendations are released as a living document that will be refined to reflect the forthcoming work of other projects funded under the INFRAEOSC-05-2018-2019 call and other relevant initiatives.
► 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 until 17 April 2020 at:
D4.1 presents a set of preliminary metrics corresponding to FAIR principles that can be used to assess data objects through manual and automated testing. We discuss the development and key aspects of the metrics, including their initial alignments with the existing CoreTrustSeal requirements. The alignment forms a basis to develop the FAIR elaboration of CoreTrustSeal requirements, which is one of main ongoing activities of WP4. Furthermore, we present draft requirements that any FAIR assessment implementation will need to consider and highlight how those requirements will impact the use cases for FAIR assessment that our upcoming work will address. We conclude by outlining the next steps in our work to iteratively improve the requirements through a number of pilots. Our priorities include the refinement of the suggested metrics based on the feedback elicited during pilot testing with several communities, in the context of the use cases developed.
► 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 until 1 July 2020 at: https://drive.google.com/file/d/1dEKvKVqQGZ7Kvejeo7UYjquWMcTg-GtK/view
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.
Request for comments:
► 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/1WcHr-F9KsjYd7PBsSa4cZNRYiTzc1aLd48B1DBdscFo/edit#
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.
►Comments and suggestions can be added until 17 April 2020 at: https://drive.google.com/file/d/1c-KFgFWXr3d9f93lZiAIMsH0W7-g547X/view?usp=sharing
This report marks the first milestone of the task. It presents a survey of existing FAIR assessment frameworks, a proposed set of guiding principles and desiderata for the FAIR assessment framework that will be constructed, and three ‘FAIR service assessment’ case studies. We are seeking wide feedback on this report to inform subsequent work and, ultimately, feed into a FAIR assessment framework for data services that delivers clear direction and value to service owners and the community at large.
►Feedback and suggestions will be most welcome as comments on the public Google Doc version of this report at: https://docs.google.com/document/d/1VO8T8mpsp4qt-XSbcdUBTMVgOVwEf9na81Ccv56NPg4/edit
This paper is milestone 4.1 of the FAIRsFAIR task 4.1 (Capability Maturity models towards FAIR Certification) within the FAIR Certification work package (WP4). This document presents the first iterative step in aligning the characteristics of FAIR digital objects with the repositories that ‘enable’ FAIRness, through the CoreTrustSeal Trustworthy Data Repository Requirements and the application of a capability/maturity evaluation approach.
►Feedback and suggestions will be most welcome as comments on the public Google Doc version of this report at: https://docs.google.com/document/d/1XbEBzRnMTVRJ8BibU3V7by_9w3kHpp6Y2bexHUiQLZ4/edit
FAIRsFAIR has a Zenodo community where you can access these and other project outputs. Visit the community here.