The following deliverables are now open for comments by the community.
Listed in this document are the seventeen minimum viable metrics proposed by FAIRsFAIR for the systematic assessment of FAIR data objects and detailed in the report FAIRsFAIR Data Object Assessment Metrics. We welcome your suggestions and remarks before 31 December 2020. Your valuable feedback will be used to refine and further improve the metrics.
https://zenodo.org/record/4003598
Aligning the CoreTrustSeal Requirements with an assessment of repositories' ability to enable FAIR data is an important part of delivering an EOSC. Trustworthy Digital Repositories (TDR) which enable FAIR data are a dependency for many components of modern, open, distributed research. This paper sets the work within the wider context of data infrastructures, describes the co-dependencies between (meta) data objects and their repository environment, and presents the developing mapping between requirements and principles. The evolving capability/maturity approach is explained and the design of a governed assessment and certification process is defined. This work will iterate alongside the wide range of ongoing data infrastructure initiatives to support a range of stakeholders on their journey towards trustworthy repository services that enable FAIR data. Extensive engagement and feedback are planned to allow us to reach this goal.
https://zenodo.org/record/4001631
One of three in a series, this report builds on the landscaping effort published in March 2020 as Persistent Identifiers and Interoperability: Outcomes from the FAIRsFAIR Survey of the European Scientific Data Landscape which reviewed and documented the state of FAIR in the European scientific data ecosystem, and identified commonalities and possible gaps in semantic interoperability, and the use of metadata and persistent identifiers across infrastructures. The new report is aimed specifically at an audience of researchers, data stewards, and service providers, and serves as an explanatory guide to the use of PIDs, metadata, and semantic interoperability.
https://zenodo.org/record/3707985#.XoYgCpMzYWo
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.
https://zenodo.org/record/3631528#.XnJjhnJ7k1l
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.
https://doi.org/10.5281/zenodo.3688762
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.