Published Versions 1 Vol 2 (1) : 30–39 2020
Unique, Persistent, Resolvable: Identifiers as the Foundation of FAIR
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Abstract & Keywords
Abstract: The FAIR principles describe characteristics intended to support access to and reuse of digital artifacts in the scientific research ecosystem. Persistent, globally unique identifiers, resolvable on the Web, and associated with a set of additional descriptive metadata, are foundational to FAIR data. Here we describe some basic principles and exemplars for their design, use and orchestration with other system elements to achieve FAIRness for digital research objects.
Keywords: Identifiers, metadata, findability, FAIR data, data infrastructures
Article and author information
Cite As
N. Juty, S.M. Wimalaratne, S. Soiland-Reyes, J. Kunze, C.A. Goble & T. Clark. Unique, persistent, resolvable: Identifiers as the foundation of FAIR. Data Intelligence 2(2020), 30–39. doi: 10.1162/dint_a_00025
Nick Juty
N. Juty ( conceived, organized and wrote initial drafts of this article, and managed the discussion of drafts.
Nick Juty is a Senior Research Technical Manager in the eScience Lab, based in the Department of Computer Science at The University of Manchester. He is involved in numerous EU projects relating to aspects of FAIR and interoperability, particularly with respect to identifier systems and metadata. Nick previously worked at EMBL-EBI where he helped create the identifier resolution system. Nick holds a PhD in Biochemistry from the University of Southampton.
Sarala M. Wimalaratne
S. Wimalaratne ( contributed discussion material in preparing the draft.
Sarala Wimalaratne spent the last 10 years at the European Bioinformatics Institute (EMBL-EBI) working with multiple data integration and infrastructure projects. During her time at the EMBL-EBI, she led the resource, which provides stable identifier resolution for life science data and beyond. She was also involved in the Data Commons Pilot Phase Consortium on globallyunique identifiers (GUIDs), the Elixir Interoperability Platform on BioSchemas and Identifiers, the FORCE11 Data Citation Implementation Pilot on Identifiers and the EU FREYA Project on identifier services. From September 2019, she will be joining DataCite as Head of Infrastructure Services.
Sarala M. Wimalaratne
Stian Soiland-Reyes
S. Soiland-Reyes ( contributed discussion material in preparing the draft.
Stian Soiland-Reyes is a Technical Architect in the eScience Lab, based in the Department of Computer Science at The University of Manchester. Since 2006 he has worked as a software engineer and researcher focusing on reproducibility, scientific workflows, interoperability, linked data, metadata and open science. He is a persistent advocate of Open Scholarly Communication, and is on the leadership team of the Common Workflow Language and on the Project Management Committee of several open source projects at the Apache Software Foundation. He co-created the Research Object model, contributed to the W3C provenance model PROV-O and multiple Linked Data initiatives. He is co-chair of the Research Object Crate team.
John Kunze
J. Kunze ( contributed discussion material in preparing the draft.
John Kunze is an Identifier Systems Architect at the California Digital Library. With a background in computer science and mathematics, he wrote BSD Unix software that comes pre-installed with Mac and Linux systems. He created the ARK identifier scheme, the scheme-agnostic resolver, and contributed heavily to Internet standards for URLs (RFC1736, RFC1625, RFC2056), archiving (BagIt - RFC8493), Web archiving (WARC), and Dublin Core metadata (RFC2413, RFC2731).
Carole A. Goble
C. Goble ( contributed discussion material in preparing the draft.
Carole Goble is Professor of Computer Science at The University of Manchester. Over the past 25 years Carole has pursued research interests in the acceleration of FAIR scientific innovation through: distributed computing, workflows and automation; knowledge management and the Semantic Web; social, virtual environments; software engineering for scientific software; and new models ofscholarship for data-intensive science. Carole has served on numerous committees and currently serves in the G7 Open Science Working Group as the UK expert. In 2008 she was awarded the Microsoft Jim Gray e-Science award for contributions to e-Science and in 2010 was elected a Fellow of the Royal Academy of Engineering. In 2014 she was awarded the Commander of the Order of the British Empire for services to Science.
Tim Clark
T. Clark ( contributed discussion material in preparing the draft.
Tim Clark is Associate Professor of Public Health Sciences, Associate Professor of Neurology (by courtesy), and Associate Research Director for Neuroinformatics in the Data Science Institute, at the University of Virginia. He holds a PhD in Computer Science from The University of Manchester. His research interests include biomedical knowledge representation, computational models of evidence, cloud computing, and neuroscience.
Publication records
Published: Oct. 16, 2019 (Versions1
Data Intelligence