Interoperability and FAIRness through a novel combination of Web technologies

Center for Plant Biotechnology and Genomics - UPM/INIA, Universidad Politécnica de Madrid, Madrid, Spain
imec, Ghent University, Ghent, Belgium
Dutch Techcenter for Life Sciences, Utrecht, The Netherlands
Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
Department of Neurology, Harvard Medical School, Boston, United States
Genomics Coordination Center and Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands
Department of Computer Science, School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United Kingdom
FAIR Data, Dutch TechCenter for Life Science, Utrecht, The Netherlands
Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
Department of Neurology, Harvard Medical School, Boston, United States of America
PerkinElmer Inc., Waltham, Massachusetts, United States
Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
Department of Human Genetics,, Leiden University Medical Center, Leiden, The Netherlands
Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
Stanford Center for Biomedical Informatics Research, Stanford University School of Medicine, Stanford, California, United States of America
DOI
10.7287/peerj.preprints.2522v1
Subject Areas
Bioinformatics, Data Science, Databases, Emerging Technologies, World Wide Web and Web Science
Keywords
FAIR Data, Interoperability, Data Integration, Semantic Web, Linked Data, REST
Copyright
© 2016 Wilkinson et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Wilkinson MD, Verborgh R, Bonino da Silva Santos LO, Clark T, Swertz MA, Kelpin FDL, Gray AJG, Schultes EA, van Mulligen EM, Ciccarese P, Thompson M, Kaliyaperumal R, Bolleman JT, Dumontier M. 2016. Interoperability and FAIRness through a novel combination of Web technologies. PeerJ Preprints 4:e2522v1

Abstract

Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such as KEGG for pathway data or UniProt for protein data) to those that are general-purpose (such as FigShare, Zenodo, or EUDat). These data have widely different levels of sensitivity and security considerations. For example, clinical observations about genetic mutations in patients are highly sensitive, while observations of species diversity are generally not. The lack of uniformity in data models from one repository to another, and in the richness and availability of metadata descriptions, makes integration and analysis of these data a manual, time-consuming task with no scalability. Here we explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any general- or special-purpose repository as a means to assist users in finding and reusing their data holdings. We show that by using off-the-shelf technologies, interoperability can be achieved even to the level of an individual spreadsheet cell. We note that the behaviors of this architecture compare favorably to the desiderata defined by the FAIR Data Principles, and can therefore represent an exemplar implementation of those principles. The proposed interoperability design patterns may be used to improve discovery and integration of both new and legacy data, maximizing the utility of all scholarly outputs.

Author Comment

This is a submission to PeerJ Computer Science for review.