Publishing FAIR data: an exemplar methodology utilizing PHI-base

A - Papers appearing in refereed journals

Rodriguez-Iglesias, A., Rodriguez-Gonzales, A., Irvine, A. G., Sesma, A., Urban, M., Hammond-Kosack, K. E. and Wilkinson, M. D. 2016. Publishing FAIR data: an exemplar methodology utilizing PHI-base. Frontiers in Plant Science. 7, p. 641.

AuthorsRodriguez-Iglesias, A., Rodriguez-Gonzales, A., Irvine, A. G., Sesma, A., Urban, M., Hammond-Kosack, K. E. and Wilkinson, M. D.
Abstract

Pathogen-Host interaction data is core to our understanding of disease processes and their molecular/genetic bases. Facile access to such core data is particularly important for the plant sciences, where individual genetic and phenotypic observations have the added complexity of being dispersed over a wide diversity of plant species vs. the relatively fewer host species of interest to biomedical researchers. Recently, an international initiative interested in scholarly data publishing proposed that all scientific data should be “FAIR”—Findable, Accessible, Interoperable, and Reusable. In this work, we describe the process of migrating a database of notable relevance to the plant sciences—the Pathogen-Host Interaction Database (PHI-base)—to a form that conforms to each of the FAIR Principles. We discuss the technical and architectural decisions, and the migration pathway, including observations of the difficulty and/or fidelity of each step. We examine how multiple FAIR principles can be addressed simultaneously through careful design decisions, including making data FAIR for both humans and machines with minimal duplication of effort. We note how FAIR data publishing involves more than data reformatting, requiring features beyond those exhibited by most life science Semantic Web or Linked Data resources. We explore the value-added by completing this FAIR data transformation, and then test the result through integrative questions that could not easily be asked over traditional Web-based data resources. Finally, we demonstrate the utility of providing explicit and reliable access to provenance information, which we argue enhances citation rates by encouraging and facilitating transparent scholarly reuse of these valuable data holdings.

KeywordsFAIR data; Linked Data; Pathogen-Host Interactions; PHI-base; Semantic Web; Semantic PHI-base; SPARQL; data integration
Year of Publication2016
JournalFrontiers in Plant Science
Journal citation7, p. 641
Digital Object Identifier (DOI)doi:10.3389/fpls.2016.00641
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeWheat
Pathogen-Host Interactions Database: PHI Database [2012-2017]
PhytoPath: an Integrated resource for comparative phytopathogen genomics [2011-2014]
PhytoPath, an infrastructure for hundreds of plant pathogen genomes [2014-2017]
[20:20 Wheat] Protecting yield potential of wheat
Publisher's version
Output statusPublished
Publication dates
Online12 May 2016
Publication process dates
Accepted26 Apr 2016
PublisherFrontiers Media SA
Copyright licenseCC BY
ISSN1664-462X

Permalink - https://repository.rothamsted.ac.uk/item/8v22x/publishing-fair-data-an-exemplar-methodology-utilizing-phi-base

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