=Paper=
{{Paper
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|title=None
|pdfUrl=https://ceur-ws.org/Vol-2849/paper-17.pdf
|volume=Vol-2849
|dblpUrl=https://dblp.org/rec/conf/swat4ls/ListerMTS19
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==None==
https://ceur-ws.org/Vol-2849/paper-17.pdf
Mapping subjects and domains across the
humanities and natural sciences in FAIRsharing
Allyson L. Lister1[0000−0002−7702−4495] , Peter McQuilton1[0000−0003−2687−1982] ,
Milo Thurston1[0000−0002−6468−9260] , and Susanna-Assunta
Sansone1[0000−0001−5306−5690]
Oxford e-Research Centre (OeRC), Department of Engineering Science, University of
Oxford, Oxford, UK contact@fairsharing.org
https://www.oerc.ox.ac.uk/
Abstract. FAIRsharing is a manually-curated registry of research data
standards, repositories and data policies across all humanities and natu-
ral science disciplines. Each FAIRsharing record contains over 40 meta-
data properties that provide a rich description of each resource. Stor-
ing over 2,700 records, FAIRsharing is accessed via a web portal, API
and other visualisation tools. In order to provide accurate, structured
searching, ontologies are used to populate a number of the FAIRshar-
ing metadata fields. Most recently, two application ontologies have been
built from over 2000 free-text user-generated tags. These tags were clas-
sified as subjects/research areas (SRAO - Subject Resource Application
Ontology) or as research domains (DRAO - Domain Resource Applica-
tion Ontology). To ensure the required breadth of scope and high level of
interoperability, and to limit redundancy with other community efforts,
these application ontologies are based on a number of well-supported and
adopted ontologies. FAIRsharing promotes FAIR and open science, with
both ontologies open and freely available via GitHub (SRAO, DRAO).
Keywords: FAIR Data · Application Ontologies · Data Sharing.
1 Introduction
As part of the FAIRsharing [4] curation pipeline, curators and maintainers an-
notate records with subjects and knowledge domains. Initially, approximately
2000 free text tags were stored as a flat list, creating usability issues and lim-
iting search functionality. Definitions, synonyms, a hierarchical structure, and
richer semantics were required. Many publicly-available vocabularies could pro-
vide part of what was needed, but none had the breadth of coverage required
across all research areas so, to provide the necessary semantics and structure, two
application ontologies (AOs), SRAO (Subject Resource Application Ontology)
and DRAO (Domain Resource Application Ontology), were created.
Application ontologies (AO) are intended as low-maintenance solutions, im-
porting only the terms and hierarchies required by a project. This drastically
reduces the size of the resulting ontology and increases interoperability with pre-
existing vocabularies. Within FAIRsharing, automated development and build
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
2 A. L. Lister et al.
procedures together with simple manual curation has produced AOs that are
both large in scope and small in build complexity.
2 Results
SRAO is a high-level subject hierarchy spanning all research areas and based on 7
ontologies and classification systems. SRAO’s hierarchy is manually curated and,
where possible, aligned with external ontologies. Definitions and/or synonyms
from these ontologies are automatically imported into SRAO via Ontofox [5] to
supplement the existing subject annotation.
DRAO provides fine-grained domain tags from over 50 external ontologies,
and is primarily built using automated procedures. Importing of the required
terms and their hierarchies was performed using Ontofox via a MIREOT [1]-
compliant process. After import, FAIRsharing-specific annotation was added to
the classes using ROBOT [2]. Although a number of biomedical application
ontologies (e.g. EFO [3]) have been created in this manner, we believe DRAO
maps more reference ontologies than any similar effort.
Both SRAO and DRAO are used by FAIRsharing curators and our user
community to annotate FAIRsharing records and perform searches across the
site. Both SRAO and DRAO are open, community-driven AOs and we hope
others will find them appropriate for use in their work. SRAO and DRAO are
available for general use via GitHub (SRAO, DRAO) with a CC BY-SA 4.0
licence. Release files are created using ROBOT. Improvements to the ontologies
can be suggested via their GitHub trackers and the ontologies are licensed for
use in other projects as appropriate.
References
1. Courtot, M., Gibson, F., Lister, A.L., Malone, J., Schober, D., Brinkman, R.R.,
Ruttenberg, A.: Mireot: The minimum information to reference an external ontol-
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1971674.1971680
2. Jackson, R.C., Balhoff, J.P., Douglass, E., Harris, N.L., Mungall, C.J., Overton,
J.A.: Robot: A tool for automating ontology workflows. BMC Bioinformatics 20(1)
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