Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach

A - Papers appearing in refereed journals

Brandizi, M., Singh, A., Rawlings, C. J. and Hassani-Pak, K. 2018. Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach. Journal of Integrative Bioinformatics. 15 (3), pp. 1-10.

AuthorsBrandizi, M., Singh, A., Rawlings, C. J. and Hassani-Pak, K.
Abstract

The speed and accuracy of new scientific discoveries – be it by humans or artificial intelligence – depends on the quality of the underlying data and on the technology to connect, search and share the data efficiently. In recent years, we have seen the rise of graph databases and semi-formal data models such as knowledge graphs to facilitate software approaches to scientific discovery. These approaches extend work based on formalised models, such as the Semantic Web. In this paper, we present our developments to connect, search and share data about genome-scale knowledge networks (GSKN). We have developed a simple application ontology based on OWL/RDF with mappings to standard schemas. We are employing the ontology to power data access services like resolvable URIs, SPARQL endpoints, JSON-LD web APIs and Neo4j-based knowledge graphs. We demonstrate how the proposed ontology and graph databases considerably improve search and access to interoperable and reusable biological knowledge (i.e. the FAIRness data principles).

Keywordsbiological knowledge networks; FAIR data; linked data; graph databases; semantic web; bio-ontologies; data integration
Year of Publication2018
JournalJournal of Integrative Bioinformatics
Journal citation15 (3), pp. 1-10
Digital Object Identifier (DOI)doi:10.1515/jib-2018-0023
PubMed ID30085931
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeDesigning Future Wheat (DFW) [ISPG]
DFW - Designing Future Wheat - Work package 4 (WP4) - Data access and analysis
DiseaseNetMiner - A novel tool for mining integrated biological networks of host and pathogen interaction
Publisher's version
Output statusPublished
Publication dates
Online07 Aug 2018
Publication process dates
Accepted07 Jul 2018
PublisherDe Gruyter
Copyright licenseCC BY-NC-ND
ISSN1613-4516

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