Special issue on Linked Data for Health Care and the Life Sciences

Abstract

Health Care and Life Sciences (HCLS) have long been a test-bed for the standards proposed by the W3C to build the Semantic Web 1 : since HCLS is descriptive by nature and its descriptions have traditionally been produced according to ad-hoc schemas in isolated resources, HCLS offers an ideal use case for technologies like RDF 2 , SPARQL 3 and OWL 4 [1,4]. This "marriage" of the HCLS domain with semantic technologies has resulted in a collection of resources that can be regarded as an HCLS-focused working implementation of the idea of the Semantic Web: the socalled Life Sciences Semantic Web (LSSW).As part of the process of implementing the LSSW, the HCLS community has adopted the Linked Data practices to publish information in a machine-friendly and linkable fashion [3], as a "down-to-earth" version of a prospective fully-fledged Semantic Web. This has resulted in members of the HCLS community, like the W3C HCLS Interest Group 5 , considerably contributing to the Linked Open Data (LOD) endeavour, with datasets like Bio2RDF [2] and Linked Open Drug Data (LODD) [5].As the LOD network grows, producers and consumers alike are facing new challenges regarding interoperable vocabularies, filtering, graphical interfaces, 1 http://www.w3.org/standards/semanticweb/ 2 http://www.w3.org/standards/techs/rdf 3 http://www.w3.org/standards/techs/sparql 4 http://www.w3.org/standards/techs/owl 5 http://www.w3.org/blog/hcls/ best practices for dataset production, dataset quality evaluation, role of automated reasoning, etc. The aim of this special issue is to showcase some of the latest developments in the application of Linked Data in HCLS and help pave the way to solve such challenges. The issue comprises the following manuscripts: in "Applying Linked Data Approaches to Pharmacology: Architectural Decisions and Implementation" Alasdair J.G. Gray et al. describe the technical decisions made when building the Open Pharmacological Space (OPS), a drug discovery platform part of the Open PHACTS project 6 ; in "Using the relation ontology Metarel for modelling Linked Data as multi-digraphs" Ward Blondé et al. describe Metarel, an ontology that describes class-level relations that can be used for SPARQL queries; in "A collaborative methodology for developing a semantic model for interlinking Cancer Chemoprevention linked-data sources" Dimitris Zeginis et al. describe how they used a new collaborative methodology to build a semantic model related to cancer chemoprevention.The manuscripts went through a rigorous review process in which half of the submissions were accepted. We would like to thank the referees for their time and effort:

Using health data repositories for developing clinical system software: a multi‐objective fuzzy genetic approach

“…Some of these considerations may include computational complexities, multiple access points, and information from multiple sources. Several papers have highlighted the strength and effective utilisation of integrated clinical data management in a semantically aware and standardised way [17][18][19]. In [20], a review on utilising semantic integration methodologies and ontologies proves the huge potential, but still, there is no gold standard benchmark solution available.…”

Enhanced reproducibility of SADI web service workflows with Galaxy and Docker

“…Linked Data has demonstrated clear value as a means of data publication in a machine-readable and web-resolvable fashion, opening up new possibilities for data discovery and integration [ 9 ]. As a result, significant life sciences data providers have implemented Linked Data solutions for their resources, including UniProt [ 10 ], EBI RDF [ 11 ], and OpenLifeData [ 12 ], each of which contributes to the growth of the Linked Open Data cloud [ 13 ].…”

Merging OpenLifeData with SADI services using Galaxy and Docker

“…Linked Data has already shown its value as a means for data publication in a machine-readable and Web resolvable fashion, opening new and interesting possibilities [Aranguren et al (2014a)]. Hence, important data providers in the life sciences have implemented Linked Data solutions, such as UniProt 7 , EBI RDF 8 , and OpenLifeData 9 , contributing to the growth of the Linked Open Data (LOD) cloud 10 .…”