Abstract
BackgroundThe value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control.We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data.ResultsReflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases.ConclusionsS3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms.
Highlights
The value and usefulness of data increases when it is explicitly interlinked with related data
S3DB was shown to include the minimum set of features required to support the management of experimental and analytic results by Life Sciences experts while making use of Linked Data best practices such as HTTP URI, subjectpredicate-object triples represented using RDF Schema, links to widely used ontologies suggested by NCBO ontology widgets [44] or new OWL classes created by the users and a SPARQL endpoint [41]. Complying with these practices is enough to cover the immediate query or “read” requirements of a Linked Data Knowledge organization systems (KOSs), we found that efficient data management or “write” operations, such as inserting, updating and deprecating data instances within a KOS could be more efficiently addressed with the identification of the S3DB Query Language (S3QL), a Domain Specific Language (DSL) devised to abstract most of the details involved in managing interlinked, contextualized, RDF statements
We have found the target audience for S3DB query language (S3QL) to be both life sciences application developers, who use it through a RESTful application programming interface (API), and life sciences researchers who use it through user interfaces for weaving the ontologies that best represent the critical contextual information in their experimental results
Summary
The value and usefulness of data increases when it is explicitly interlinked with related data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. The architecture of that Web is expected by its original architects [14] to require a representation of usage contexts that can be applied in the collaboration and controlled sharing of data. When this functionality is supported, as that report anticipates, “social machines” will be able to manage the simultaneous and conflicting views of data that fuel scientific debate. It will be demonstrated that S3QL provides a convenient mechanism to engage Linked Data in general
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