S3QL: A distributed domain specific language for controlled semantic integration of life sciences data
1 Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland
2 Biomathematics, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da República, Estação Agronómica Nacional, 2780-157 Oeiras, Portugal
3 Laboratório Nacional de Computação Ciêntifica, Av. Getúlio Vargas, 333,Quitandinha, 25651-075 Petrópolis, Brasil
4 Sanofi Pasteur, 38 Sidney Street, Cambridge, MA 02139, USA
5 Laboratory of Molecular Genetics, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da República, Estação Agronómica Nacional, 2780-157 Oeiras, Portugal
6 Research Center for Intelligent Media, Furtwangen University, Furtwangen, Germany
7 Laboratory of Microbiology, The Rockefeller University, 10021 New York, USA
8 Division of Informatics, Department of Pathology, University of Alabama at Birmingham, 619 South 19th Street, Birmingham, Alamaba, USA
BMC Bioinformatics 2011, 12:285 doi:10.1186/1471-2105-12-285Published: 14 July 2011
The 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.
Reflecting 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.
S3QL 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.