PMC3680174
Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases
Currently, the large amount of plant high-throughput data that have been produced by different laboratories is distributed across many different crop-specific databases. Plant biologists and breeders often need to access several databases to perform tasks such as locating allelic variants for genetic markers in different crop populations and in a given environment or investigating the consequences of a mutation at the transcriptome, proteome, metabolome and phenome levels. The integration of these disparate databases would make complex analyses easier and could also reveal hidden knowledge 12.
However, biological data integration faces challenges because of syntactic and semantic heterogeneity. In their reviews, Stein LD 3 and Goble C & Stevens R 4 provide a fair criticism of the lack of integrated approaches and provide a similar vision for the future, which is that the Semantic Web (SW) can aid in data integration. According to the W3C, “the SW provides a common framework that allows data to be shared and reused across applications, enterprises, and community boundaries”a. The SW currently provides recommendations (RDF 5, SPARQL 6, OWL 7) for enabling interoperability across databases. Furthermore, major plant databases, such as TAIR 8, Gramene 9, IRIS 10, MaizeGDB 11 and GnpIS 12, annotate their data using ontology terms to link different datasets and to facilitate queries across multiple databases. Guided by life science integration studies 1314, annotating data with ontologies promotes the development of ontology-driven integration platforms 1516.
In parallel, Web Services (WS) are becoming an increasingly popular way of establishing robust remote access to major bioinformatics resources, such as EMBL-EBI, KEGG and NCBI. WS are virtually platform-independent and are easily reusable. Indeed, analysis and data retrieval WSs can be rapidly combined and integrated into complex workflows.
The common use of the SW and WS standards has the promise of achieving integration and interoperability among the currently disparate bioinformatics resources on the Web 17. There are currently existing efforts to describe Web Services with semantic annotations by using ontologies, such as SSWAP 18, SADI 19 and BioMoby 20. However, none of these approaches are focused on the automation of business logic 21. The implementation of new Semantic Web Services (SWS) can be time-consuming and requires the developer to know how to manipulate SW and WS standards and to have expertise on the database schema. To our knowledge, there are currently no ongoing efforts in the context of the automation of SWS creation that are both specific to relational databases and based only on W3C standards.
Références
- ^ Tsesmetzis N, Couchman M, Higgins J, Smith A, Doonan JH, Seifert GJ, Schmidt EE, Vastrik I, Birney E, Wu G, D’Eustachio P, Stein LD, Morris RJ, Bevan MW, Walsh SV. "Arabidopsis reactome: a foundation knowledgebase for plant systems biology -- abc". Plant Cell 20. (2008): 1426–1436. doi: 10.1105/tpc.108.057976 PMCID: PMC2483364
- ^ Lysenko A, Hindle MM, Taubert J, Saqi M, Rawlings CJ. Data integration for plant genomics—exemplars from the integration of Arabidopsis thaliana databases. Brief Bioinform. 2009;10:676–693.
- ^ Stein LD. Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges. Nat Rev Genet. 2008;9:678–688. -- abc 123 789
- ^ Goble C, Stevens R. State of the nation in data integration for bioinformatics. J Biomed Inform. 2008;41:687–693. doi: 10.1016/j.jbi.2008.01.008.
- ^ RDF/XML Syntax Specification (Revised) http://www.w3.org/TR/REC-rdf-syntax/
- ^ SPARQL Query Language for RDF. http://www.w3.org/TR/rdf-sparql-query/
- ^ OWL Web Ontology Language Overview. http://www.w3.org/TR/owl-features/
- ^ Swarbreck D, Wilks C. The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res. 2008;36:D1009–D1014.
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- ^ Lawrence CJ, Harper LC. MaizeGDB: The Maize Model Organism Database for Basic, Translational, and Applied Research. Int J Plant Genomics. 2008;2008:1–10.
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- ^ Wilkinson MD, Vandervalk B, McCarthy L. SADI Semantic Web Services – ‘cause you can’t always GET what you want! 2009. pp. 13–18. (Services Computing Conference, 2009 APSCC 2009 IEEE Asia-Pacific: 7-11 Dec. 2009).
- ^ Gessler D, Schiltz G. SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services. BMC Bioinformatics. 2009;10:309. doi: 10.1186/1471-2105-10-309.
- ^ Wilkinson MD, Vandervalk B, McCarthy L. The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation. J Biomed Semantics. 2011;2:8. doi: 10.1186/2041-1480-2-8.
- ^ Wilkinson MD, Senger M, Kawas E, Bruskiewich R, Gouzy J, Noirot C, Bardou P, Ng A, Haase D, Saiz Ede A. Interoperability with Moby 1.0–it's better than sharing your toothbrush! Brief Bioinform. 2008;9(3):220–231. --aad
- ^ Wilkinson M, McCarthy L. SADI, SHARE, and the in silico scientific method. BMC Bioinform. 2010;11:S7. -- abcdsd
