Applying the Semantic Web at UCHSC - Center for Computational Pharmacology Ian Wilson.

Post on 30-Dec-2015

221 views 0 download

Transcript of Applying the Semantic Web at UCHSC - Center for Computational Pharmacology Ian Wilson.

Applying the Semantic Web at UCHSC - Center for Computational Pharmacology

Ian Wilson

Projects with semantics at UCHSC-CCP Integrated Neuroscience Initiative on

Alcoholism (INIA) Analysis Suite Ongoing project to support the INIA

consortium (30+ universities geographically dispersed)

First release at the Neuroscience 2004 conference – Microarrays only at the moment

NLP Enrichment Opportunities Recent funding September 2004 – NLM

Data integration framework for life science knowledge-bases

INIA SemWeb Opportunities Conversion of LISP-CM based signal

transduction knowledge-base to OWL Application framework to link the semantics

of our data – e.g. MAGE, fMRI, etc. Exploring ‘scientific workflow’ tools to

enable composition of semantically annotated web services – easy UI for the investigator myGrid project – also presenting at the

conference Issues with the granularity of semantics

NLP Enrichment Opportunities Using Direct Memory Access Parsing

(DMAP) – ‘conceptual parsing’ supported by ontologies

Developing Protege plug-in to support NLP annotations – gold standard development

Text sources Entrez GeneRIFs

255 character summary of gene function derived from PubMed

Gene Ontology Definitions

Data Integration Framework Creating RDF wrappers for several

bioinformatics data sources Using NCBI, GO, Uniprot, etc. as test cases Alignment of several bio-ontologies –

extending when appropriate Investigating/benchmarking several

triple stores and browsers Kowari, Jena, Sesame Lightweight JSP, Longwell

Mappings are not always straight forward

Why integrate? Current architecture is not maintainable

Web tiered databases Data models in flux Web client interfaces in flux Everyone has a different client interface and data model design

CLI tools

500+ services/databases & Growing

Cutting and pasting

Large number of steps

Frequently repeated – info now rapidly added to public databases

Don’t always get results

Semantic Web Concerns Inference

Modeling default reasoning and negation in OWL?

Reification is not sufficient for context – Quads Named graphs

DL’s are good for certain tasks, but Need other logics in the life sciences closed world reasoning – e.g. rules

Scalability Need to constrain search in RDF space

Conclusion

Always looking for collaborators Questions?