@conference {168, title = {Ontology Driven Integration of Biology Experiment Data}, booktitle = {Ohio Collaborative Conference on BioInformatics (OCCBIO 2009), Posters \& Demos}, year = {2009}, address = {Cleveland, OH, USA}, author = {Raghava Mutharaju and Satya S. Sahoo and D. Brent Weatherly and Pramod Anantharam and Flora Logan and Amit Sheth and Rick Tarleton} } @conference {162, title = {Ontology-Driven Provenance Management in eScience: An Application in Parasite Research}, booktitle = {On the Move to Meaningful Internet Systems: OTM 2009, Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009, Proceedings, Part II}, volume = {5871}, year = {2009}, pages = {992{\textendash}1009}, publisher = {Springer}, organization = {Springer}, address = {Vilamoura, Portugal}, abstract = {

Provenance, from the French word {\textquotedblleft}provenir{\textquotedblright}, describes the lineage or history of a data entity. Provenance is critical information in scientific applications to verify experiment process, validate data quality and associate trust values with scientific results. Current industrial scale eScience projects require an end-to-end provenance management infrastructure. This infrastructure needs to be underpinned by formal semantics to enable analysis of large scale provenance information by software applications. Further, effective analysis of provenance information requires well-defined query mechanisms to support complex queries over large datasets. This paper introduces an ontology-driven provenance management infrastructure for biology experiment data, as part of the Semantic Problem Solving Environment (SPSE) for Trypanosoma cruzi (T.cruzi). This provenance infrastructure, called T.cruzi Provenance Management System (PMS), is underpinned by (a) a domain-specific provenance ontology called Parasite Experiment ontology, (b) specialized query operators for provenance analysis, and (c) a provenance query engine. The query engine uses a novel optimization technique based on materialized views called materialized provenance views (MPV) to scale with increasing data size and query complexity. This comprehensive ontology-driven provenance infrastructure not only allows effective tracking and management of ongoing experiments in the Tarleton Research Group at the Center for Tropical and Emerging Global Diseases (CTEGD), but also enables researchers to retrieve the complete provenance information of scientific results for publication in literature.

}, doi = {10.1007/978-3-642-05151-7_18}, url = {http://dx.doi.org/10.1007/978-3-642-05151-7_18}, author = {Satya S. Sahoo and D. Brent Weatherly and Raghava Mutharaju and Pramod Anantharam and Amit Sheth and Rick Tarleton}, editor = {Robert Meersman and Tharam S. Dillon and Pilar Herrero} } @conference {169, title = {Trykipedia: Collaborative Bio-Ontology Development using Wiki Environment}, booktitle = {Ohio Collaborative Conference on BioInformatics (OCCBIO 2009), Posters \& Demos}, year = {2009}, address = {Cleveland, OH, USA}, author = {Pramod Anantharam and Satya S. Sahoo and D. Brent Weatherly and Flora Logan and Raghava Mutharaju and Amit Sheth and Rick Tarleton} }