Semantic Data Lake for Biomedical Research

Capitalizing on the transformative opportunities afforded by the extremely large and ever growing volumevelocityand variety of biomedical data being continuously produced is a major challengeThe development and increasingly widespread adoption of several new technologiesincluding next generation genetic sequencingelectronic health records and clinical trials systemsand research data warehouses means that we are in the midst of a veritable explosion in data productionThis in turn results in the migration of the bottleneck in scientific productivity into data management and interpretationtools are urgently needed to assist cancer researchers in the assemblyintegrationtransformationand analysis of these Big Data setsIn this projectwe propose to develop the Semantic Data Lake for Biomedical ResearchSDL BRsystema cluster computing software environment that enables rapid data ingestionmultifaceted data modelinglogical and semantic querying and data transformationand intelligent resource discoverySDL BR is based on the idea of a data lakea distributed store that does not make any assumptions about the structure of incoming dataand that delays modeling decisions until data is to be usedThis project adds to the data lake paradigm methods for semantic data modelingintegrationand queryingand for resource discovery based on learned relationships between users and data resources The SDL BR System is a distributed computing software solution that enables research institutions to manageintegrateand make available large institutional data sets to researchersand that permits users to generate data models specific to particular applicationsIt uses state of the art cluster computingSemantic Weband machine learning technologies to provide for rapid data ingestionsemantic modeling and queryingand search and discovery of data resources through a sophisticatedWeb based user interface