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To address these limitations, the CTIIP team is developing a unified query interface to make it easier to analyze data from different research domains. This interface, plus related open-source software and data standards, would then be applied to co-clinical, small animal model data, and provide a common platform and data engine for the hosting of “pilot challenges.” These pilot challenges will proactively facilitate biological and clinical research across the clinical, pre-clinical, and digital pathology imaging research domains. The algorithms used in the pilot challenges will be shared with the community via an open-source software clearinghouse.
The approach taken to development in this project emphasizes modular semantic interoperability and open source tooling, making it immediately valuable to scientists with NCI-funded research networks in the three research domains, as well as the national and international research communities, and providing a framework for enhanced adoption of these methods by biologists in the larger genomics/proteomic communities.
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This sub-project addresses the lack of uniformly accepted standards within digital pathology and the simultaneous need for integration of pathology data with radiographic, genomic, and proteomic data. Its mission is to create an open-source digital pathology image server that can host and serve digital pathology images for any of the major vendors without recoding, facilitating data integration. This image server would establish an informatics and IT infrastructure to implement pilot challenges for clinical and pre-clinical studies that integrate the (CKK: talk to Ulli about different names for the same? domains mentioned on this page) genomics, diagnostic imaging, and digital pathology domains.
Goals: data exploration, data connection, data mashup, make data available for analysis, make data accessible for image algorithms
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•Extend software to support data mashups between image-derived information from TCIA and clinical and molecular metadata from TCGA.
Integrative Query System
Extend software to support data mashups between image-derived information from TCIA and clinical and molecular metadata from TCGA.
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