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Technical description: A Statistical Computing Environment (SCE) provides a foundation for documenting rigor in the analysis and reporting of clinical trial results while increasing productivity and quality.  To ensure credibility, reliability and data integrity assurance the best way is to work in an environment that tracks all of the objects. By developing a table of contents of the objects to be created one can track the objects. The table of contents itself becomes a part of the study metadata. The environment would typically include standard programs and algorithms for producing common reports of trial data. Above all, the statistical computing environment develops electronic documentation of the entire process.

Cross reference

caGRID should support interoperability from non grid platforms.

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Technical description: One persons object is another person's attribute". Depending on one's world view, a real life entity can be modeled in UML as Object, Attribute or value set. In caBIG models now, some model Race (and Ethnicity) as an Object while others model Race (and Ethnicity) as an attribute. This is problematic, because Race data that is modeled differently cannot be "seamlessly integrated" on caGrid (there needs to be a transform). One can start to use the SAIF language in terms of Conceptual, Platform Independent (logical) and Platform Specific (Implemented).  Given that the grid has CIMs, PIMs and PSMs for applications, and BAM and a DAM and other institutions, may have their own DAMs, BAMs, CIMs, PIMs and PSMs.  These elements need to be mapped to each other at whatever level needed, to get to some semantic interoperability.

Cross reference

Semantic search on the cancer grid.

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Technical description:  The Lexical Grid, coordinated by the Mayo Clinic Division of Biomedical Statistics and Informatics, provides a semantic foundation upon which multiple APIs can be developed that support consistent searching, navigation and cross terminology traversal. These open-source tools are used in a variety of projects such as the NCI Cancer Biomedical Informatics Grid, the National Center for Biomedical Ontology, the Biomedical Grid Terminology project, and the World Health Organization International Classification of Diseases (ICD-11) development process. LexGrid hosts a wide variety of terminologies and ontologies including ICD-9-CM, the Gene Ontology, the HL7 Version 3 vocabulary, and SNOMED-CT. LexGrid can also represent complete NLM Unifed Medical Language System, which currently includes over 100 source terminologies. The Lex-RDF model, maps the LexGrid model elements to corresponding constructs in W3C specifications such as RDF, OWL, and SKOS. With LexRDF, the terminological information represent in LexGrid can be translated to RDF triples, and therefore allowing LexGrid to leverage standard tools and technologies such as SPARQL and RDF triple stores.

Cross reference

  • Use case

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Integration of radiology, pathology, molecular and genomic data to better predict patient outcome and support clinical decision.

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Technical description: A service is needed that can collate data from the national cancer imaging archive, caArray, cancer central clinical database to pull out information for a patient on staging, grading,  and other prognostic aspects of cancer. This service can run on multiple instances of various tools and pull out corresponding data the patient. This service can also be extended to support clinical decision like if a particular cohort reports better outcome and survival rates with treatment A, then it can be used as a standard line of treatment for patients with similar picture.

B. Forms Stories

Create and reuse forms

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