secondly, to illustrate a few points on how/where the mechanisms to improve traceability along the process and deliverables are envisioned:
1. Scott Bahlavooni, Biogen Idec, and Gary Walker, Quintiles, presented a handy summary of the
diverse PhUSE / FDA CS WG’s, their deliverables to date and ongoing projects as reflected in the PhUSE wiki, PhUSE / FDA -CS WGs area.
2. Mitra Rocca, FDA, provided insights into the RDF representation of the CDISC CDASH standard, one of the deliverables produced by the Semantic Technologies WG, “Representing CDISC Foundational Standards in RDF” project team. This representation of CDISC Foundational Standards offers a core mechanism for Semantic Interoperability.
3. Landen Bain, CDISC - our Session Chair, presented a recap of the keyCRF project under the
Semantic Technologies WG, very helpful for those of you who could not attend Session 3. The keyCRF project aims to create a semantically annotated electronic Case Report Form (eCRF) that can enable the pre-population of the eCRF from linked data elements in an EHR summary document, HL7's Continuity of Care Document (CCD). This project is expected to use the CDISC CDASH standard represented in RDF, potentially extracting metadata directly from an MDR repository such as CDISC SHARE
4. I provided a summary of the work performed to date by the Results Metadata (RM) team, a sub-
team of the Semantic Technologies WG team. As a member of the RM team, I would like to acknowledge team members Marc Andersen (co-lead), Tim Williams, Ian Fleming (co-lead) and Ippei Akiya for the underlying technical work on the POC -object of my presentation-, plus Frederik Malfait and Geoff Lowe for the overall support on RDF.
In this talk, I presented an overview of the process, standards and technologies used in the proof of concept (POC) for delivering Statistical Results as an RDF Data Cube (a Data Cube, referred as well as a multidimensional dataset, represented in RDF). The RDF Data Cube includes both statistical results and metadata describing those results, where each cell of this data cube or multidimensional dataset represents one set of statistical results that fall under the same dimensions or categorical variables. One important source of metadata illustrated in the POC, and stored in the RDF Data Cube, links directly to the CDISC Standard Controlled Terminology definitions represented in RDF. Similarly, the CDISC Standards upon which the data is modeled are expected to be linked and represented in the deliverables. All these link mechanisms, plus the fact that storing both data and metadata for each statistical result in the same package are aimed at facilitating traceability and data integration, allowing exploratory analysis as well, and potentially helping to improve the regulatory review process.
Strength through Collaboration
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44