- From: Richard Boyce <rdb20@pitt.edu>
- Date: Thu, 5 May 2011 11:45:29 -0400
- To: "public-semweb-lifesci@w3.org" <public-semweb-lifesci@w3.org>, "Gardner, Gregory" <gardnerga@upmc.edu>
Hi All, We are working on creating a linked-data version of an academic drug-drug interaction (DDIs) knowledge-base called the DIKB that contains assertions about DDIs observed in clinical studies as well as assertions about drug mechanisms that can be used to infer DDIs. DIKB assertions are linked to supporting and refuting evidence (see <http://www.pitt.edu/~rdb20/data/DIKB-lightning-summary-05262010.pdf>). Additionally, each use of evidence is linked to "evidence-use assumptions"; other DIKB assertions that represent assumptions made by the knowledge base curator when inferring a drug mechanism claim from an evidence item. We have questions about how to best represent this assertion/evidence structure as scientific discourse. We have been looking at the SWAN discourse ontology and it seems possible to use its elements but have ran into some issues that we are unsure about. For example, we are not sure if we should map DIKB assertions to research statements qualified as hypotheses or claims and it is not clear to us if we should represent DIKB evidence-use assumptions using SWAN elements. Would anyone have any thoughts based on their experience representing discourse? Also, has anybody used elements from the OBO Information Artifact Ontology w/ SWAN to represent scientific discourse? We also are interested in representing DDIs that are computationally inferred from assertions in the DIKB but are not sure if there is an ontology for algorithmic inferences. Would anyone have a suggestion? Thanks in advance, -Rich -- Richard Boyce, PhD Assistant Professor of Biomedical Informatics and Intelligent Systems Scholar, Comparative Effectiveness Research Program University of Pittsburgh rdb20@pitt.edu 412-648-6768
Received on Thursday, 5 May 2011 15:46:57 UTC