HCLSIG BioRDF Subgroup/Meetings/2006-09-25 Conference Call

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Conference Details

  • Date of Call: Monday September 25, 2006
  • Time of Call: 11:00am Eastern Time
  • Dial-In #: +1.617.761.6200 (Cambridge, MA)
  • Participant Access Code: 246733 ("BIORDF")
  • IRC Channel: irc.w3.org port 6665 channel #BioRDF (see W3C IRC page for details, or see Web IRC)
  • Duration: ~1 hour
  • Convener: Susie Stephens
  • Scribe: Marja-Riitta Koivunen (Zakim instructions)

Attendees: Oliver Bodenreider, Alan Ruttenberg, Kei Cheung, Susie Stephens, Jonathan Rees, Vipal Kashyap, John Barkley, Marja Koivunen, Joanne Luciano, Daniel Rubin, Don Doherty, and Scott Marshall.

Regrets: Ora Lassila, Kerstin Forsberg, Carole Goble and Matthias Samwald.


  1. We'll collect URI statements for the F2F
  2. Kei Cheung will give a demo of AlzPharm. To view the demo go to https://conference.oracle.com and then enter the ID 56605701.
  3. Vipal Kashyap will give an overview of BIONT, highlight possible intersection points between BioRDF and BIONT for the F2F meeting, and describe BIONT use cases

1 Collection of URI statements

  • collection of URI statements will be done by e-mail (Action item: Susie)

2 Kei Cheung demo

Run demo

  1. goto AlzPharm
  2. query drug: Donepezil
  3. Result page has a list of articles related to the drug with description, journal, title and some other semantic information
  4. Last column has PubMed article information e.g. http://www.ncbi.nlm.nih.gov/entrez/query.fcgiCMD=search&DB=pubmed&term=12469988 and corresponding discussions on the Alzforum
  5. Explore a sample article with a lot of Alzforum discussions with title: Long-term donepezil treatment in 565 patients with Alzheimer's disease (AD2000): randomised double-blind trial (http://www.alzforum.org/pap/annotation.asp?pmid=15220031).

3 Vipal Kashyap overview of BIONT

  • the actual ontology is discussed outside this call
  • BIONT use cases
  • aim is to do use case modelling in style of UML
  • we concentrate more on what's the value of the technologies than the details of the technologies
  • use case main page(id problems have been solved in these cases)

case 1: correlation between SNPs and genes


  • today just keyword search but here aim is for better semantic matching between concepts in different data sources using different ontologies

case 2:


  • again, SW can be helpful in semantic matching steps

case 3:


BioRDF/Tasks section]