Planned 2-23-06 HCLSig Teleconference Agenda: Time: 11:00 am EDT Feb 23 2006 in America/New York for a duration of 1 hour Phone: tel:+1-617-761-6200 (Zakim) conference #4257 (HCLS) irc://irc.w3.org:6665/hcls Chairs: Eric Neumann, Tonya Hongsermeier Scribe: Brian Gilman a) Convene, take roll, review record b) Propose next call March 9, 2006, nominate a scribe c) Introductions - New participants since last call. d) Review a DRAFT TEMPLATE for task proposals of the various sub-groups. Attached is a DRAFT TEMPLATE formatted with the BIORDF group proposal to serve as a point of discussion regarding what are the key components of a Task Proposal. It's derivative of a draft template <http://esw.w3.org/topic/HCLSIGGRDDL> Eric Miller has supplied with additional features added. The current proposals are in a broad range, from granular tasks to more sweeping use case implementations. What is the right level of granularity? How do we get to clearer delineation of the tasks and task-owners? How do we clarify interrelationship of the tasks vis-a-vis each other and other activities of the W3C <<BioRDF task proposal DRAFT TEMPLATE.htm>>
e) Outstanding issues: Does the Unstructured to Structured Data proposal still stand? Who are the key participants in this proposal? Eric Neumann, Tonya Hongsermeier HCLSIG co-chairsTitle: Task: *DRAFT* To build a life sciences demo using RDF and OWL to get a stronger understanding as to the work required, to expl
Task:
Identify best practices and gaps in current available tools for converting
structured data into RDF? Task Objectives: 1) This HCLSIG task is designed to provide
guidence, examples, and shared experiences collected using GRDDL for exposing collections of HCLSIG related content for use in the Semantic Web.
2) To build a life sciences demo using RDF and OWL to
get a stronger understanding as to the work required, to explore the
effectiveness of current tools, and to document our finding to help accelerate
the adoption of the Semantic Web by others.
Task Participants: Olivier Bodenreider, Kei Cheung, Roger Cutler, Brian
Gilman, Joanne Luciano, Brian Osborne, Alan Ruttenburg, Matt Shanahan, Susie
Stephens, Charles Tilford. @@ who else @@ Use case context: A neurosciences knowledge integration portal??? Problem statement for this use case: (what does this task solve demonstrating
the value of semantic web technologies in the context of this use case?) Deliverable(s) A demonstration of a use
case with the following features:
· The demo will primarily
take advantage of data sets from the NCBI. However, additional data sets will
be required with time as the ultimate goal is to build a demo that spans from
bench to bedside. · The demo will focus on
the domain area of neuroscience, in order to be able to build upon the ongoing
work in Scientific Commons and SWANS. ·
The main focus of the
demo is on the integration of many data sets, although scalability is also of
interest. ·
? A Report on
tool gaps or best practices?? Related resources: - Gleaning Resource Descriptions from Dialects of Languages
(GRDDL), Dan Connolly, Dominique Hazaël-Massieux, World Wide
Web Consortium (W3C) - XML and RDF with GRDDL, Dominique
Hazaël-Massieux, World Wide Web Consortium (W3C), -
XSLT, RDB access Task supports and dependencies: - @@ user group 1 @@, @@ user group 2 @@ Tools and Services: -
W3C online GRDDL demo service Timeline for Task Completion (below should outline sequence and owners for
each step) Stage 1 (3 month goals) · Identify the initial data sources to be used
in the demo. · Explore additional data
sources that would be required for the demo to span bench to bedside. · Learn about GRDDL,
SPARQL, OWL, etc. · Increase knowledge of
neuroscience. · Set up a Wiki for
communication. Stage 2 (6 months goals) · Transform data into RDF
from Word, Excel, XML, Relational, etc. · Analysis of semantic
requirements (connect to ontology sub-group). · Move from screen
scraping to an API. · Create documents that
describe work undertaken, and observations. Stage 3 (12 months goals) · Use ontologies with the
demo. · Answer scientific
questions and hopefully glean new scientific insights through using the demo. · Validate the
effectiveness of the data integration. |