Joint Initiative on Extending the FOAF Vocabulary for Expert Finding
This page is dedicated to starting the ExpertFinder subproject of FOAF on devising vocabulary extensions and best practices to annotate not only personal home pages, but also pages of institutions, conferences, publication indexes, etc. with adequate metadata to find experts on particular topics.
What do you think should be the project goals?
- The 1st ExpertFinder Workshop (EFW2007), co-located with the KnowledgeWeb General Assembly took place in Berlin, January 16, 2007. Find more information about the outcomes here or on the workshop homepage.
- The 2nd ExpertFinder Workshop ([wiki:/FEW2007 FEW2007]), co-located with the ISWC 2007 Busan took place in Busan, Novemeber 12, 2007. 2nd Workshop Homepage, Minutes of Meeting at Busan.
A mailing list has been set up for enhancing collaboration: if you are interested in joining this effort, please check out the expertfinder-dev mailinglist!
What do you think Expertfinder action Items should be?
- Get people to share what they are working on
- Make a list of action points
- Set EXPERTFINDERPROJECTPLAN
- Higgings (Eclipse)
The use cases for this initiative reach from scientific communities (annotation of research institutes, finding experts/reviewers for a certain area) to industrial (human resources, company and job profiles), creating CVs, etc.
For the widely adopted use of such vocabulary extensions we identify the following main goals:
- An Extended vocabulary based on RDF FOAF: to describe persons, institutions, enterprises, publications, events, projects, areas of expertise and interests...
- Best Practices: on how to publish the related metadata in order to enable automatic processing.
- Rules and Other Enabling Technologies: The possibility to add rules to metadata to express implicit, interlinked metadata. Support implementations of ExpertFinder applications.
- Use Cases: Identify practical real world use cases and devise enabling technologies and applications to demonstrate the benefits of publishing and combining metadata using common vocabularies.