RuleML FOAF


RuleML FOAF
A Use Case for Web-based Social Networking

Jie Li, Harold Boley, Virendrakumar C. Bhavsar, David Hirtle, Jing Mei

Version History, 2005-12-04: Version 0.1


Version History, 2006-01-17: Version 0.2


Version History, 2006-03-31: Version 0.3


Web-based social networking is emerging as a major application area for Semantic Web metadata. Recently, a number of portals have become popular in this area, among which the FOAF (Friend-Of-A-Friend project) addresses. The RDF-based FOAF, originated by Dan Brickley and Libby Miller, allows expression of personal information and relationships, and permits machine-readable homepages for grouping, categorization and linking of persons.

However, the FOAF vocabulary does not currently capture rule knowledge but only facts. Therefore, we aim at enhancing FOAF by applying a Web Rule Language such as RuleML (Rule Markup Language).
Overview

RuleML FOAF is currently being developed. We will mainly propose a rule vocabulary specification augmenting the current fact-only FOAF vocabulary. For an introduction see Jie Li's RuleML FOAF (PPT), or our RIF RuleML FOAF (PPT), or our short version of RIF RuleML FOAF (PPT).

RuleML FOAF has been applied in an early study on finding an expert with FOAF facts and rules as well as a domain taxonomy. For more details see our paper entitled Expert Finding for eCollaboration Using FOAF with RuleML Rules or the corresponding talk (PPT) for the Montreal Conference on eTechnologies (MCeTech), 2006.

Our Objectives

Our main objectives of the RuleML FOAF project are as follows:

Develop the current RDF FOAF vocabulary for both elementary and rule-derivable facts Enrich such descriptive facts by OO RuleML rules deriving new descriptions Develop a general RuleML FOAF vocabulary for rules Build rulebases for the FOAF community to exchange and share information Implement both FNF (Fact Normal Form) and RNF (Rule Normal Form) to benefit both the current FOAF community and the development of FOAF projects by extending them inferential with more new features.
Highlights of Our Two Normal Forms

Two normal forms for RuleML FOAF rulebases are proposed for our system: a rule-oriented normal form (RNF) and a fact-oriented normal form (FNF). While the RNF is more compact, the FNF directly corresponds to RDF FOAF facts.

Rule-oriented Normal Form (RNF): The RNF includes rules as well as the (elementary) facts that are needed by the premises of the rules. Those facts that are derivable from the rules by a bottom-up engine such as OO jDREW BU are removed from the rulebase. (Complementarily, corresponding queries could be posed to a top-down engine such as OO jDREW TD.) The FNF includes elementary facts and derived facts. Rules are removed from the published rulebase after all possible facts are derived by running a bottom-up engine such as OO jDREW BU. (When new elementary facts are asserted, the rules need to be re-applied to them.)
Our Proposed Work

We propose to apply the RuleML language to metadata constituting FOAF profiles so that FOAF rules can enrich FOAF facts. The realization of this proposed work can be divided into the following steps.

FOAF Vocabularies in OO RuleML (via POSL) XSLT Translation of OO RuleML Facts to RDF Designing a FOAF Rule Vocabulary Computing Derived FOAF Properties in Social Networks Use Cases for FOAF RuleML

Site Contact: Harold Boley. Page Version: 2006-05-17


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