**6. Case study**

In this section, we're going to make an in-depth study of applications built on the top of FOAF project and to provide insights into the semantic web based collaborative knowledge management.

The Friend of a Friend (FOAF) is a project about creating a web of machine-readable homepages describing people, the links between them and the things they create and do[19]. The project accumulates various kinds of data, such as text, photo and records, from real practices and defines relations between different data source by social relations[20][21][22].Knowledge life cycle of a typical FOAF application is as follows:

(1) Knowledge representation. Users of these applications can publish their personnel information in FOAF language , an XML-based RDF knowledge representation language introduced by the FOAF project. The language employs classes FOAF:Agent,

The Semantic Web-Based Collaborative Knowledge Management 99

knowledge processing activities complex. The Semantic Web provides a new platform for Man-Machine cooperative knowledge processing because of its computer-readable knowledge representation technologies. Therefore, Man-Machine cooperative knowledge

This chapter discussed new features of the Semantic Web-based knowledge processing, designed a model to combine the Semantic Web with Web2.0 for knowledge processing and proposed a unified framework of organizational knowledge ecosystems and knowledge processing software systems, after in-depth studies on the Semantic Web, Web 2.0 and Knowledge Ecology. Research methods such as literature review, case study, system study,

This research was supported by Natural Science Foundation of China (No. 71103020), Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China), Ministry of Education (No. KF2011001), Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality(No. PHR201108368), and National Basic Research Program of China (973

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**8. Acknowledgments** 

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**9. References** 

FOAF:Document, FOAF:Group, FOAF:Image, FOAF:OnlineAccount, FOAF:Orgnization, FOAF:Person, FOAF:PersonalProfileDocument, FOAF:Project to represent an agent, document, group, image, account, organization, person, personal profile information or project respectively. Currently, although some tools are developed to capture FOAF information automatically from the web, the reliability of those tools is not enough to be completed the task by computers itself. The machine's knowledge presentation is in need of man's intervention. As a result, knowledge representation in FOAF project should be conducted by the collaboration of men and machines.

(2) Knowledge interconnection: The FOAF language defines tags FOAF:knows, FOAF:made, FOAF:maker, FOAF:fundBy, FOAF:member, FOAF:member, FOAF:currentProjects, FOAF:pastProjects, FOAF:SchoolHomepag to represent relationships between friends, resource and its makers, resource and its funders, organization and its members ,a project and its relevant projects, persons and schools. Therefore, applications on the top of FOAF can build a machine readable web of knowledge elements.

(3) Knowledge reasoning: Applications built on the top of FOAF can conduct social network analysis and compute the size or density of a collaborative network, degree of or distances between actors, length of a collaborative walk, diameter and radius of a collaborative network, reachability between enablers, and centrality of an agent.

(4) Knowledge retrieving: Queries of knowledge retrieving in these applications can be written in the SPARQL language, a query language for RDF recommended by W3C.As SPARQL has a good support for expressing queries across diverse data sources, applications built on the FOAF can provide cross domain data sharing and on-demand knowledge services.

(5) Knowledge validation: FOAF applications can validate the results sets of retrieving activities by integration the semantic web with web2.0. The knowledge represented by semantic web technologies has good support for machine readability and be convenient to validate automatically. However, machines are not always competent at automatic knowledge validation and in need of human intervention. Pro-Ams (Profession Amateurs) from the long tails of web2.0 applications have good domain knowledge and can be used to make up for deficiencies in knowledge validation by computers.

(6) Knowledge integration: the Knowledge validation could be followed by integration of knowledge from different sources. A semantic web-based collaborative knowledge processing system built on FOAF project has a good capability for integrating personal information with tacit knowledge, explicit knowledge or application by integration the semantic web technologies with web2.0 principles.

While FOAF is a simple application of the Semantic Web, it has been widely used in social network analysis[23, search engine[24], e-commerce partner query [25].The success of FOAF application not only stress the necessity for studying human-machine collaborative knowledge management, but also highlights the importance of human intervention in knowledge processing by computers.
