AI

Proposes a class of applications called Collective Knowledge Systems, which are the “killer apps” for the integration of the Social Web (2.0) and the Semantic Web. Characteristics of these systems, principles, and examples from real applications are included.

Original abstract: What can happen if we combine the best ideas from the Social Web and Semantic Web?  The Social Web is an ecosystem of participation, where value is created by the aggregation of many individual user contributions.  The Semantic Web is an ecosystem of data, where value is created by the integration of structured data from many sources.  What applications can best synthesize the strengths of these two approaches, to create a new level of value that is both rich with human participation and powered by well-structured information?  This paper proposes a class of applications called collective knowledge systems, which unlock the “collective intelligence” of the Social Web with knowledge representation and reasoning techniques of the Semantic Web.

This is the paper that first published the fabled definition of ontology as specification, with a theoretical grounding in AI agency and knowledge representation. This journal was merged into the International Journal of Human-Computer Studies, and this paper was recognized as the highest cited article in the history of those journals.

Abstract: To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems.