Clustering of LDAP Directory Schemas to Facilitate Information Resources Interoperability Across Organizations

Jianghua Liang, Vijay K. Vaishnavi
Department of Computer Information Systems
Georgia State University

Art Vandenberg
Information Systems & Technology
Georgia State University

Absract

Directories provide a well-defined general mechanism for describing organizational resources such as the resources of the Internet2 higher education research community and the GRID community. LDAP (Lightweight Directory Access Protocol) directory services enable data sharing by defining information's metadata (schema) and access protocol. Interoperability of directory information between organizations is increasingly important. Improved discovery of directory schemas across organizations, better presentation of their semantic meaning, and fast definition and adoption (reuse) of existing schemas promotes interoperability of information resources in directories. This paper focuses on the discovery of related directory object class schemas and in particular on clustering schemas to facilitate discovering relationships and so enable reuse. The results of experiments exploring the use of Self-Organizing Maps (SOM) to cluster directory object classes at a level comparable to a set of human experts are presented. The results show that it is possible to discover the values of the parameters of the SOM algorithm so as to cluster directory metadata at level comparable to human experts.

KEY WORDS AND PHRASES: Self-Organizing Maps, LDAP directories, clustering analysis, clustering evaluation, neural network configuration