Contributed by Organizations or Campuses; Articles, Papers, and Reports; and Metadata

The Web puzzle of online information resources often hinders end-users from effective and efficient access to these resources. Clustering resources into appropriate subject-based groupings may help alleviate these difficulties, but will it work with heterogeneous material? The University of Michigan and the University of California Irvine joined forces to test automatically enhancing metadata records using the Topic Modeling algorithm on the varied OAIster corpus. We created labels for the resulting clusters of metadata records, matched the clusters to an in-house classification system, and developed a prototype that would showcase methods for search and retrieval using the enhanced records. Results indicated that while the algorithm was somewhat time-intensive to run and using a local classification scheme had its drawbacks, precise clustering of records was achieved and the prototype interface proved that faceted classification could be powerful in helping end-users find resources.

In making this argument, the article demystifies metadata by defining and categorizing types of standards, provides a brief historical overview of the rise of descriptive standards in museums, libraries and archives, and considers the current tensions and ambitions in making descriptive practice more economic [1].

Martha L. Brogan's Contexts and Contributions: Building the Distributed Library is a major contribution to the Digital Library Federation's (DLF) suite of work that focuses on the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH). With generous funding from the Institute of Museum and Library Services, DLF has harnessed deep OAI expertise from the University of Michigan, the University of Illinois at Urbana-Champaign, and Emory University to prototype "next-generation" OAI services informed by advisory panels of scholars and technical experts; to build registries of providers to aid in the creation of new OAI-based services; and to formulate best practices for sharable metadata that focus what we have learned collectively for innovative library services. The best practices work has received intellectual and practical support from our colleagues at the National Science Digital Library (NSDL), a service of the National Science Foundation (NSF).