Investigating and modeling metadata use to support information architecture development in the statistical knowledge network

Authors:
Carol A. Hert;Sheila O. Denn;Daniel W. Gillman;Jung Sun Oh;Maria Cristina Pattuelli;Naybell Hernández
Affiliations:
SchemaLogic, Inc., Kirkland, WA;Graduate School of Library and Information Science, Simmons College, Boston, MA;United States Bureau of Labor Statistics, Washington, DC;School of Information and Library Science, University of North Carolina-Chapel Hill, Chapel Hill, NC;School of Information and Library Science, University of North Carolina-Chapel Hill, Chapel Hill, NC;School of Information Studies, Syracuse University, Syracuse, NY
Venue:
Journal of the American Society for Information Science and Technology
Year:
2007

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Abstract

Metadata and an appropriate metadata model are non-trivial components of information architecture conceptualization and implementation, particularly when disparate and dispersed systems are integrated. Metadata availability can enhance retrieval processes, improve information organization and navigation, and support management of digital objects. To support these activities efficiently, metadata need to be modeled appropriately for the tasks. The authors' work focuses on how to understand and model metadata requirements to support the work of end users of an integrative statistical knowledge network (SKN). They report on a series of user studies. These studies provide an understanding of metadata elements necessary for a variety of user-oriented tasks, related business rules associated with the use of these elements, and their relationship to other perspectives on metadata model development. This work demonstrates the importance of the user perspective in this type of design activity and provides a set of strategies by which the results of user studies can be systematically utilized to support that design.