Functionalities for automatic metadata generation applications: a survey of metadata experts' opinions

  • Authors:

  • Jane Greenberg;Kristina Spurgin;Abe Crystal

  • Affiliations:

  • School of Information and Library Science, University of North Carolina at Chapel Hill, 100 Manning Hall, CB #3360, Chapel Hill NC 27599-3360, USA.;School of Information and Library Science, University of North Carolina at Chapel Hill, 100 Manning Hall, CB #3360, Chapel Hill NC 27599-3360, USA.;School of Information and Library Science, University of North Carolina at Chapel Hill, 100 Manning Hall, CB #3360, Chapel Hill NC 27599-3360, USA

  • Venue:
  • International Journal of Metadata, Semantics and Ontologies
  • Year:
  • 2006

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Abstract

This paper reports on the automatic metadata generation applications (AMeGA) project's metadata expert survey. Automatic metadata generation research is reviewed and the study's methods, key findings and conclusions are presented. Participants anticipate greater accuracy with automatic techniques for technical metadata (e.g., ID, language, and format metadata) compared to metadata requiring intellectual discretion (e.g., subject and description metadata). Support for implementing automatic techniques paralleled anticipated accuracy results. Metadata experts are in favour of using automatic techniques, although they are generally not in favour of eliminating human evaluation or production for the more intellectually demanding metadata. Results are incorporated into Version 1.0 of the Recommended Functionalities for automatic metadata generation applications (Appendix A).