Metadata extraction and harvesting: A comparison of two automatic metadata generation applications

Abstract

This research explores the capabilities of two Dublin Core automatic metadata generation applications, Klarity and DC-dot. The top level Web page for each resource, from a sample of 29 resources obtained from National Institute of Environmental Health Sciences (NIEHS), was submitted to both generators. Results indicate that extraction processing algorithms can contribute to useful automatic metadata generation. Results also indicate that harvesting metadata from META tags created by humans can have a positive impact on automatic metadata generation. The study identifies several ways in which automatic metadata generation applications can be improved and highlights several important areas of research. The conclusion is that integrating extraction of harvesting methods will be the best approach to creating optimal metadata, and more research is needed to identify when to apply which method. © 2003 by The Haworth Press, Inc.