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New Technology of Library and Information Service  2009, Vol. 3 Issue (3): 23-29    DOI: 10.11925/infotech.1003-3513.2009.03.05
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Collection/Item Metadata Relationships
Allen H. Renear  Karen M.Wickett  Richard.J.Urban  David Dubin  Sarah L.Shreeves
(Graduate School of Library and Information Science Center for Informatics Research in
Science and ScholarshipUniversity of Illinois, USA)
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Contemporary retrieval systems, which search across collections, usually ignore collection-level metadata. Alternative approaches, exploiting collection-level information, will require an understanding of the various kinds of relationships that can obtain between collection-level and item-level metadata. This paper outlines the problem and describes a project that is developing a logic-based framework for classifying collection/item metadata relationships. This framework will support (i) metadata specification developers defining metadata elements, (ii) metadata creators describing objects, and (iii) system designers implementing systems that take advantage of collection-level metadata. We present three examples of collection/item metadata relationship categories, attribute/value-propagation, value-propagation, and value-constraint and show that even in these simple cases a precise formulation requires modal notions in addition to first-order logic. These formulations are related to recent work in information retrieval and ontology evaluation.

Key wordsMetadata      Dublin Core      Collections      Context      logic      Inferencing     
Received: 09 February 2009      Published: 25 March 2009


About author:: Allen H. Renear Karen,M.Wickett,Richard.J.Urban,David Dubin,Sarah L.Shreeves

Cite this article:

Allen H. Renear Karen,M.Wickett,Richard.J.Urban,David Dubin,Sarah L.Shreeves. Collection/Item Metadata Relationships. New Technology of Library and Information Service, 2009, 3(3): 23-29.

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[1] Arms, William Y., Naomi Dushay, Dave Fulker, and Carl Lagoze. (2003). A Case Study in Metadata Harvesting: The NSDL. Library Hi Tech, 21(2), 228-237.
[2] Brachman, Ronald J. (1983). What ISA is and isn’t: An Analysis of Taxonomic Links in Semantic Networks. IEEE Computer, 16 (10), 30-36.
[3] Brachman, Ronald J., Deborah L. McGuinness, Peter F. Patel-Schneider, Lori A. Resnick, and Alex Borgida. (1991).Living with classic: When and How to Use a KL-ONE-like Language. In John Sowa, Principles of Semantic Networks: Explorations in the Representation of Knowledge, (pp. 401-456).
[4] Brockman, William, Laura Neumann, Carole L. Palmer, Tonya.J. Tidline. (2001). Scholarly Work in the Humanities and the Evolving Information Environment. Washington, DC: Digital Library Federation/Council on Library and Information Resources.
[5] Christenson, Heather, and Roy Tennant. (2005). Integrating Information Resources: Principles, Technologies, and Approaches. California Digial Library. Retrieved from
[6] Currall, James, Michael Moss, and Susan Stuart. (2004). What is a collection? Archivaria, 58, 131-146.
[7] Dempsey, Lorcan. (2005, October 9). From Metasearch to Distributed Information Environments. Message Posted to
[8] DLF. (2005). The Distributed Library: OAI for Digital Library Aggregation. OAI Scholars Advisory Panel, 2005 June 20-21, Washington, DC. Digital Library Federation.
[9] DCMI. (2007). Dublin Core Collections Application Profile. Retrieved April 13, 2008, from
[10] Dushay, Naomi, and Diane I. Hillmann. (2003). Analyzing Metadata for Effective use and Re-use. DC-2003:Proceedings of the International DCMI Metadata Conference and Workshop, (pp. 161-170).
[11] Foulonneau, Muriel, Timothy W. Cole, Thomas G. Habing, and Sarah L. Shreeves. (2005). Using Collection Descriptions to Enhance Aggregation of Garvested Item-level Metadata. Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries, (pp. 32-41). ACM Press.
[12] Gasser, Less, Besiki Stvilia, Michael B. Twidale, and Linda C. Smith. (2001). A New Framework for Information Quality Assessment. Technical Report ISRN UIUCLIS--2001/1+AMAS. Champaign, Ill.: University of Illinois at Urbana Champaign.
[13] Guarino, Nicola, and Christopher A. Welty. (2004). An Overview of OntoClean. In Steffen Staab and Rudi Studer, Handbook on Ontologies. Springer.
[14] Heaney, Michael. (2000). An Analytic Model of Collections and Their Catalogues. UK Office for Library and Information Science.
[15] Hutt, Arven, and Jenn Riley. (2005). Semantics and Syntax of Dublin Core Usage in Open Archives Initiative Data Providers of Cultural Heritage Materials. Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries, Denver, Colo, June 7-June 11, (pp. 262-270). New York: ACM Press.
[16] Lagoze, Carl, Dean Krafft, Tim Cornwell, Naomi Dushay, Dean Eckstrom, and John Saylor. (2006). Metadata Aggregation and "Automated Digital Libraries": A Retrospective on the NSDL experience. Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries. New York: ACM Press.
[17] Lalmas, Mounia. (1998). Logical Models in Information Retrieval. Information Processing and Management, (34)1, 19-33.
[18] Lee, Hur-Li. (2005). The Concept of Collection from the User’s Perspective. Library Quarterly, 75(1), 67-85.
[19] Lee, Hur-Li. (2000). What is a Collection? JASIS, 51(12), 1106-1113.
[20] Palmer, Carole L. (2004). Thematic Research Collections. In Susan Schreibman, Raymond G. Siemens, and John Unsworth (Eds.), Companion to digital humanities (pp. 348-365). Oxford: Blackwell Publishing.
[21] Palmer, Carole L., and Ellen M. Knutson. (2004). Metadata Practices and Implications for Federated Collections. Proceedings of the 67th ASIS&T Annual Meeting.
[22] Palmer, Carole L., Ellen M. Knutson, Michael Twidale, and Oksana Zavalina. (2006). Collection Definition in Federated Digital Resource Development. Proceedings of the 69th ASIS&T Annual Meeting, Austin, Texas, 2006.
[23] Renear, Allen. H., Richard Urban, Karen Wickett, C. L. Palmer., and David Dubin. (2008a). Substaining Collection Value: Managing Collection/item Metadata Relationships. Proceedings of the Digital Humanities Conference, Oulu, Finland, 2008.

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