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Journal article
Evaluation of Semi-Automatic Metadata Generation Tools: A Survey of the Current State of the Art
Information technology and libraries, v 34(3)
01 Jan 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Assessment of the current landscape of semi-automatic metadata generation tools is particularly important considering the rapid development of digital repositories and the recent explosion of big data. Utilization of semi-automatic metadata generation is critical in addressing these environmental changes and may be unavoidable in the future considering the costly and complex operation of manual metadata creation. To address such needs, this study examines the range of semi-automatic metadata generation tools (N = 39) while providing an analysis of their techniques, features, and functions. The study focuses on open-source tools that can be readily utilized in libraries and other memory institutions. The challenges and current barriers to implementation of these tools were identified. The greatest area of difficulty lies in the fact that the piecemeal development of most semi-automatic generation tools only addresses part of the issue of semi-automatic metadata generation, providing solutions to one or a few metadata elements but not the full range of elements. This indicates that significant local efforts will be required to integrate the various tools into a coherent set of a working whole. Suggestions toward such efforts are presented for future developments that may assist information professionals with incorporation of semi-automatic tools within their daily workflows.
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Details
- Title
- Evaluation of Semi-Automatic Metadata Generation Tools: A Survey of the Current State of the Art
- Creators
- Jung-ran Park - Drexel UniversityAndrew Brenza - Drexel University
- Publication Details
- Information technology and libraries, v 34(3)
- Publisher
- Amer Library Assoc
- Number of pages
- 21
- Grant note
- Institute of Museum and Library Services
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000368667600002
- Scopus ID
- 2-s2.0-84942583296
- Other Identifier
- 991019168265704721
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Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Information Science & Library Science