Final Report for the AMeGA (Automatic Metadata Generation Applications) Project

Persistent Link:
http://hdl.handle.net/10150/106026
Title:
Final Report for the AMeGA (Automatic Metadata Generation Applications) Project
Author:
Greenberg, Jane; Spurgin, Kristina; Crystal, Abe
Citation:
Final Report for the AMeGA (Automatic Metadata Generation Applications) Project 2005,
Issue Date:
2005
URI:
http://hdl.handle.net/10150/106026
Submitted date:
2005-06-23
Abstract:
Summary of findings (from Executive Summary of report for Goal 1 (complete), Goal 2, (Partial), Goal 3 (see actual document)): Research in the area of automatic metadata generation falls, primarily, into two areas: Experimental research, focusing on information retrieval techniques and digital resource content, and applications research, focusing on the development of content creation software and metadata generation tools used in the operational setting. The main finding, presented in this report, is that there is a disconnect between experimental research and application development. It seems that metadata generation applications could be vastly improved by integrating experimental research findings. Metadata generation applications might also improve metadata output if they took advantage of metadata generation functionalities supported by content creation software. For example, Microsoft Word supports the metadata generation of a number of elements that conceptually map to the Dublin Core metadata standard. Some of these elements are generated automatically, while others need to be input by a document author or another person. Content creation software provides a means for generating metadata, which can be harvested by metadata generation applications. More research is needed to understand how metadata creation features in content creation software are used in practice. ... Two-hundred and seventeen (217) survey participants provided responses useful for data analysis (the initial goal was to recruit at least 100 participants). Three quarters of participants had three or more years of cataloging and/or indexing experience, verifying their status as metadata experts. Organizations are using a variety of different metadata standards (selected examples include: MAchine Readable Cataloging (MARC)â bibliographic format, Dublin Core, Encoded Archival Description, Gateway to Educational Materials, Metadata Object Description Schema, Text Encoding Initiative, and the Government Information Locator Service). Most participants (81%) reported using one or two systems for metadata creation in their organization, whereas one participant reported the use of seven different systems.
Type:
Technical Report
Language:
en
Keywords:
Metadata

Full metadata record

DC FieldValue Language
dc.contributor.authorGreenberg, Janeen_US
dc.contributor.authorSpurgin, Kristinaen_US
dc.contributor.authorCrystal, Abeen_US
dc.date.accessioned2005-06-23T00:00:01Z-
dc.date.available2010-06-18T23:38:25Z-
dc.date.issued2005en_US
dc.date.submitted2005-06-23en_US
dc.identifier.citationFinal Report for the AMeGA (Automatic Metadata Generation Applications) Project 2005,en_US
dc.identifier.urihttp://hdl.handle.net/10150/106026-
dc.description.abstractSummary of findings (from Executive Summary of report for Goal 1 (complete), Goal 2, (Partial), Goal 3 (see actual document)): Research in the area of automatic metadata generation falls, primarily, into two areas: Experimental research, focusing on information retrieval techniques and digital resource content, and applications research, focusing on the development of content creation software and metadata generation tools used in the operational setting. The main finding, presented in this report, is that there is a disconnect between experimental research and application development. It seems that metadata generation applications could be vastly improved by integrating experimental research findings. Metadata generation applications might also improve metadata output if they took advantage of metadata generation functionalities supported by content creation software. For example, Microsoft Word supports the metadata generation of a number of elements that conceptually map to the Dublin Core metadata standard. Some of these elements are generated automatically, while others need to be input by a document author or another person. Content creation software provides a means for generating metadata, which can be harvested by metadata generation applications. More research is needed to understand how metadata creation features in content creation software are used in practice. ... Two-hundred and seventeen (217) survey participants provided responses useful for data analysis (the initial goal was to recruit at least 100 participants). Three quarters of participants had three or more years of cataloging and/or indexing experience, verifying their status as metadata experts. Organizations are using a variety of different metadata standards (selected examples include: MAchine Readable Cataloging (MARC)â bibliographic format, Dublin Core, Encoded Archival Description, Gateway to Educational Materials, Metadata Object Description Schema, Text Encoding Initiative, and the Government Information Locator Service). Most participants (81%) reported using one or two systems for metadata creation in their organization, whereas one participant reported the use of seven different systems.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.subjectMetadataen_US
dc.titleFinal Report for the AMeGA (Automatic Metadata Generation Applications) Projecten_US
dc.typeTechnical Reporten_US
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