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Natural Language Processing with Python by Edward Loper, Steven Bird, Ewan Klein

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Describing Language Resources Using OLAC Metadata

Members of the NLP community have a common need for discovering language resources with high precision and recall. The solution which has been developed by the Digital Libraries community involves metadata aggregation.

What Is Metadata?

The simplest definition of metadata is “structured data about data.” Metadata is descriptive information about an object or resource, whether it be physical or electronic. Although the term “metadata” itself is relatively new, the underlying concepts behind metadata have been in use for as long as collections of information have been organized. Library catalogs represent a well-established type of metadata; they have served as collection management and resource discovery tools for decades. Metadata can be generated either “by hand” or automatically using software.

The Dublin Core Metadata Initiative began in 1995 to develop conventions for finding, sharing, and managing information. The Dublin Core metadata elements represent a broad, interdisciplinary consensus about the core set of elements that are likely to be widely useful to support resource discovery. The Dublin Core consists of 15 metadata elements, where each element is optional and repeatable: Title, Creator, Subject, Description, Publisher, Contributor, Date, Type, Format, Identifier, Source, Language, Relation, Coverage, and Rights. This metadata set can be used to describe resources that exist in digital or traditional formats.

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