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Structural metadata describes how the components of an object are organized. An example of structural metadata would be how pages are ordered to form chapters of a book. Finally, administrative metadata gives information to help manage the source. Administrative metadata refers to the technical information, such as file type, or when and how ...
A good example of metadata is the cataloging system found in libraries, which records for example the author, title, subject, and location on the shelf of a resource. Another is software system knowledge extraction of software objects such as data flows, control flows, call maps, architectures, business rules, business terms, and database schemas.
A type of structural and metadata encoding system using an XML Document Type Definition (DTD) was the result of these efforts. The MoAII DTD was limited in that it did not provide flexibility in which metadata terms could be used for the elements in the descriptive, administrative, and structural metadata portions of the object. [5]
Depending on the application the data objects may be, for example, text documents, images, [3] audio, [4] mind maps [5] or videos. Often the documents themselves are not kept or stored directly in the IR system, but are instead represented in the system by document surrogates or metadata.
Ecological Metadata Language (EML) [1] is a metadata standard developed by and for the ecology discipline. It is based on prior work done by the Ecological Society of America and others, [2] including the Knowledge Network for Biocomplexity. [3] EML is a set of XML schema documents that allow for the structural expression of metadata. It was ...
The MARC Standards, which BIBFRAME seeks to replace, were developed by Henriette Avram [2] at the U.S. Library of Congress during the 1960s. By 1971, MARC formats had become the national standard for dissemination of bibliographic data in the United States, and the international standard by 1973.
The ISO/IEC 11179 model is a result of two principles of semantic theory, combined with basic principles of data modelling. The first principle from semantic theory is the thesaurus type relation between wider and more narrow (or specific) concepts, e.g. the wide concept "income" has a relation to the more narrow concept "net income".
Metadata is often said to be "data about data", but this is misleading. Data profiles are an example of actual "data about data". Metadata adds one layer of abstraction to this definition– it is data about the structures that contain data. Metadata may describe the structure of any data, of any subject, stored in any format.