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METADATA TYPOLOGY AND METADATA USES
2013This chapter provides an overview of metadata typologies and uses, clarifying why sometimes different approaches to metadata types and metadata uses could be misleading. We present a general overview of how metadata can be interpreted differently, and then elaborate specific typologies of metadata schemas, metadata schemes, and metadata elements.
Mendez, Eva, Van Hooland, Seth
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Communications of the ACM, 2006
Metadata promises too much value as a business management tool to dismiss its implementation and maintenance effort as the equivalent of Sisyphean torture.
Ganesan Shankaranarayanan, Adir Even
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Metadata promises too much value as a business management tool to dismiss its implementation and maintenance effort as the equivalent of Sisyphean torture.
Ganesan Shankaranarayanan, Adir Even
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Metadata, metadata, everywhere – but where is the hook?
OCLC Systems & Services: International digital library perspectives, 2001Encoded Archival Description (EAD) and Dublin Core (DC) are metadata standards with different purposes. EAD fully supports archival descriptive practices, but lacks the robust mechanisms for Web resource discovery that DC provides. This article explores the relationship between the two standards and pinpoints areas where there could be a more direct ...
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2022
This chapter seeks to demystify metadata for archaeologists who are responsible for producing and managing digital documentation, but who are not themselves trained in library and information science. It provides a general overview of the role and importance of metadata in contextualizing digital documents and ensuring possibilities for future reuse ...
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This chapter seeks to demystify metadata for archaeologists who are responsible for producing and managing digital documentation, but who are not themselves trained in library and information science. It provides a general overview of the role and importance of metadata in contextualizing digital documents and ensuring possibilities for future reuse ...
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Metadata Analyser: Measuring Metadata Quality
2017Scientific research is increasingly dependent on publicly available information and data sharing. So far, the best practices to ensure that data is accessible and shareable has been to deposit it in public repositories. However, these repositories often fail to implement mechanisms that measure data quality, which could lead to improving the ...
Bruno Inácio +2 more
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2015 31st IEEE International Conference on Data Engineering Workshops, 2015
We present a vision of a technology and domain agnostic service that will store metadata that describes properties of the diverse data sets in an enterprise (or across several enterprises), and spread among heterogenous stores, such as relational databases, data warehouses, NoSQL or NewSQL cloud storage platforms, etc.
Akon Dey +3 more
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We present a vision of a technology and domain agnostic service that will store metadata that describes properties of the diverse data sets in an enterprise (or across several enterprises), and spread among heterogenous stores, such as relational databases, data warehouses, NoSQL or NewSQL cloud storage platforms, etc.
Akon Dey +3 more
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, 2005 International Journal of Semantic Computing, 2012
The M3O abstracts from the existing metadata standards and formats and provides generic modeling solutions for annotations, decompositions, and provenance of metadata. Being a generic modeling framework, the M3O aims at integrating the existing metadata standards and metadata formats rather than replacing them.
Ansgar Scherp +2 more
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The M3O abstracts from the existing metadata standards and formats and provides generic modeling solutions for annotations, decompositions, and provenance of metadata. Being a generic modeling framework, the M3O aims at integrating the existing metadata standards and metadata formats rather than replacing them.
Ansgar Scherp +2 more
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IEEE Software, 2002
I occasionally come across people who describe their programming tasks as tedious, which is often the sign of a design problem. One common source of tedium is pulling data from an external source. You almost always do the same thing with the data, but because the data differs each time, it's difficult to reduce such tedious programming.
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I occasionally come across people who describe their programming tasks as tedious, which is often the sign of a design problem. One common source of tedium is pulling data from an external source. You almost always do the same thing with the data, but because the data differs each time, it's difficult to reduce such tedious programming.
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Repairing Raw Metadata for Metadata Management
Information Systems, 2023Hiba Khalid, Esteban Zimányi
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