Data management is growing in complexity as largescale applications take advantage of the loosely coupled resources brought together by grid middleware and by abundant storage capacity. Metadata describing the data products used in and generated by these applications is essential to disambiguate the data and enable reuse. Data provenance, one kind of metadata, pertains to the derivation history of a data product starting from its original sources. In this pape
International audienceIn the context of astronomy projects, provenance information is important to e...
There is underlying need to support data provenance in a service-based computing environment such as...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
Data management is growing in complexity as largescale applications take advantage of the loosely co...
Data management is growing in complexity as large-scale applications take advantage of the loosely c...
In many application areas like e-science and data-warehousing detailed information about the origin ...
eScience allows scientific research to be carried out in highly distributed environments. The comple...
Large-scale, dynamic and open environments such as the Grid and Web Services build upon existing com...
The ease with which one can copy and transform data on the Web, has made it increasingly difficult t...
E-science applications use fine grained data provenance to maintain the reproducibility of scientifi...
Semantically rich metadata is foreseen to be pervasive in tomorrow’s cyber world. People are more wi...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
Provenance metadata in e-Science captures the derivation history of data products generated from sci...
Provenance information in eScience is metadata that\u27s critical to effectively manage the exponent...
The World Wide Web evolves into a Web of Data, a huge, globally distributed dataspace that contains ...
International audienceIn the context of astronomy projects, provenance information is important to e...
There is underlying need to support data provenance in a service-based computing environment such as...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
Data management is growing in complexity as largescale applications take advantage of the loosely co...
Data management is growing in complexity as large-scale applications take advantage of the loosely c...
In many application areas like e-science and data-warehousing detailed information about the origin ...
eScience allows scientific research to be carried out in highly distributed environments. The comple...
Large-scale, dynamic and open environments such as the Grid and Web Services build upon existing com...
The ease with which one can copy and transform data on the Web, has made it increasingly difficult t...
E-science applications use fine grained data provenance to maintain the reproducibility of scientifi...
Semantically rich metadata is foreseen to be pervasive in tomorrow’s cyber world. People are more wi...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
Provenance metadata in e-Science captures the derivation history of data products generated from sci...
Provenance information in eScience is metadata that\u27s critical to effectively manage the exponent...
The World Wide Web evolves into a Web of Data, a huge, globally distributed dataspace that contains ...
International audienceIn the context of astronomy projects, provenance information is important to e...
There is underlying need to support data provenance in a service-based computing environment such as...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
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