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'''Information provenance''' is the accurate historical record of an information object such as a [[digital]] [[text]], an [[image]], or an [[audio file]]. Provenance begins with identification of the original form and [[authorship]] of an object or its constituent components and continues with identification of each subsequent alteration to the object. Provenance information can include not only what was changed but also who or what produced the change, when the change was made, and other attributes of the object. As reliance on [[networked information]] and [[transactional process]]es grows, the need for technical means of establishing information provenance becomes increasingly important. The goal of information provenance capabilities is to track the pedigree of a digital object from its origin through all transformations leading to the current state. |
'''Information provenance''' is the accurate historical record of an information object such as a [[digital]] [[text]], an [[image]], or an [[audio file]]. Provenance begins with identification of the original form and [[authorship]] of an object or its constituent components and continues with identification of each subsequent alteration to the object. Provenance information can include not only what was changed but also who or what produced the change, when the change was made, and other attributes of the object. As reliance on [[networked information]] and [[transactional process]]es grows, the need for technical means of establishing information provenance becomes increasingly important. The goal of information provenance capabilities is to track the pedigree of a digital object from its origin through all transformations leading to the current state. |
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| + | == Discussion == |
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| + | The provenance of [[information]] can help a [[user]] determine whether to trust it and how to interpret it. Information provenance techniques are also needed to control [[information sharing]]. Partners (e.g., allies, collaborators, or corporations engaged in a joint project) generally want to [[information sharing|share information]], but only to a limited extent. For example, there may be a constraint that [[information]] of certain types can be shared only among certain partners. Enforcing such constraints is complicated by alternate [[data format]]s and by transformations that combine [[data]] and deliver derived results. For example, the [[classification]] level of [[information]] derived from otherwise [[unclassified]] sources may prevent its public release. In addition, as diverse [[dataset]]s are combined, accurate [[information]] may be interspersed with inaccurate [[information]]. To [[verify]] the provenance of the information, [[data]] about its source and derivation (or [[aggregation]]) must be [[propagate]]d with the [[information]] itself. |
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[[Category:Data]] |
[[Category:Data]] |
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Revision as of 06:32, 4 June 2010
Overview
Information provenance is the accurate historical record of an information object such as a digital text, an image, or an audio file. Provenance begins with identification of the original form and authorship of an object or its constituent components and continues with identification of each subsequent alteration to the object. Provenance information can include not only what was changed but also who or what produced the change, when the change was made, and other attributes of the object. As reliance on networked information and transactional processes grows, the need for technical means of establishing information provenance becomes increasingly important. The goal of information provenance capabilities is to track the pedigree of a digital object from its origin through all transformations leading to the current state.
Discussion
The provenance of information can help a user determine whether to trust it and how to interpret it. Information provenance techniques are also needed to control information sharing. Partners (e.g., allies, collaborators, or corporations engaged in a joint project) generally want to share information, but only to a limited extent. For example, there may be a constraint that information of certain types can be shared only among certain partners. Enforcing such constraints is complicated by alternate data formats and by transformations that combine data and deliver derived results. For example, the classification level of information derived from otherwise unclassified sources may prevent its public release. In addition, as diverse datasets are combined, accurate information may be interspersed with inaccurate information. To verify the provenance of the information, data about its source and derivation (or aggregation) must be propagated with the information itself.