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003 DE-He213
005 20160624102014.0
007 cr nn 008mamaa
008 100301s2006 gw | s |||| 0|eng d
020 _a9783540463030
_9978-3-540-46303-0
024 7 _a10.1007/11890850
_2doi
050 4 _aQA75.5-76.95
072 7 _aUNH
_2bicssc
072 7 _aUND
_2bicssc
072 7 _aCOM030000
_2bisacsh
082 0 4 _a025.04
_223
245 1 0 _aProvenance and Annotation of Data
_h[electronic resource] :
_bInternational Provenance and Annotation Workshop, IPAW 2006, Chicago, IL, USA, May 3-5, 2006, Revised Selected Papers /
_cedited by Luc Moreau, Ian Foster.
260 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2006.
300 _aXII, 292 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v4145
505 0 _aSession 1: Keynotes -- Automatic Generation of Workflow Provenance -- Managing Rapidly-Evolving Scientific Workflows -- Session 2: Applications -- Virtual Logbooks and Collaboration in Science and Software Development -- Applying Provenance in Distributed Organ Transplant Management -- Provenance Implementation in a Scientific Simulation Environment -- Towards Low Overhead Provenance Tracking in Near Real-Time Stream Filtering -- Enabling Provenance on Large Scale e-Science Applications -- Session 4: Semantics 1 -- Harvesting RDF Triples -- Mapping Physical Formats to Logical Models to Extract Data and Metadata: The Defuddle Parsing Engine -- Annotation and Provenance Tracking in Semantic Web Photo Libraries -- Metadata Catalogs with Semantic Representations -- Combining Provenance with Trust in Social Networks for Semantic Web Content Filtering -- Session 5: Workflow -- Recording Actor State in Scientific Workflows -- Provenance Collection Support in the Kepler Scientific Workflow System -- A Model for User-Oriented Data Provenance in Pipelined Scientific Workflows -- Applying the Virtual Data Provenance Model -- Session 6: Models of Provenance, Annotations and Processes -- A Provenance Model for Manually Curated Data -- Issues in Automatic Provenance Collection -- Electronically Querying for the Provenance of Entities -- AstroDAS: Sharing Assertions Across Astronomy Catalogues Through Distributed Annotation -- Session 8: Systems -- Security Issues in a SOA-Based Provenance System -- Implementing a Secure Annotation Service -- Performance Evaluation of the Karma Provenance Framework for Scientific Workflows -- Exploring Provenance in a Distributed Job Execution System -- gLite Job Provenance -- Session 9: Semantics 2 -- An Identity Crisis in the Life Sciences -- CombeChem: A Case Study in Provenance and Annotation Using the Semantic Web -- Principles of High Quality Documentation for Provenance: A Philosophical Discussion.
520 _aProvenance is a well understood concept in the study of ?ne art, where it refers to the documented history of an art object. Given that documented history, the objectattains anauthority that allows scholarsto understandand appreciateits importance and context relative to other works. In the absence of such history, art objects may be treated with some skepticism by those who study and view them. Over the last few years, a number of teams have been applying this concept of provenance to data and information generated within computer systems. If the provenance of data produced by computer systems can be determined as it can for some works of art, then users will be able to understand (for example) how documents were assembled, how simulation results were determined, and how ?nancial analyses were carried out. A key driver for this research has been e-Science. Reproducibility of results and documentation of method have always been important concerns in science, and today scientists of many ?elds (such as bioinformatics, medical research, chemistry, and physics) see provenanceas a mechanism that can help repeat s- enti?cexperiments,verifyresults,andreproducedataproducts.Likewise,pro- nance o?ers opportunities for the business world, since it allows for the analysis of processes that led to results, for instance to check they are well-behaved or satisfy constraints; hence, provenance o?ers the means to check compliance of processes,on the basis of their actual execution. Indeed, increasing regulation of many industries (for example, ?nancial services) means that provenance reco- ing is becoming a legal requirement.
650 0 _aComputer science.
650 0 _aOperating systems (Computers).
650 0 _aInformation storage and retrieval systems.
650 0 _aInformation systems.
650 0 _aMultimedia systems.
650 0 _aInformation Systems.
650 1 4 _aComputer Science.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aInformation Systems Applications (incl.Internet).
650 2 4 _aOperating Systems.
650 2 4 _aComputers and Society.
650 2 4 _aManagement of Computing and Information Systems.
650 2 4 _aMultimedia Information Systems.
700 1 _aMoreau, Luc.
_eeditor.
700 1 _aFoster, Ian.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540463023
786 _dSpringer
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v4145
856 4 0 _uhttp://dx.doi.org/10.1007/11890850
942 _2EBK5755
_cEBK
999 _c35049
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