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Provenance and Annotation of Data : International Provenance and Annotation Workshop, IPAW 2006, Chicago, Il, USA, May 3-5, 2006, Revised Selected Papers / edited by Ian Foster.

SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online

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Format:
Book
Contributor:
Foster, Ian, 1959- editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 4145.
Information Systems and Applications, incl. Internet/Web, and HCI ; 4145
Language:
English
Subjects (All):
Data structures (Computer science).
Information storage and retrieval.
Application software.
Operating systems (Computers).
Computers and civilization.
Management information systems.
Computer science.
Data Structures and Information Theory.
Information Storage and Retrieval.
Information Systems Applications (incl. Internet).
Operating Systems.
Computers and Society.
Management of Computing and Information Systems.
Local Subjects:
Data Structures and Information Theory.
Information Storage and Retrieval.
Information Systems Applications (incl. Internet).
Operating Systems.
Computers and Society.
Management of Computing and Information Systems.
Physical Description:
1 online resource (XII, 292 pages).
Edition:
First edition 2006.
Contained In:
Springer eBooks
Place of Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
System Details:
text file PDF
Summary:
Provenance 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.
Contents:
Session 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.
Other Format:
Printed edition:
ISBN:
978-3-540-46303-0
9783540463030
Access Restriction:
Restricted for use by site license.

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