Provenance : an introduction to PROV /

The World Wide Web is now deeply intertwined with our lives, and has become a catalyst for a data deluge, making vast amounts of data available online, at a click of a button. With Web 2.0, users are no longer passive consumers, but active publishers and curators of data. Hence, from science to food...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Moreau, Luc (College teacher) (Autor), Groth, Paul (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham, Switzerland : Springer, [2013]
Colección:Synthesis lectures on the semantic web, theory and technology ; #7.
Temas:
Data integrity.
Database management.
Semantic Web.
Intégrité des données.
Bases de données > Gestion.
Web sémantique.
COMPUTERS > Database Management > General.
Data integrity
Database management
Semantic Web
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. Introduction
  • 1.1 The case for provenance
  • 1.2 A definition of provenance
  • 1.3 Provenance and the web architecture
  • 1.4 The W3C PROV standard
  • 1.5 Online extensions.
  • 2. A data journalism scenario
  • 2.1 Scenario: The employment report
  • 2.1.1 Characters
  • 2.1.2 Story creation and publication
  • 2.1.3 Crunching data
  • 2.1.4 Reusing the story
  • 2.2 Provenance use cases
  • 2.2.1 Quality assessment
  • 2.2.2 Compliance
  • 2.2.3 Cataloging
  • 2.2.4 Replay
  • 2.3 A brief introduction to expressing provenance
  • 2.4 Summary.
  • 3. The PROV ontology
  • 3.1 Overview
  • 3.2 Qualified relation patterns
  • 3.3 Data flow view
  • 3.3.1 Entity
  • 3.3.2 Derivation
  • 3.3.3 Revision
  • 3.3.4 Quotation
  • 3.3.5 Primary source
  • 3.4 Process flow view
  • 3.4.1 Activity
  • 3.4.2 Generation
  • 3.4.3 Usage
  • 3.4.4 Invalidation
  • 3.4.5 Start
  • 3.4.6 End
  • 3.4.7 Communication
  • 3.5 Responsibility view
  • 3.5.1 Agent
  • 3.5.2 Attribution
  • 3.5.3 Association
  • 3.5.4 Delegation
  • 3.6 Alternates view
  • 3.6.1 Specialization
  • 3.6.2 Alternate
  • 3.7 Bundles
  • 3.8 Miscellaneous
  • 3.8.1 Collection and membership
  • 3.8.2 Refined derivation
  • 3.8.3 Further properties
  • 3.9 Ontology structure
  • 3.10 Summary.
  • 4. Provenance recipes
  • 4.1 Modeling
  • 4.1.1 Iterative modeling
  • 4.1.2 Identify, identify, identify!
  • 4.1.3 From data flow to activities
  • 4.1.4 Plan for revisions
  • 4.1.5 Modeling update and other destructive activities
  • 4.1.6 Modeling message passing
  • 4.1.7 Modeling parameters
  • 4.1.8 Introduce the environment
  • 4.1.9 Modeling sub-activities
  • 4.2 Organizing
  • 4.2.1 Stitch provenance together
  • 4.2.2 Use content-negotiation when exposing provenance
  • 4.2.3 Bundle up and provide attribution to provenance
  • 4.2.4 Embedding provenance in HTML
  • 4.2.5 Embedding provenance in other media
  • 4.2.6 When all else fails, add provenance to PROV headers
  • 4.2.7 Embedding provenance in bundles: self-referential bundles
  • 4.2.8 When displaying provenance, adopt conventional layout
  • 4.3 Collecting
  • 4.3.1 Use structured logs to collect provenance
  • 4.3.2 Collect in a local form, expose as PROV
  • 4.4 Anti-patterns
  • 4.4.1 Activity but no derivation
  • 4.4.2 Association but no attribution
  • 4.4.3 Specify responsibility first, what a PROV:Agent is will follow
  • 4.5 Summary.
  • 5. Validation, compliance, quality, replay
  • 5.1 Validation use cases
  • 5.2 Principles of validation
  • 5.2.1 Events and their ordering
  • 5.2.2 Simultaneous events
  • 5.2.3 Nested intervals and specialization
  • 5.2.4 Use cases revisited
  • 5.3 Utilizing provenance
  • 5.3.1 Provenance-based compliance
  • 5.3.2 Provenance-based quality assessment
  • 5.3.3 Provenance-based cataloging
  • 5.3.4 Provenance-based replaying
  • 5.4 Implementation techniques for provenance analysis
  • 5.4.1 Finding ancestors
  • 5.4.2 Deep traversal
  • 5.4.3 Pattern detection for policy compliance
  • 5.4.4 Time comparison
  • 5.4.5 Trust-based filtering
  • 5.4.6 Finding external ancestor resources
  • 5.4.7 Replay technique
  • 5.5 Summary.
  • 6. Provenance management
  • 6.1 Exposing provenance
  • 6.1.1 Embedding provenance in HTML with RDFA
  • 6.1.2 Provenance services
  • 6.2 Provenance management tools
  • 6.2.1 ProvToolbox
  • 6.2.2 ProvPy
  • 6.2.3 ProvConvert and ProvTranslator
  • 6.2.4 ProvStore
  • 6.2.5 ProvValidator
  • 6.2.6 Browser PROV extractor
  • 6.2.7 ProvVis: interactive visualizations for PROV
  • 6.3 Provenance management on www.provbooK.org
  • 6.3.1 Directories
  • 6.3.2 URI schemes for entities, agents, and activities
  • 6.3.3 The PROV book ontology
  • 6.3.4 Data journalism provenance
  • 6.3.5 Exposing provenance
  • 6.4 Summary.
  • 7. Conclusion
  • 7.1 Toward provenance self certification: a checklist
  • 7.2 Applying provenance in the wild
  • 7.3 Open issues
  • 7.3.1 Provenance enabling systems
  • 7.3.2 Fundamentals of provenance
  • 7.3.3 Provenance analytics
  • 7.3.4 Securing provenance
  • 7.4 Final words
  • Bibliography
  • Authors' biographies
  • Index.

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