Anchoring data quality dimensions in ontological foundations
Communications of the ACM
Communications of the ACM
Communications of the ACM - Supporting community and building social capital
AIMQ: a methodology for information quality assessment
Information and Management
Assessing data quality with control matrices
Communications of the ACM - Information cities
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
A survey of data provenance in e-science
ACM SIGMOD Record
Provenance management in curated databases
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Beyond accuracy: what data quality means to data consumers
Journal of Management Information Systems
A survey of trust and reputation systems for online service provision
Decision Support Systems
Measuring Data Believability: A Provenance Approach
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
Addressing the provenance challenge using ZOOM
Concurrency and Computation: Practice & Experience - The First Provenance Challenge
Querying and re-using workflows with VsTrails
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
An Approach to Evaluate Data Trustworthiness Based on Data Provenance
SDM '08 Proceedings of the 5th VLDB workshop on Secure Data Management
Trident: Scientific Workflow Workbench for Oceanography
SERVICES '08 Proceedings of the 2008 IEEE Congress on Services - Part I
Database Systems: The Complete Book
Database Systems: The Complete Book
Overview and Framework for Data and Information Quality Research
Journal of Data and Information Quality (JDIQ)
A framework for semantic annotation of geospatial data for agriculture
International Journal of Metadata, Semantics and Ontologies
Provenance in Databases: Why, How, and Where
Foundations and Trends in Databases
A proof markup language for Semantic Web services
Information Systems
Explaining answers from the Semantic Web: the Inference Web approach
Web Semantics: Science, Services and Agents on the World Wide Web
Quality-driven query answering for integrated information systems
Quality-driven query answering for integrated information systems
Understanding the semantics of data provenance to support active conceptual modeling
Active conceptual modeling of learning
The Effects and Interactions of Data Quality and Problem Complexity on Classification
Journal of Data and Information Quality (JDIQ)
The Open Provenance Model core specification (v1.1)
Future Generation Computer Systems
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
Incorporating the timeliness quality dimension in internet query systems
WISE'05 Proceedings of the 2005 international conference on Web Information Systems Engineering
A Novel Framework for Monitoring and Analyzing Quality of Data in Simulation Workflows
ESCIENCE '11 Proceedings of the 2011 IEEE Seventh International Conference on eScience
Automatic generation of workflow provenance
IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
Provenance analysis: Towards quality provenance
E-SCIENCE '12 Proceedings of the 2012 IEEE 8th International Conference on E-Science (e-Science)
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Data quality is growing in relevance as a research topic. Quality assessment has been progressively incorporated in many business environments, and in software engineering practices. eScience environments, however, because of the multiplicity and heterogeneity of data sources and scientific experts involved in a given problem, complicate data quality assessment. This paper deals with the evaluation of the quality of data managed by eScience applications. Our approach is based on data provenance, i.e. the history of the origins and transformations applied to a given data product. Our contributions include a the specification of a framework to track data provenance and use it to derive quality information, b a model for data provenance based on the Open Provenance Model, and c a methodology to evaluate the quality of data based on its provenance. Our proposal is validated experimentally by a prototype that takes advantage of the Taverna workflow system.