Anchoring data quality dimensions in ontological foundations
Communications of the ACM
Communications of the ACM - Supporting community and building social capital
Data Quality for the Information Age
Data Quality for the Information Age
AIMQ: a methodology for information quality assessment
Information and Management
Data Quality: The Accuracy Dimension
Data Quality: The Accuracy Dimension
Quality-driven Integration of Heterogenous Information Systems
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Evaluating and Selecting Web Sources as External Information Resources of a Data Warehouse
WISE '02 Proceedings of the 3rd International Conference on Web Information Systems Engineering
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Completeness of integrated information sources
Information Systems - Special issue: Data quality in cooperative information systems
Schema and ontology matching with COMA++
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Beyond accuracy: what data quality means to data consumers
Journal of Management Information Systems
Ontology Matching
ACM Computing Surveys (CSUR)
A Semantic-Based Ontology Matching Process for PDMS
Globe '09 Proceedings of the 2nd International Conference on Data Management in Grid and Peer-to-Peer Systems
Do you know your IQ?: a research agenda for information quality in systems
ACM SIGMETRICS Performance Evaluation Review
Quality-driven query answering for integrated information systems
Quality-driven query answering for integrated information systems
Automatically incorporating new sources in keyword search-based data integration
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Communications of the ACM
Matching ontologies in open networked systems: techniques and applications
Journal on Data Semantics V
Feedback-based data set recommendation for building linked data applications
Proceedings of the 8th International Conference on Semantic Systems
What should i link to? identifying relevant sources and classes for data linking
JIST'11 Proceedings of the 2011 joint international conference on The Semantic Web
Identifying candidate datasets for data interlinking
ICWE'13 Proceedings of the 13th international conference on Web Engineering
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In the last decade, applications that make use of data sources available on the Web have experienced a huge growth. One of the main problems regarding that consists in finding the most relevant data sources for a given application. In a general way, a data source is considered relevant when it contributes for answering queries submitted to the application. However, it may happen that a specific data source contributes for answering an application query but the answer provided by the data source does not really meet the user requirements. This may occur because the data source has generic data and the user wants more specific data, for example. On the other hand, some data sources may have data of poor quality, i.e., the data may be outdated, incomplete or incorrect. In such cases, it is not enough just to find data sources that can answer to the application queries. It is also important to check if the available data also meet the user needs. In this paper, we discuss such problem and we propose an approach, based on Information Quality (IQ), to help the evaluation of the relevance of a Web data source for domain-specific applications. We also present an example illustrating how our proposal can be used to enhance this evaluation.