ACM Computing Surveys (CSUR)
Quality-driven information filtering using the WIQA policy framework
Web Semantics: Science, Services and Agents on the World Wide Web
Discovering and Maintaining Links on the Web of Data
ISWC '09 Proceedings of the 8th International Semantic Web Conference
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
Linked Data
Declarative data fusion – syntax, semantics, and implementation
ADBIS'05 Proceedings of the 9th East European conference on Advances in Databases and Information Systems
A framework for storing and providing aggregated governmental linked open data
EGOVIS'12/EDEM'12 Proceedings of the 2012 Joint international conference on Electronic Government and the Information Systems Perspective and Electronic Democracy, and Proceedings of the 2012 Joint international conference on Advancing Democracy, Government and Governance
On the diversity and availability of temporal information in linked open data
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Managing the life-cycle of linked data with the LOD2 stack
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part II
Assessing linkset quality for complementing third-party datasets
Proceedings of the Joint EDBT/ICDT 2013 Workshops
LOP: capturing and linking open provenance on LOD cycle
Proceedings of the Fifth Workshop on Semantic Web Information Management
Introduction to linked data and its lifecycle on the web
RW'13 Proceedings of the 9th international conference on Reasoning Web: semantic technologies for intelligent data access
Environmental Modelling & Software
Test-driven evaluation of linked data quality
Proceedings of the 23rd international conference on World wide web
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The Web of Linked Data grows rapidly and already contains data originating from hundreds of data sources. The quality of data from those sources is very diverse, as values may be out of date, incomplete or incorrect. Moreover, data sources may provide conflicting values for a single real-world object. In order for Linked Data applications to consume data from this global data space in an integrated fashion, a number of challenges have to be overcome. One of these challenges is to rate and to integrate data based on their quality. However, quality is a very subjective matter, and finding a canonic judgement that is suitable for each and every task is not feasible. To simplify the task of consuming high-quality data, we present Sieve, a framework for flexibly expressing quality assessment methods as well as fusion methods. Sieve is integrated into the Linked Data Integration Framework (LDIF), which handles Data Access, Schema Mapping and Identity Resolution, all crucial preliminaries for quality assessment and fusion. We demonstrate Sieve in a data integration scenario importing data from the English and Portuguese versions of DBpedia, and discuss how we increase completeness, conciseness and consistency through the use of our framework.