Data Quality for the Information Age
Data Quality for the Information Age
User-Driven Ontology Evolution Management
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Quality-driven Integration of Heterogenous Information Systems
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Ontology Evolution: Not the Same as Schema Evolution
Knowledge and Information Systems
Lineage retrieval for scientific data processing: a survey
ACM Computing Surveys (CSUR)
Provenance management in curated databases
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Analyzing the Evolution of Life Science Ontologies and Mappings
DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
Instance-based matching of large life science ontologies
DILS'07 Proceedings of the 4th international conference on Data integration in the life sciences
Ontology analysis on complexity and evolution based on conceptual model
DILS'06 Proceedings of the Third international conference on Data Integration in the Life Sciences
On matching large life science ontologies in parallel
DILS'10 Proceedings of the 7th international conference on Data integration in the life sciences
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Ontology-based annotations associate objects, such as genes and proteins, with well-defined ontology concepts to semantically and uniformly describe object properties. Such annotation mappings are utilized in different applications and analysis studies whose results strongly depend on the quality of the used annotations. To study the quality of annotations we propose a generic evaluation approach considering the annotation generation methods (provenance) as well as the evolution of ontologies, object sources, and annotations. Thus, it facilitates the identification of reliable annotations, e.g., for use in analysis applications. We evaluate our approach for functional protein annotations in Ensembl and Swiss-Prot using the Gene Ontology.