CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
Conceptual schema analysis: techniques and applications
ACM Transactions on Database Systems (TODS)
Data Integration in the Large: The Challenge of Reuse
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Enterprise information integration: successes, challenges and controversies
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Semantic-integration research in the database community
AI Magazine - Special issue on semantic integration
Improving data quality through effective use of data semantics
Data & Knowledge Engineering - Special issue: WIDM 2004
Scalable access controls for lineage
TAPP'09 First workshop on on Theory and practice of provenance
Scalable interoperability through the use of COIN lightweight ontology
ODBIS'05/06 Proceedings of the First and Second VLDB conference on Ontologies-based databases and information systems
Reduce, reuse, recycle: practical approaches to schema integration, evolution and versioning
CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
Assessing the quality of large-scale data standards: A case of XBRL GAAP Taxonomy
Decision Support Systems
Hi-index | 0.00 |
For meaningful information exchange or integration, providers and consumers need compatible semantics between source and target systems. It is widely recognized that achieving this semantic integration is very costly. Nearly all the published research concerns how system integrators can discover and exploit semantic knowledge in order to better share data among the systems they already have. This research is very important, but to make the greatest impact, we must go beyond after-the-fact semantic integration among existing systems, to actively guiding semantic choices in new ontologies and systems - e.g., what concepts should be used as descriptive vocabularies for existing data, or as definitions for newly built systems. The goal is to ease data sharing for both new and old systems, to ensure that needed data is actually collected, and to maximize over time the business value of an enterprise's information systems.