Integration of biological sources
- 1 September 2004
- journal article
- Published by Association for Computing Machinery (ACM) in ACM SIGMOD Record
- Vol. 33 (3), 51-60
- https://doi.org/10.1145/1031570.1031583
Abstract
This paper surveys the area of biological and genomic sources integration, which has recently become a major focus of the data integration research field. The challenges that an integration system for biological sources must face are due to several factors such as the variety and amount of data available, the representational heterogeneity of the data in the different sources, and the autonomy and differing capabilities of the sources. This survey describes the main integration approaches that have been adopted. They include warehouse integration, mediator-based integration, and navigational integration. Then we look at the four major existing integration systems that have been developed for the biological domain: SRS, BioKleisli, TAMBIS, and DiscoveryLink. After analyzing these systems and mentioning a few others, we identify the pros and cons of the current approaches and systems and discuss what an integration system for biologists ought to be.Keywords
This publication has 12 references indexed in Scilit:
- The Molecular Biology Database Collection: 2003 updateNucleic Acids Research, 2003
- Report on the EDBT'02 panel on scientific data integrationACM SIGMOD Record, 2002
- Querying multiple bioinformatics information sourcesACM SIGMOD Record, 2002
- Knowledge-based integration of neuroscience data sourcesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Data integrationPublished by Association for Computing Machinery (ACM) ,2002
- DiscoveryLink: A system for integrated access to life sciences data sourcesIBM Systems Journal, 2001
- Query processing in the TAMBIS bioinformatics source integration systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999
- Database techniques for the World-Wide WebACM SIGMOD Record, 1998
- Challenges in Integrating Biological Data SourcesJournal of Computational Biology, 1995
- Federated database systems for managing distributed, heterogeneous, and autonomous databasesACM Computing Surveys, 1990