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K2/Kleisli and GUS: Experiments in integrated access to genomic data sources

Open access
Davidson, S. B., Crabtree, J., Brunk, B. P., Schug, J., Tannen, V., Overton, G. C., Stoeckert, C. J.·2001·IBM Systems Journal

Abstract

The integrated access to heterogeneous data sources is a major challenge for the biomedical community. Several solution strategies have been explored: link-driven federation of databases, view integration, and warehousing. In this paper we report on our experiences with two systems that were developed at the University of Pennsylvania: K2, a view integration implementation, and GUS, a data warehouse. Although the view integration and the warehouse approaches each have advantages, there is no clear “winner.” Therefore, in selecting the best strategy for a particular application, users must consider the data characteristics, the performance guarantees required, and the programming resources available. Our experiences also point to some practical tips on how database updates should be published, and how XML can be used to facilitate the processing of updates in a warehousing environment.

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Metadata

Authors
Davidson, S. B., Crabtree, J., Brunk, B. P., Schug, J., Tannen, V., Overton, G. C., & Stoeckert, C. J.
Venue
IBM Systems Journal
Publisher
IBM
Published
2001
Volume
40
Issue
2
Pages
512-531
ISSN
0018-8670 (ISSN-L)
OpenAlex
W1968766436
Cited by
199
References
0
FWCI
31.36
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: K2/Kleisli and GUS: Experiments in integrated access to genomic data sources. https://app.cochat.ai/papers/10.1147/sj.402.0512
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Davidson, S. B., Crabtree, J., Brunk, B. P., Schug, J., Tannen, V., Overton, G. C., & Stoeckert, C. J. (2001). K2/Kleisli and GUS: Experiments in integrated access to genomic data sources. IBM Systems Journal. https://doi.org/10.1147/sj.402.0512

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.