Managing Biological Data using bdbms

Authors:
Mohamed Y. Eltabakh;Mourad Ouzzani;Walid G. Aref;Ahmed K. Elmagarmid;Yasin Laura-Silva;Muhammad U. Arshad;David Salt;Ivan Baxter
Affiliations:
Dept. of Computer Science, Purdue University, West Lafayette, IN, USA. meltabak@cs.purdue.edu;Cyber Center, Purdue University, West Lafayette, IN, USA. mourad@cs.purdue.edu;Dept. of Computer Science, Purdue University, West Lafayette, IN, USA. aref@cs.purdue.edu;Dept. of Computer Science, Purdue University, West Lafayette, IN, USA. ake@cs.purdue.edu;Dept. of Computer Science, Purdue University, West Lafayette, IN, USA. ylaurasi@cs.purdue.edu;Dept. of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA. marshad@ecn.purdue.edu;Dept. of Horticulture&Landscape Architecture, Purdue University, West Lafayette, IN, USA. dsalt@purdue.edu;Dept. of Horticulture&Landscape Architecture, Purdue University, West Lafayette, IN, USA. ibaxter@purdue.edu
Venue:
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Year:
2008

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Abstract

We demonstrate bdbms, an extensible database engine for biological databases. bdbms started on the observation that database technology has not kept pace with the specific requirements of biological databases and that several needed key functionalities are not supported at the engine level. While bdbms aims at supporting several of these functionalities, this demo focuses on: (1) Annotation and provenance management including storage, indexing, querying, and propagation, (2) Local dependency tracking of dependencies and derivations among data items, and (3) Update authorization to support data curation. We demonstrate how bdbms enables biologists to manipulate their databases, annotations, and derivation information in a unified database system using the Purdue Ionomics Information Management System (PiiMS) as a case study.