By Shamkant B. Navathe, Upen Patil (auth.), YoonJoon Lee, Jianzhong Li, Kyu-Young Whang, Doheon Lee (eds.)
This publication constitutes the refereed court cases of the ninth foreign convention on Database structures for complicated functions, DASFAA 2004, held in Jeju Island, Korea in March 2004.
The 60 revised complete papers and 18 revised brief papers awarded including 2 invited articles have been rigorously reviewed and seleted from 272 submissions. The papers are equipped in topical sections on entry tools, question processing in XML, defense and integrity, question processing in temporal and spatial databases, semi-structured databases, wisdom discovery in temporal and spatial databases, XML and multimedia and information discovery on the internet, question processing and optimization, class and clustering, internet seek, cellular databases, parallel and allotted databases, and multimedia databases.
Read Online or Download Database Systems for Advanced Applications: 9th International Conference, DASFAA 2004, Jeju Island, Korea, March 17-19, 2003. Proceedings, PDF
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Additional resources for Database Systems for Advanced Applications: 9th International Conference, DASFAA 2004, Jeju Island, Korea, March 17-19, 2003. Proceedings,
Characteristic 5: Most users of biological data do not require write access to the database; read-only access is adequate. Write access is limited to privileged users called curators. For example, the database created as part of the mitomap project has on average more than 15,000 users per month on the Internet. There are fewer than twenty non-curator-generated submissions to mitomap every month. Thus, the number of users requiring write access is small. Users generate a wide variety of readaccess patterns into the database, but these patterns are not the same as those seen in traditional relational databases.
Definitions of such data must thus be able to represent a complex substructure of data as well as relationships and to ensure that no information is lost during biological data modeling. The structure of biological data often provides an additional context for interpretation of the information. Biological information systems must be able to represent any level of complexity in any data schema, relationship, or schema substructure—not just hierarchical, binary, or table data. As an example, mitomap is a database documenting the human mitochondrial genome.
As an example, mitomap is a database documenting the human mitochondrial genome. This single genome is a small, circular piece of dna encompassing information about 16,569 nucleotide bases; 52 gene loci encoding messenger rna, ribosomal rna, and transfer rna; 1000 known population variants; over 60 known disease associations; and a limited set of knowledge on the complex molecular interactions of the biochemical energy producing pathway of oxidative phosphorylation. As might be expected, its management has encountered a large number of problems; we have been unable to use the traditional rdbms or odbms approaches to capture all aspects of the data (Navathe and Kogelnik, 1999).