Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Computati...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Computational Biology
Article . 1995 . Peer-reviewed
License: Mary Ann Liebert TDM
Data sources: Crossref
DBLP
Article . 1995
Data sources: DBLP
versions View all 3 versions
addClaim

A Strategy for Database Interoperation

Authors: Peter D. Karp;

A Strategy for Database Interoperation

Abstract

To realize the full potential of biological databases (DBs) requires more than the interactive, hypertext flavor of database interoperation that is now so popular in the bioinformatics community. Interoperation based on declarative queries to multiple network-accessible databases will support analyses and investigations that are orders of magnitude faster and more powerful than what can be accomplished through interactive navigation. I present a vision of the capabilities that a query-based interoperation infrastructure should provide, and identify assumptions underlying, and requirements of, this vision. I then propose an architecture for query-based interoperation that includes a number of novel components of an information infrastructure for molecular biology. These components include a knowledge base that describes relationships among the conceptualizations used in different biological databases, a module that can determine the DBs that are relevant to a particular query, a module that can translate a query and its results from one conceptualization to another, a collection of DB drivers that provide uniform physical access to different database management systems, a suite of translators that can interconvert among different database schema languages, and a database that describes the network location and access methods for biological databases. A number of the components are translators that bridge the heterogeneities that exist between biological DBs at several different levels, including the conceptual level, the data model, the query language, and data formats.

Keywords

Computer Communication Networks, Databases, Factual, Artificial Intelligence, Computer Systems, Database Management Systems, Molecular Biology, Information Systems

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    58
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
58
Average
Top 1%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!