A user-centric classification of tools for biological resource discovery and integration on the web

Rida Bazzi, Jeffrey M. Kiefer, Zoé Lacroix

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The need to use resource discovery and composition tools to assist in the development of scientific workflows is well established. While systems have been developed to guide scientists in the design and implementation of their protocols into executable workflows, these systems differ significantly in the way they support the various steps of resource discovery. This paper proposes a classification of resource exploration and discovery tools according to five main categories: content, graphical interface, maintenance, optimization, and query. The paper overviews six resource discovery approaches and evaluates them according to the proposed classification. An example of how the metrics can be used in the selection of an appropriate tool for given requirements is presented.

Original languageEnglish (US)
Title of host publicationResource Discovery - Third International Workshop, RED 2010, Revised Selected Papers
Pages71-87
Number of pages17
DOIs
StatePublished - Jan 27 2012
Event3rd International Workshop on Resource Discovery, RED 2010 - Paris, France
Duration: Nov 5 2010Nov 5 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6799 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Workshop on Resource Discovery, RED 2010
CountryFrance
CityParis
Period11/5/1011/5/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'A user-centric classification of tools for biological resource discovery and integration on the web'. Together they form a unique fingerprint.

  • Cite this

    Bazzi, R., Kiefer, J. M., & Lacroix, Z. (2012). A user-centric classification of tools for biological resource discovery and integration on the web. In Resource Discovery - Third International Workshop, RED 2010, Revised Selected Papers (pp. 71-87). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6799 LNCS). https://doi.org/10.1007/978-3-642-27392-6_6