Efficient Exploration of Biological Data Using Semantic Web Compatible Databases

Nazar Zaki, Chandana Tennakoon

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

1 Citation (Scopus)

Abstract

There are over 1600 publicly available biological databases, and this number is growing at a steady rate. These databases are not in a uniform format, however, web-based technologies can be employed to integrate them. One of the key steps in enabling semantic web techniques is to convert these databases into a uniform format, for example, that of the Resource Description Framework (RDF). There are already several biological databases available in RDF format. However, some of the major databases are only found in custom formats. In this paper, we review the methods that are available to explore biological databases in RDF format. We also review current projects that facilitate the conversion of biological data into RDF format. We will identify the strengths and weaknesses of the current exploratory methods and suggest improvements that will enable both novice and expert users to search biological databases more effectively.

Original languageEnglish
Title of host publicationProceedings - 2016 3rd International Conference on Soft Computing and Machine Intelligence, ISCMI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-72
Number of pages6
ISBN (Electronic)9781509036967
DOIs
Publication statusPublished - Oct 2 2017
Event3rd International Conference on Soft Computing and Machine Intelligence, ISCMI 2016 - Dubai, United Arab Emirates
Duration: Nov 23 2016Nov 25 2016

Publication series

NameProceedings - 2016 3rd International Conference on Soft Computing and Machine Intelligence, ISCMI 2016

Other

Other3rd International Conference on Soft Computing and Machine Intelligence, ISCMI 2016
Country/TerritoryUnited Arab Emirates
CityDubai
Period11/23/1611/25/16

Keywords

  • Biological Databases
  • Faceted Browsing
  • RDF
  • SPARQL
  • Semantic Web

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Control and Optimization

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