DartWiki: A semantic wiki for ontology-based knowledge integration in the biomedical domain

Tong Yu, Huajun Chen*, Jinhua Mi, Peiqin Gu, Ting Wu, Jeff Z. Pan

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

3 Citations (Scopus)

Abstract

Semantic Web languages and technologies can be used for the annotation, classification, and organization of knowledge assets and digital artifacts based on biomedical ontologies. In this paper, we present a semantic wiki, named DartWiki, to build ontology-based digital encyclopedia for the biomedicine domain. DartWiki provides a Web-based interface for accessing knowledge artifacts in both per-artifact and per-concept mode. In the per-artifact mode, users can access these artifacts, and annotate them in both short texts and logical statements in terms of domain ontologies. In the concept-based mode, users can navigate a graph of concepts, and review and edit the synthesized page about a selected concept, which contains meaningful information about the concept, and also its related concepts and artifacts. Smooth transitions between the two modes are achieved through semantic links. As a use case of the DartWiki, we provide an open platform for the management and maintenance of digital artifacts in Integrated Medicine. This system provides medical practitioners with relevant and trustworthy knowledge artifacts, and also means to input artifacts, to clarify their meaning, and to check and improve their quality, which encourages the inclusion and participation of users, and effectively creates an online community around knowledge sharing.

Original languageEnglish
Pages (from-to)278-288
Number of pages11
JournalCurrent Bioinformatics
Volume7
Issue number3
DOIs
Publication statusPublished - 2012

Keywords

  • Domain ontology
  • Integrated medicine
  • Knowledge management
  • Semantic web
  • Semantic wiki
  • Traditional chinese medicine

Fingerprint

Dive into the research topics of 'DartWiki: A semantic wiki for ontology-based knowledge integration in the biomedical domain'. Together they form a unique fingerprint.

Cite this