An effective knowledge quality framework based on knowledge resources interdependencies

Farzad Sabetzadeh, Yue Hong Eric Tsui

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)


Purpose – The purpose of this paper is to introduce a new knowledge quality assessment framework based on interdependencies between content and schema as knowledge resources to enhance the quality of the knowledge that is being generated, disseminated and stored in a collaborative environment. Design/methodology/approach – A knowledge elaboration approach is based on intervening factors of schematic clustering applied to a trial wiki bulletin board. Through this schematic intervention in the form of group creation within a wiki environment, a user-centric mechanism is created to substantiate, compose and narrate the generated contents in a self-organizing way. Findings – Through this approach, quality in content can be enhanced by means of a favourably manipulated collaboration schema adopted by the knowledge management system (KMS) users instead of applying knowledge mining tools. Research limitations/implications – With consideration to trust as a significant factor in this study, the verification and referral process may vary for KMS structures that are of larger scale or in low-trust collaborative environments. Originality/value – This study demonstrates transition to higher quality knowledge with less time spent on the original content refinement and composition by paying due consideration to the interdependencies between knowledge resource content and its schema. Validation is done via a clustered group structure in a specially designed wiki which had been used as a discussion bulletin board on directed topics over an extended period.
Original languageEnglish
Pages (from-to)360-375
Number of pages16
Issue number3
Publication statusPublished - 1 Jan 2015


  • Knowledge management
  • Knowledge quality
  • Knowledge resource
  • Wiki

ASJC Scopus subject areas

  • Computer Science Applications
  • Library and Information Sciences

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