Evaluation criteria for information quality research

被引:0
|
作者
Woodall P. [1 ]
Borek A. [2 ]
Parlikad A.K. [1 ]
机构
[1] Department of Engineering, Institute for Manufacturing, University of Cambridge, 17 Charles Babbage Road, Cambridge
[2] Gartner Deutschland GmbH, Lehrer-Wirth-Straße 2, München
基金
英国工程与自然科学研究理事会;
关键词
Data quality; Data quality evaluation; DQ artefacts; DQ evaluation; Evaluation criteria; Information quality; IQ artefacts; IQ evaluation;
D O I
10.1504/IJIQ.2016.083125
中图分类号
学科分类号
摘要
Evaluation of research artefacts (such as models, frameworks and methodologies) is essential to determine their quality and demonstrate worth. However, in the information quality (IQ) research domain there is no existing standard set of criteria available for researchers to use to evaluate their IQ artefacts. This paper therefore describes our experience of selecting and synthesising a set of evaluation criteria used in three related research areas of information systems (IS), software products (SP) and conceptual models (CM), and analysing their relevance to different types of IQ research artefact. We selected and used a subset of these criteria in an actual evaluation of an IQ artefact to test whether they provide any benefit over a standard evaluation. The results show that at least a subset of the criteria from the other domains of IS, SP and CM are relevant for IQ artefact evaluations, and the resulting set of criteria, most importantly, enabled a more rigorous and systematic selection of what to evaluate. Copyright © 2016 Inderscience Enterprises Ltd.
引用
收藏
页码:124 / 148
页数:24
相关论文
共 50 条
  • [1] Research and Implementation of Information Quality Improvement
    Chen, Bing
    Wang, Beizhan
    Zheng, Chengman
    Hu, Xueqin
    FOURTH INTERNATIONAL CONFERENCE ON COOPERATION AND PROMOTION OF INFORMATION RESOURCES IN SCIENCE AND TECHNOLOGY (COINFO 2009), 2009, : 225 - +
  • [2] Information Hiding and Its Criteria for Evaluation
    Iwamura, Keiichi
    Kawamura, Masaki
    Kuribayashi, Minoru
    Iwata, Motoi
    Kang, Hyunho
    Gohshi, Seiichi
    Nishimura, Akira
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2017, E100D (01): : 2 - 12
  • [3] Citizen Science: An Information Quality Research Frontier
    Lukyanenko, Roman
    Wiggins, Andrea
    Rosser, Holly K.
    INFORMATION SYSTEMS FRONTIERS, 2020, 22 (04) : 961 - 983
  • [4] Citizen Science: An Information Quality Research Frontier
    Roman Lukyanenko
    Andrea Wiggins
    Holly K. Rosser
    Information Systems Frontiers, 2020, 22 : 961 - 983
  • [5] Data measurement in research information systems: metrics for the evaluation of data quality
    Otmane Azeroual
    Gunter Saake
    Jürgen Wastl
    Scientometrics, 2018, 115 : 1271 - 1290
  • [6] Data measurement in research information systems: metrics for the evaluation of data quality
    Azeroual, Otmane
    Saake, Gunter
    Wastl, Jurgen
    SCIENTOMETRICS, 2018, 115 (03) : 1271 - 1290
  • [7] Research in evaluation criteria of evidence combination
    Yang, Yang
    Cheng, Yongmei
    Liang, Yan
    Pan, Quan
    Wan, Wenjing
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 2618 - +
  • [8] Data and Information Quality: Research Themes and Evolving Trends
    Shankaranarayanan, G.
    Blake, Roger
    AMCIS 2015 PROCEEDINGS, 2015,
  • [9] Information quality evaluation for grid information services
    Xing, Wei
    Corcho, Oscar
    Goble, Carole
    Dikaiakos, Marios
    TOWARDS NEXT GENERATION GRIDS, 2007, : 165 - +
  • [10] Formulating Priority Coefficients for Information Quality Criteria on the Blog
    Kargar, Mohammad Javad
    Ramli, Abd R.
    Ibrahim, H.
    Azimzadeh, F.
    ADVANCES IN COMPUTER SCIENCE AND ENGINEERING, 2008, 6 : 396 - +