Abstract
This article will discuss ongoing research about Information Quality (IQ). Raters evaluating various IQ dimensions (accuracy, completeness, objectivity…) of same object showed low agreement level, therefore making IQ not measurable. Increase of IQ measurability to sufficient level would present an opportunity for guidelines to replace information of low with high quality. Speculations why IQ dimensions are not measurable have been made but at the same time mechanisms that improve agreement level have been proposed by researchers for validation. Moreover context in which information is being evaluated has not been yet addressed by existing research. This article will describe and explain a study that aims to create a robust model that will validate and measure effect of three different IQ aspects. Although this article is still work in progress, current results regarding research construction and preliminary testing will be presented as well as future steps.
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References
Hilligoss, B., Rieh, S.Y.: Developing a unifying framework of credibility assessment: Construct, heuristics, and interaction in context. Inf. Process. Manage. 44(4), 1467–1484 (2008)
Yaari, E., Baruchson-Arbib, S., Bar-Ilan, J.: Information quality assessment of community-generated content - A user study of Wikipedia. J. Inf. Sci. 37(5), 487–498 (2011)
Ge, M., Helfert, M.: A review of information quality assessment. In: IET Conference Proceedings, Institution of Engineering and Technology, pp. 951–958 (2007)
Geiger, J.G.: Data quality management: the most critical initiative you can implement. In: SUGI 29, Montreal, Canada (2004)
Arazy, O., Kopak, R.: On the measurability of information quality. J. Am. Soc. Inform. Sci. Technol. 62(1), 89–99 (2011)
Rieh, S.Y., Danielson, D.R.: Credibility: a multidisciplinary framework. Annu. Rev. Inf. Sci. Technol. 41, 307–364 (2007)
Wang, R.Y., Strong, D.M.: Beyond accuracy: what data quality means to data consumers. J. Manage. Inf. Syst. 12(4), 5–33 (1996)
Flanagin, A.J., Metzger, M.J.: The role of site features, user attributes, and information verification behaviors on the perceived credibility of web-based information. New Media Soc. 9(2), 319–342 (1981)
Lee, Y.W., et al.: AIMQ: a methodology for information quality assessment. Inf. Manag. 40(2), 133–146 (2002)
Liu, Z.M.: Perceptions of credibility of scholarly information on the web. Inf. Process. Manage. 40(6), 1027–1038 (2004)
Oakleaf, M.: Using rubrics to assess information literacy: an examination of methodology and interrater reliability. J. Am. Soc. Inform. Sci. Technol. 60(5), 969–983 (2009)
Mai, J.E.: The quality and qualities of information. J. Am. Soc. Inform. Sci. Technol. 64(4), 675–688 (2013)
Eppler, M.J.: Managing Information Quality: Increasing the Value of Information in Knowledge-intensive Products and Processes, 2nd edn. Springer, Berlin (2006)
Reijers, H.A., Mendling, J.: A study into the factors that influence the understandability of business process models. IEEE Transact. Syst. Man Cybern. 41(3), 449–462 (2011)
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Fidler, M., Lavbič, D. (2015). Research About Measurability of Information Quality. In: Uden, L., Heričko, M., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2015. Lecture Notes in Business Information Processing, vol 224. Springer, Cham. https://doi.org/10.1007/978-3-319-21009-4_21
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DOI: https://doi.org/10.1007/978-3-319-21009-4_21
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