Towards a Conceptualization of Data and Information Quality in Social Information Systems

Abstract

Data and information quality (DIQ) have been defined traditionally in an organizational context and with respect to traditional information systems (IS). Numerous frameworks have been developed to operationalize traditional DIQ accordingly. However, over the last decade, social information systems (SocIS) such as social media have emerged that enable social interaction and open collaboration of voluntary prosumers, rather than supporting specific tasks as do traditional IS in organizations. Based on a systematic literature review, the paper identifies and categorizes prevalent DIQ conceptualizations. The authors differentiate the various understandings of DIQ in light of the unique characteristics of SocIS and conclude that they do not capture DIQ in SocIS well, nor how it is defined, maintained, and improved through social interaction. The paper proposes a new conceptualization of DIQ in SocIS that can explain the interplay of existing conceptualizations and provides the foundation for future research on DIQ in SocIS.

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Notes

  1. 1.

    The combination of multiple DIQ conceptualizations should not be confused with the combination of multiple DIQ dimensions/metrics; the latter is common to most of the DIQ definitions (see Sect. 2.3 on the levels of DIQ definitions) and also occurs without a DIQ conceptualization (category “only dimensions”).

  2. 2.

    “A Wikiproject refers to a group of contributors who are dedicated to developing, maintaining, and organizing articles related to a particular topic” (Kane and Ransbotham 2012).

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Acknowledgements

The authors thank three anonymous reviewers, the guest editors of the special issue on human information behavior, as well as the discussants at the International Conference on Information Systems 2015 for their input and valuable comments on earlier drafts of this article.

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Correspondence to Dipl.-Wirt.-Inf. Roman Tilly.

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Accepted after three revisions by the editors of the special issue.

Appendices

Appendix

A1 Structured Literature Search

To develop a taxonomy of existing DIQ conceptualizations, we first conducted a structured literature search of the DIQ domain in general. We identified relevant DIQ conceptualizations and definitions we used to develop a taxonomy. Our literature review followed the best-practice approaches of the IS discipline (Webster and Watson 2002; Kitchenham and Charters 2007).

A1.1 Search Process

We identified relevant articles by searching systematically the titles, keywords, and abstracts of all articles published in the Senior Scholars’ Basket (Association for Information Systems 2011) that is, European Journal of Information Systems, Information Systems Journal, Information Systems Research, Journal of AIS, Journal of Information Technology, Journal of MIS, Journal of Strategic Information Systems, and MIS Quarterly.

We conducted a keyword-based search (Kitchenham 2004; Kitchenham and Charters 2007) using two combinations of keywords: “information AND quality” and “data AND quality.” We also searched the titles, keywords, and abstracts of all articles archived in the AIS Electronic Library (AISeL) for the keywords “information quality” and “data quality.” We collected all papers published before 20 April 2015 that matched these keywords.

We screened the results manually, removed duplicates, and excluded articles that did not cover at least one of the concepts ‘data quality’, ‘information quality’, and DIQ. We included only articles that stated explicitly or referred to a definition of data quality and/or information quality.

A1.2 Results

Our search process resulted in a set of 730 articles. After removing duplicates and all articles that did match our exclusion criteria (see above), we identified 342 potentially relevant papers. We then screened each of these articles for their respective definitions of DIQ and decided to submit 249 articles to further analysis (see Table 1).

Table 1 Results of the search process

A2 Taxonomy

A2.1 Process of Taxonomy Development after Nickerson et al. (2012)

Nickerson et al. 2012 propose an iterative method to develop taxonomies. Briefly summarized, the method proceeds as follows: (1) based on the purpose of the taxonomy, determine a meta-characteristic that informs the selection of characteristics in later stages; (2) determine objective and subjective ending conditions for the iterative cycle to stop; and (3) choose whether to proceed “empirical-to-conceptual” or “conceptual-to-empirical.” Then, in “empirical-to-conceptual”: (4e) identify objects; (5e) identify their common characteristics; and (6e) group characteristics into dimensions and create/revise the taxonomy. In “conceptual-to-empirical,” the process is: (4c) deduce characteristics and dimensions from prior knowledge, experience, or theory; (5c) examine whether objects for characteristics and dimensions; and (6c) create/revise the taxonomy. The process then continues as follows: (7) evaluate objective and subjective ending conditions and either enter into the next iteration (step 3) or terminate, if all conditions are met. Note that in this method, it is possible to alternate between “empirical-to-conceptual” and “conceptual-to-empirical” iterations.

A2.2 Resulting Taxonomy

Table 2 presents an overview of the existing DIQ conceptualizations that were identified through the process of taxonomy building including short descriptions each conceptualization, key publications or examples for this conceptualization, how it maps to the TAD framework, its main points of conflict with SocIS characteristics, and how many studies were assigned to each DIQ conceptualization.

Table 2 Taxonomy and discussion of existing DIQ conceptualizations

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Tilly, R., Posegga, O., Fischbach, K. et al. Towards a Conceptualization of Data and Information Quality in Social Information Systems. Bus Inf Syst Eng 59, 3–21 (2017). https://doi.org/10.1007/s12599-016-0459-8

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Keywords

  • Social information systems
  • Social media
  • Data quality
  • Information quality
  • Socio-technical processes