A study on analytical framework to breakdown conditions among data quality measurements

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    The point of this survey is to feature issues in information quality research and to talk about potential research chance to accomplish high information quality inside an association. The survey received deliberate writing audit technique in view of research articles distributed in diaries and gathering procedures. Here built up an audit technique in light of particular subjects, for example, ebb and flow inquire about territory in information quality, basic measurements in information quality, information quality administration model and approaches and information quality evaluation strategies. In light of the audit methodology, here select pertinent research articles, concentrate and amalgamation the data to answer an examination questions. The survey features the headway of information quality research to take after its genuine application and talk about the accessible hole for future research. Research territory, for example, association’s administration, information quality effect towards the association and database related specialized answers for information quality overwhelmed the early years of information quality research. Be that as it may, since the Web is presently occurring as the new data source, the rising of new research regions, for example, information quality evaluation for web and huge information is unavoidable. This audit additionally recognizes and talks about basic information quality measurements in association, for example, information fulfillment, consistency, exactness and convenience. Likewise think about and feature holes in information quality administration model and procedures. This survey is critical to feature and break down restriction of existing information quality research identified with the current needs in information quality, for example, unstructured information sort and enormous information.

  • Keywords

    Data quality, Data quality management model, assessment methods, database, organization.

  • References

      [1] Strong DM, Lee YW & Wang RY, “Data Quality in Context”, Communications of the ACM, Vol.40, No.5, (1997), pp.103–110.

      [2] Lee YW & Strong DM, “Knowing-Why About Data Processes and Data Quality”, Journal of Management Information Systems, Vol.20, No.3, (2003), pp.13–39.

      [3] Levitin AV & Redman TC, “Data as a resource: properties, implications, and prescriptions”, Sloan Management Review, Vol.40, (1998), pp.89–101.

      [4] Wang RY, “A product perspective on total data quality management”, Communications of the ACM, Vol.41, No.2, (1998), pp.58–65.

      [5] Liu J, Li J, Li W & Wu J, “Rethinking big data: A review on the data quality and usage issues”, ISPRS Journal of Photogrammetry and Remote Sensing, Vol.115, (2016), pp.134–142.

      [6] Sadiq S & Indulska M, “Open data: Quality over quantity”, International Journal of Information Management, Vol.37, No.3, (2017), pp.150–154.

      [7] Kitchenham B, Pearl Brereton O, Budgen D, Turner M, Bailey J & Linkman S, “Systematic literature reviews in software engineering – A systematic literature review”, Information and Software Technology, Vol.51, No.1, (2009), pp.7–15.

      [8] Wang RY, Storey VC & Firth CP, “A framework for analysis of data quality research”, IEEE Transactions on Knowledge and Data Engineering, Vol.7, No.4, (1995), pp.623–640.

      [9] Madnick SE, Wang RY, Lee YW & Zhu H, “Overview and Framework for Data and Information Quality Research”, Journal of Data and Information Quality, Vol.1, No.1, (2009), pp.1–22.

      [10] Dalip DH, Gonçalves MA, Cristo M & Calado P, “Automatic Assessment of Document Quality in Web Collaborative Digital Libraries”, Journal of Data and Information Quality, Vol.2, No.3, (2011), pp.1–30.

      [11] Rajakumari SB, “Data Quality Mining in Electronic News Paper”, Indian Journal of Science and Technology, Vol.7(S5), (2014), pp.47–50.

      [12] Chen JV, Su B & Widjaja AE, “Facebook C2C social commerce: A study of online impulse buying”, Decision Support Systems, Vol.83, (2016), pp.57–69.

      [13] Xiao Y, Lu LYY, Liu JS & Zhou Z, “Knowledge diffusion path analysis of data quality literature: A main path analysis”, Journal of Informetrics, Vol.8, No.3, (2014), pp.594–605.

      [14] Marotta A & Delgado A, “Data Quality Management in Web Warehouses using BPM”, ICIQ, (2016).

      [15] Helfert M & Ge M, “Big Data Quality-Towards an Explanation Model in a Smart City Context”, ICIQ, (2016).

      [16] Woodall AP, Borek A, Gao J, Oberhofer M & Koronios A, “An Investigation of How Data Quality is Affected by Dataset Size in the Context of Big Data Analytics”, Proceedings of the International Conference on Information Quality, (2014).

      [17] Sadiq S, Yeganeh N & Indulska M, “20 years of data quality research: themes, trends and synergies”, Proceedings of the Twenty-Second Australasian Database Conference, Vol.115, (2011), pp.153–162.

      [18] Hassany P, Panahy S, Sidi F, Affendey LS, Jabar MA, Ibrahim H & Mustapha A, “A Framework to Construct Data Quality Dimensions Relationships”, Indian Journal of Science and Technology, Vol.6, No.5, (2013), pp.4421–4431.

      [19] Wand Y & Wang RY, “Anchoring data quality dimensions in ontological foundations”, Communications of the ACM, Vol.39, No.11, (1996), pp.86–95.

      [20] Wang R & Strong D, “Beyond accuracy: What data quality means to data consumers”, Journal of management information systems, Vol.12, No.4, (1996), pp.5–33.

      [21] Bovee M, Srivastava RP & Mak B, “A conceptual framework and belief-function approach to assessing overall information quality”, International Journal of Intelligent Systems, Vol.18, No.1, (2003), pp.51–74.

      [22] Kahn BK, Strong DM & Wang RY, “Information quality benchmarks: product and service performance”, Communications of the ACM, Vol.45, No.4, (2002), pp.184–192.

      [23] Ballou DP & Pazer HL, “Modeling Data and Process Quality in Multi-Input, Multi-Output Information Systems”, Management Science, Vol.31, (1985), pp.150–163.

      [24] Jayawardene V, Sadiq S & Indulska M, “An Analysis of Data Quality Dimensions”, ITEE Technical Report No. 2013-01, Vol.1,(2013), pp.1–32.

      [25] Strong DM, Lee YW & Wang RY, “10 potholes in the road to information quality”, Computer, Vol.30, No.8, (1997), pp.38– 46.

      [26] Batini C, Cappiello C, Francalanci C & Maurino A, “Methodologies for data quality assessment and improvement”, ACM Computing Surveys, Vol.41, No.3, (2009).

      [27] Batini C & Scannapieca M, “Data Quality”, Springer Berlin Heidelberg, (2006).

      [28] Wang RY, Reddy MP & Kon HB, “Toward quality data: An attribute-based approach”, Decision Support Systems, Vol.13, No.3–4, (1995), pp. 349–372.

      [29] Gi Lee S, Lee B & Jeong H, “A Study on the Problem Analysis and Improvement Plan of the Data Quality Management System of National R&D Data”, Indian Journal of Science and Technology, Vol.8, No.23, (2015).

      [30] Surendar, A., M. Kavitha, and V. Saravanakumar. "Proactive model based testing and evaluation for component-based systems." International Journal of Engineering & Technology 8.1.1 (2018): 74-77.

      [31] Lee YW, Strong DM, Kahn BK & Wang RY, “AIMQ: a methodology for information quality assessment”, Information & Management, Vol.40, No.2, (2002), pp.133–146.

      [32] Sidi F, Shariat Panahy PH, Affendey LS, Jabar MA, Ibrahim H & Mustapha A, “Data quality: A survey of data quality dimensions”, International Conference on Information Retrieval & Knowledge Management, (2012), pp.300–304.

      [33] Ryu KS, Park JS & Park JH, “A Data Quality Management Maturity Model”, ETRI Journal, Vol.28, No.2, (2006), pp.191–204.

      [34] Wang RY, Kon HB & Madnick SE, “Data Quality Requirements Analysis and Modeling”, Ninth International Conference on Data Engineering, (1993).

      [35] Pipino LL, Lee YW & Wang RY, “Data quality assessment”, Communications of the ACM, Vol.45, No.4, (2002).




Article ID: 9276
DOI: 10.14419/ijet.v7i1.1.9276

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.