Getting Better Information Quality By Assessing And Improving Information Quality Management

Information quality has already become a decisive factor in information dependent business. Much has been said about the growing importance of data and information quality, and many researching lines over the last decade have looked at specific data and information quality issues from different standpoints. However data and information quality goes beyond the definition of data quality dimensions, there is still lack of an integrative framework, which can guide organizations in the assessment and improvement of data and information quality in a coordinated and global way. In this paper a framework to fill this gap is proposed. This framework is based on the Information Management Process (IMP) concept and it consists of two main components: an Information Quality Management Model structured in Maturity Levels (CALDEA) and an Assessment and Improvement Methodology (EVAMECAL). The methodology allows the assessment of an IMP in terms of maturity levels given by CALDEA, which can also be used as guidance for improvements. In the paper, a tool for automating the assessment and improvement is also briefly described.

[1]  Michael Gertz,et al.  Report on the Dagstuhl Seminar , 2004, SGMD.

[2]  José M. Tribolet,et al.  Business Process Modeling Towards Data Quality: A Organizational Engineering Approach , 2004, ICEIS.

[3]  Thomas Gilb,et al.  Software Inspection , 1994 .

[4]  Hongjiang Xu Would Organization Size Matter For Data Quality , 2003, ICIQ.

[5]  Richard Y. Wang,et al.  IP-MAP: Representing the Manufacture of an Information Product , 2000, IQ.

[6]  Holger Hinrichs,et al.  CLIQ – Intelligent Data Quality Management , 2000 .

[7]  BUSINESS PROCESS MODELING TOWARDS DATA QUALITY ASSURANCE , 2004 .

[8]  Bacmground Bootstrap Bootstrap: Europe's assessment method , 1993, IEEE Software.

[9]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[10]  W. Edwards Deming,et al.  Out of the Crisis , 1982 .

[11]  Mikhaila Burgess,et al.  A Flexible Quality Framework for Use within Information Retrieval , 2003, ICIQ.

[12]  Richard Y. Wang,et al.  Data quality assessment , 2002, CACM.

[13]  Won Kim,et al.  Towards Quantifying Data Quality Costs , 2003, J. Object Technol..

[14]  Richard Y. Wang,et al.  Quality information and knowledge , 1998 .

[15]  Mario Piattini,et al.  Metrics for databases: a way to assure the quality , 2002, Information and Database Quality.

[16]  Richard Y. Wang,et al.  Data Quality , 2000, Advances in Database Systems.

[17]  Udo Grimmer,et al.  A Methodological Approach to Data Quality Management Supported by Data Mining , 2001, IQ.

[18]  Zoubida Kedad,et al.  A quality-based framework for physical data warehouse design , 2000, DMDW.

[19]  Egon Berghout,et al.  The Goal/Question/Metric method: a practical guide for quality improvement of software development , 1999 .

[20]  Thomas C. Redman,et al.  Data Quality: The Field Guide , 2001 .

[21]  Holger Hinrichs,et al.  An ISO 9001: 2000 Compliant Quality Management System for Data Integration in Data Warehouse Systems , 2001, DMDW.

[22]  Alfonso Fuggetta,et al.  Software process: a roadmap , 2000, ICSE '00.

[23]  Martin J. Eppler Managing Information Quality , 2003 .

[24]  Martin J. Eppler,et al.  Conceptualizing Information Quality: A Review of Information Quality Frameworks from the Last Ten Years , 2000, IQ.

[25]  Gerhard Getto Risk Management Supporting Quality Management of Software Acquisition Projects , 2000 .

[26]  Diane M. Strong,et al.  AIMQ: a methodology for information quality assessment , 2002, Inf. Manag..

[27]  Watts S. Humphrey,et al.  Managing the software process , 1989, The SEI series in software engineering.

[28]  David Loshin Enterprise knowledge management: the data quality approach , 2000 .

[29]  Jack E. Olson,et al.  Data Quality: The Accuracy Dimension , 2003 .

[30]  John A. Hoxmeier Dimensions of Database Quality , 2005, Encyclopedia of Information Science and Technology.

[31]  Diane M. Strong,et al.  Information quality benchmarks: product and service performance , 2002, CACM.

[32]  S. B. Kiselev,et al.  The capability maturity model: guidelines for improving the software process , 1995 .

[33]  Total Quality data Management (TQdM) - Methodology for Information Quality Improvement , 2002, Information and Database Quality.

[34]  Diane M. Strong,et al.  Data quality in context , 1997, CACM.

[35]  Giri Kumar Tayi,et al.  Enhancing data quality in data warehouse environments , 1999, CACM.

[36]  M. Marré,et al.  A Software Engineering View of Data Quality , 2022 .

[37]  Veda C. Storey,et al.  A Framework for Analysis of Data Quality Research , 1995, IEEE Trans. Knowl. Data Eng..

[38]  Joseph Moses Juran Juran on planning for quality , 1988 .

[39]  Stuart E. Madnick,et al.  Data quality requirements analysis and modeling , 2011, Proceedings of IEEE 9th International Conference on Data Engineering.

[40]  François Coallier,et al.  How ISO 9001 fits into the software world , 1994, IEEE Software.

[41]  Matthias Jarke,et al.  Dwq : Esprit Long Term Research Project, No 22469 Data Warehouse Quality: a Review of the Dwq Project , 2022 .

[42]  Thomas Redman,et al.  Data quality for the information age , 1996 .

[43]  Richard Y. Wang,et al.  Modeling Information Manufacturing Systems to Determine Information Product Quality Management Scien , 1998 .

[44]  Michael E. Fagan Design and Code Inspections to Reduce Errors in Program Development , 1976, IBM Syst. J..

[45]  Larry P. English Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing Profits , 1999 .

[46]  TR,et al.  Information technology — Software process assessment — Part 2 : A reference model for processes and process capability , 1998 .

[47]  Denis C. Meredith Managing with Metrics: Theory into Practice , 2000 .