Information quality

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Information quality (IQ) is a contextual property of or a perspective to the content within information systems. There exist two complementary yet partially conflicting definitions of high-quality: firstly, information is considered high quality if it is fit for its intended purpose [1] ; secondly, it is deemed high quality if it conforms to specified requirements [2] .

Contents

The primary distinction between these definitions is that Juran's perspective focuses on the suitability of information for its intended purpose, which can be measured by the success of its application even without direct access to or exact knowledge of the data. For example, a black-box AI with access to English Wikipedia can work well for users' purposes but using Estonian Wikipedia fails for the same purposes. Given that the AI remains the same, it can be concluded that English version data would be of higher quality in comparison to Estonian version, even without exact comparison of data contents and their properties in each version. In contrast, Crosby emphasizes adherence to predefined specifications, assuming specific criteria rather than measuring the success of its use; for instance, information in Wikipedia could be proven to be good based on criteria such as existing peer validation and academic references, even if the AI results are poor. This approach falls into problems when data is not completely accessible or all quality properties cannot be known and measured leading to false impression of quality due to lacking and misleading metrics.

Numerous IQ frameworks and methodologies provide tangible approach to assess and measure DQ/IQ in a robust and rigorous manner. [3]

Conceptual problems

Although the foundational definitions are usable for most everyday purposes, specialists often use more complex models for information quality. It has been suggested, however, that higher the quality the greater will be the confidence in meeting more general, less specific contexts. [4]

Dimensions and metrics of information quality

"Information quality" is a measure of its fitness for use or conformance to requirements. In this way, "quality" is considered contextual and it can then vary across users and uses of the information. The exact degree of quality is often described with dimensions such as accuracy, timeliness, completeness, and similar scales. Although a huge amount of academic research has been directed to these dimensions, there does not exist consensus on their definitions or practical usefulness [5] .

Historically, Richard Wang and Diane Strong proposed a list of dimensions or elements used in assessing Information Quality is: [6]

Other authors propose similar but different lists of dimensions for analysis, and emphasize measurement and reporting as information quality metrics. Larry English prefers the term "characteristics" to dimensions. [8] However, a considerable amount of information quality research involves investigating and describing various categories of desirable attributes (or dimensions) of data. Research has recently shown the huge diversity of terms and classification structures used. [9]

Quality metrics

Source: [3]

Authority refers to the expertise or recognized official status of a source. Consider the reputation of the author and publisher. When working with legal or government information, consider whether the source is the official provider of the information. Verifiability refers to the ability of a reader to verify the validity of the information irrespective of how authoritative the source is. To verify the facts is part of the duty of care of the journalistic deontology, as well as, where possible, to provide the sources of information so that they can be verified

Scope of coverage refers to the extent to which a source explores a topic. Consider time periods, geography or jurisdiction and coverage of related or narrower topics.

Composition and organization has to do with the ability of the information source to present its particular message in a coherent, logically sequential manner.

Objectivity is the bias or opinion expressed when a writer interprets or analyze facts. Consider the use of persuasive language, the source's presentation of other viewpoints, its reason for providing the information and advertising.

  1. Adherence to moral and ethical principles; soundness of moral character
  2. The state of being whole, entire, or undiminished
  1. Of large scope; covering or involving much; inclusive: a comprehensive study.
  2. Comprehending mentally; having an extensive mental grasp.
  3. Insurance. covering or providing broad protection against loss.

Validity of some information has to do with the degree of obvious truthfulness which the information carries

As much as 'uniqueness' of a given piece of information is intuitive in meaning, it also significantly implies not only the originating point of the information but also the manner in which it is presented and thus the perception which it conjures. The essence of any piece of information we process consists to a large extent of those two elements.

Timeliness refers to information that is current at the time of publication. Consider publication, creation and revision dates. Beware of Web site scripting that automatically reflects the current day's date on a page.

Means that documented methods are capable of being used on the same data set to achieve a consistent result.

Professional associations

IQ International—the International Association for Information and Data Quality [10]
IQ International is a not-for-profit, vendor neutral, professional association formed in 2004, dedicated to building the information and data quality profession.
CDOIQ Society [11]
Chief Data Officers and Information Quality Society is a global professional society supporting data leaders with networking, meetings, best practices, experience, certification, and training.

Information quality conferences

A number of major conferences relevant to information quality are held annually:

Annual MIT Chief Data Officer & Information Quality (CDOIQ) Symposium [12]
Annual conferences held at the Massachusetts Institute of Technology, Cambridge, MA, USA
Data Governance and Information Quality Conference [13]
Commercial conferences held each year in the USA
Data Quality Asia Pacific [14]
Commercial conference held annually in Sydney or Melbourne, Australia
Enterprise Data and Business Intelligence Conference Europe [15]
Commercial conferences held annually in London, England.
Information and Data Quality Conference [16]
Not for profit conference run annually by IQ International (the International Association for Information and Data Quality) in the USA [17]
International Conference on Information Quality [18]
Academic Conference launched through MITIQ held annually at a University
Master Data Management & Data Governance Conferences [19]
Six major conferences are run annually by the MDM Institute in venues such as London, San Francisco, Sydney, Toronto, Madrid, Frankfurt, Shanghai and New York City.

See also

References

  1. ↑ Juran J (1988) Juran on Planning for Quality, The Free Press, New York
  2. ↑ Crosby P (1979) Quality Is Free, McGraw-Hill, New York
  3. 1 2 Fadahunsi, Kayode Philip; Akinlua, James Tosin; O'Connor, Siobhan; Wark, Petra A; Gallagher, Joseph; Carroll, Christopher; Majeed, Azeem; O'Donoghue, John (March 2019). "Protocol for a systematic review and qualitative synthesis of information quality frameworks in eHealth". BMJ Open. 9 (3) e024722. doi: 10.1136/bmjopen-2018-024722 . ISSN   2044-6055. PMC   6429947 . PMID   30842114.
  4. ↑ See Ivanov, K. (1972) "Quality-control of information: On the concept of accuracy of information in data banks and in management information systems" Archived 2009-09-01 at the Wayback Machine . The University of Stockholm and The Royal Institute of Technology. Doctoral dissertation. Further details are found in Ivanov, K. (1995). A subsystem in the design of informatics: Recalling an archetypal engineer. In B. Dahlbom (Ed.), The infological equation: Essays in honor of Börje Langefors Archived 2009-07-27 at the Wayback Machine , (pp. 287–301). Gothenburg: Gothenburg University, Dept. of Informatics (ISSN 1101-7422).
  5. ↑ Ehrlinger L, Wöß W (2022) "A Survey of Data Quality Measurement and Monitoring Tools," Frontiers in Big Data, Volume 5, DOI: 10.3389/fdata.2022.850611
  6. ↑ Wang, R.; Strong, D. (1996). "Beyond Accuracy: What Data Quality Means to Data Consumers". Journal of Management Information Systems. 12 (4): 5–34. doi:10.1080/07421222.1996.11518099. S2CID   205581875.
  7. ↑ Miller, Holmes (Spring 1996). "The Multiple Dimensions of Information Quality". Information Systems Management. 13 (2): 79–82. doi:10.1080/10580539608906992.
  8. ↑ English, Larry P. (2009) "Information Quality Applied", Wiley Publishing, Indianapolis. ISBN   978-0-470-13447-4
  9. ↑ Laranjeiro, Nuno, Seyma Nur Soydemir, and Jorge Bernardino. 2015. "A Survey on Data Quality: Classifying Poor Data." In The 21st IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2015). Zhangjiajie, China: IEEE Computer Society. https://dx.doi.org/10.1109/PRDC.2015.41 PDF
  10. ↑ "IQ International - the International Association for Information and Data Quality". IQ International website. Retrieved 2016-08-05.
  11. ↑ "CDOIQ Society". CDOIQ Society website. Retrieved 2026-02-02.
  12. ↑ Annual MIT Chief Data Officer & Information Quality Symposium
  13. ↑ Data Governance and Information Quality Conference
  14. ↑ Data Quality Asia Pacific
  15. ↑ Data Governance Conference Europe
  16. ↑ Information and Data Quality Conference [ permanent dead link ]
  17. ↑ "IQ International Conferences". IQ International. Retrieved 2016-06-21.
  18. ↑ "ICIQ.GLOBAL - Central hub of the MIT International Conference on Information Quality".
  19. ↑ MDM SUMMIT Conference

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