Information quality (IQ) is the quality of the content of information systems . It is often pragmatically defined as: “The fitness for use of the information provided.”
Although this pragmatic definition is usable for most everyday purposes, specialists often use more complex models for information quality. Most information system practitioners use the term synonymously with data quality . However, as many academics make a distinction between data and information ,  some will insist on a distinction between data quality and information quality. This distinction would be akin to the distinction between syntax and semantics where for example, the semantic value of “one” could be expressed in different syntaxes like 00001; 1.0000; 01.0; Or 1. A data difference may not necessarily represent poor information quality.
Information quality assurance is the process to guarantee confidence that particular information meets some context specific quality requirements. It has been suggested, however, that the higher the quality, the more general, the less specific contexts. 
Dimensions and metrics of information quality
“Information quality” is a measure of the value of the information provided to the user of that information. “Quality” is often perceived as the quality of information. Nevertheless, the intersubjectivity is not the same . Accuracy can be seen as just one element of IQ, but can also be seen as encompassing many other dimensions of quality.
If not, it is perceived that it is a trade-off between different dimensions, aspects or elements of the information determining its suitability for any given tasks. Wang and Strong proposes a list of dimensions or elements used in assessing Information Quality is: 
- Intrinsic IQ: accuracy , objectivity , Believability , reputation
- Contextual IQ: relevance , value-added , Timeliness , Completeness , amount of information
- Representational IQ: interpretability , format, coherence, compatibility 
- Accessibility IQ: accessibility , access security
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.  In fact, 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. 
Whereas a description of events has been made. While the occurrences are described as being able to be evaluated by a person, the description of the person who is the subject of the decision, Of the occurrences being described.
In an attempt to deal with this natural phenomenon, well-known professionals who represent the researchers’ guild. They could also be described as ‘quality traits’ of information, since they are not so easily quantified, but rather subjectively identified on an individual basis.
Context of information in organizations
Information quality dimensions are perceived to be differently important by different users.  For instance, drawing is Porter’s value chain,  employees working in primary activities of the value chain as Compared To employees working in secondary activities Perceive significant information quality criteria differentially. As such, primary areas perceive timeliness more important than secondary areas.  Further, IT and HR staff perceive security of information more important than other functional areas.  However, IT staff perceives completeness as less important than other areas. Thus, it is important for mangers to consider different user perspectives when working on improving information quality.
The general satisfaction level with quality data. Among the following criteria, security and conciseness were influenced strongest by employees’ general satisfaction levels: 
- Consistently Represented
The eight criteria above have also been mentioned in trade-off relationships in literature.  For instance, if management improves security of information, it may need to be traded-off for accessibility.
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- Authority / verifiability
Authority refers to the. 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 as much as possible, to provide the sources of information so that they can be verified
- Scope of coverage
Scope of coverage. Consideration of time periods, geography or jurisdiction and coverage of related or narrower topics.
- Composition and organization
Composition and organization has 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 of presentation of other viewpoints, its reason for providing the information and advertising.
- Adherence to moral and ethical principles; Soundness of moral character
- The state of being whole, whole, or undiminished
- Of wide scope; Covering or involving much; Inclusive: a comprehensive study.
- Comprehending mentally; Having an extensive mental grasp.
- Insurance. Covering or providing broad protection against loss.
Validity of some information that has information about the carries
As much as ‘uniqueness’ of a given piece of information is intuitive in meaning, it implies not only the originating point of the information but also the perception which it conjures. The essence of any piece of information we process consists of 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.
- Reproducibility (used when referring to informative information)
Means that documented methods are capable of being used on the same data to achieve a consistent result.
- IQ International-the International Association for Information and Data Quality 
- IQ International is a not-for-profit, vendor-neutral, professional association formed in 2004, dedicated to building the information and data quality profession.
Information quality conferences
A number of major conferences relevant to information quality are held annually:
- Data Governance and Information Quality Conference 
- Commercial conferences held each year in the USA
- Data Quality Asia Pacific 
- Commercial conference held in Sydney or Melbourne, Australia
- Enterprise Data and Business Intelligence Conference Europe 
- Commercial conferences held annually in London, England.
- Information and Data Quality Conference 
- Not for profit conference run annually by IQ International [the International Association for Information and Data Quality ]
- International Conference on Information Quality 
- Academic Conference launched through MITIQ held annually at a University
- Master Data Management & Data Governance Conferences 
- Six major conferences were held annually by the MDM Institute in London, San Francisco, Sydney, Toronto, Madrid, Frankfurt, Shanghai and New York City.
- Data quality
- Accuracy and precision
- Jump up^ For a scientific and philosophical unraveling of these concepts see Churchman, CW (1971)The design of inquiry systems, New York: Basic Books.
- Jump up^ SeeIvanov, K.(1972)”Quality-control of information: On the concept of accuracy of information in data banks and in management information systems”. The University of Stockholm and The Royal Institute of Technology. Doctoral dissertation. Further details are found inIvanov, 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 , pp. 287-301. Gothenburg: Gothenburg University, Dept. Of Informatics (ISSN 1101-7422).
- Jump up^ Wang, R .; Strong, D. (1996). “Beyond Accuracy: What Data Quality Means to Data Consumers”. Journal of Management Information Systems. 12 (4): 5-34.
- Jump up^ Miller, Holmes (Spring 1996). “THE MULTIPLE DIMENSIONS OF INFORMATION QUALITY” . Information Systems Management . 13 (2): 79-82. Doi : 10.1080 / 10580539608906992 . Retrieved 16 September2010 .
- Jump up^ English, Larry P. (2009) “Information Quality Applied”, Wiley Publishing, Indianapolis. ISBN 978-0-470-13447-4
- Jump up^ Laranjeiro, Nuno, Seyma Nur Soydemir, and Jorge Bernardino. 2015. “IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2015). Zhangjiajie, China: IEEE Computer Society. Http://dx.doi.org/10.1109/PRDC.2015.41 PDF
- ^ Jump up to:a b c d Dominique, Fehrenbacher, Dennis; Markus, Helfert, (2012-01-01). “Contextual Factors Influencing Perceived Importance and Trade-offs of Information Quality” . Communications of the Association for Information Systems . 30 (1). ISSN 1529-3181 .
- Jump up^ Porter, Michael E. (1985). Competitive Advantage: Creating and Sustaining Superior Performance . New York .: Simon and Schuster.
- Jump up^ Fehrenbacher, Dennis D. (2016-04-02). “Perceptions of information quality dimensions from the perspective of commodity theory” . Behavior & Information Technology . 35 (4): 254-267. ISSN 0144-929X . Doi :10.1080 / 0144929X.2015.1128974 .
- Jump up^ “IQ International – the International Association for Information and Data Quality” . IQ International website . Retrieved 2016-08-05 .
- Jump up^ Data Governance and Information Quality Conference
- Jump up^ Data Quality Asia Pacific
- Jump up^ Data Governance Conference Europe
- Jump up^ Information and Data Quality Conference
- Jump up^ “IQ International Conferences” . IQ International . Retrieved 2016-06-21.
- Jump up^ http://www.iciq2013.org/
- Jump up^ MDM SUMMIT Conference