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". IQ frameworks also provides a tangible approach to assess and measure DQ/IQ in a robust and rigorous manner. Conceptual problems 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 the process to guarantee confidence that particular information meets some context specific quality requirements. It has been suggested, however, that higher the quality the greater will be the confidence in meeting more general, less specific contexts. Dimensions and metrics of information quality "Information quality" is a measure of the value which the information provides to the user of that information. "Quality" is often perceived as subjective and the quality of information can then vary among users and among uses of the information. Nevertheless, a high degree of quality increases its objectivity or at least the intersubjectivity. Accuracy can be seen as just one element of IQ but, depending upon how it is defined, can also be seen as encompassing many other dimensions of quality. If not, it is perceived that often there is a trade-off between accuracy and other dimensions, aspects or elements of the information determining its suitability for any given tasks. Richard Wang and Diane Strong propose 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. While information as a distinct term has various ambiguous definitions, there's one which is more general, such as "description of events". While the occurrences being described cannot be subjectively evaluated for quality, since they're very much autonomous events in space and time, their description can—since it possesses a garnishment attribute, unavoidably