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A standard representation of the pyramid form of DIKW models, from 2007 and earlier [1] [2]. The DIKW pyramid, also known variously as the knowledge pyramid, knowledge hierarchy, information hierarchy, [1]: 163 DIKW hierarchy, wisdom hierarchy, data pyramid, and information pyramid, [citation needed] sometimes also stylized as a chain, [3]: 15 [4] refer to models of possible structural and ...
Data is a fact depicted as a figure or a statistic, while data in context—such as in a historical time frame—is information. By contrast, knowledge is interpretative and predictive. Its deductive character allows a person with knowledge to understand the implications of information, and act accordingly.
Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources.The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.
Data, information, knowledge, and wisdom are closely related concepts, but each has its role concerning the other, and each term has its meaning. According to a common view, data is collected and analyzed; data only becomes information suitable for making decisions once it has been analyzed in some fashion. [8]
Information analysis is the process of inspecting, transforming, and modeling information, by converting raw data into actionable knowledge, in support of the decision-making process. Information quality (shortened as InfoQ) is the potential of a dataset to achieve a specific (scientific or practical) goal using a given empirical analysis method.
Knowledge management (KM) is the set of procedures for producing, disseminating, utilizing, and overseeing an organization's knowledge and data.It alludes to a multidisciplinary strategy that maximizes knowledge utilization to accomplish organizational goals.
Knowledge retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items. It draws on a range of fields including epistemology (theory of knowledge), cognitive psychology, cognitive neuroscience, logic and inference, machine learning and knowledge discovery, linguistics, and information technology.