Difference between revisions of "Data-centric knowledge"
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Data-centric knowledge is a mapping of concepts | Data-centric knowledge is a formalized mapping of concepts to data points. Its universal applicability is based on the representability assumption of [[Kan-Extension]]. Kan extension states that all concepts and idealized knowledge are [[representable]] through functors from a domain of complex data types to uniquely identifiable data entries in set-theoretic format. This means that [[knowledge]] of any kinds can all be stored or [[represented]] using concrete data points stored in databases. | ||
[[Category:Kan Extension]] | [[Category:Kan Extension]] | ||
[[Category:Representable]] | [[Category:Representable]] | ||
Revision as of 05:45, 18 February 2022
Data-centric knowledge is a formalized mapping of concepts to data points. Its universal applicability is based on the representability assumption of Kan-Extension. Kan extension states that all concepts and idealized knowledge are representable through functors from a domain of complex data types to uniquely identifiable data entries in set-theoretic format. This means that knowledge of any kinds can all be stored or represented using concrete data points stored in databases.