Difference between revisions of "Data-centric knowledge"
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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. | 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 [[Representable Functor|represented]] using concrete data points stored in databases. | ||
[[Category:Kan Extension]] | [[Category:Kan Extension]] | ||
[[Category:Representable]] | [[Category:Representable]] | ||
Revision as of 05:55, 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.