段玉聪
[转载]Revisiting Data-Information-Knowledge-Wisdom
2021-7-10 14:43
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Keynote Speech: Revisiting Data-Information-Knowledge-Wisdom Hierarchy from a Logic Perspective



Prof. Mykola Nikitchenko

(Keynote Speaker)

 

Taras Shevchenko National University of Kyiv, Ukraine

 

 

 

 

 

 

 

 

 


Brief Bio: Mykola Nikitchenko is the Chairman of the Department of Theory and Technology of Programming at the Faculty of Computer Science and Cybernetics of Taras Shevchenko National University of Kyiv (Ukraine). His main scientific interests are: foundations of Logic and Computer Science, formal methods of software development, abstract computability, predicate and program logics. He was a visiting researcher at the International Institute for Software Technology of the United Nations University, Macao (1996); Guest Professor at the Technical University of Denmark (1997-1998), Paul Sabatier University of Toulouse, France (2011), Johannes Kepler University of Linz, Austria (2012), University of Bialystok, Poland (2017); a lecturer at the World Congress and School on Universal Logic in Vichy, France (2018). He is the (co)author of 10 handbooks and monographs. He is the current Chairman of the Ukrainian Logic Society.

 

Title of Speech: Revisiting Data-Information-Knowledge-Wisdom Hierarchy from a Logic Perspective

Abstract: Among various approaches to explication of Data-Information-Knowledge-Wisdom Hierarchy (DIKW) we advocate a logic-oriented approach. It stems from analysis of the notion of wisdom which often is understood as the ability to think and act in a profound way. But thinking and acting are notions of logic. This poses a question of explication of all notions of the DIKW hierarchy on the basis of logic. We try to give such explications in integrity of three levels of consideration: methodological (philosophical), conceptual (scientific), and formal (mathematical). Categories of the philosophical level are projected to scientific and then to mathematical levels. At these levels notions are considered in integrity of their intensional and extensional aspects. We start with the notion of intensionalized data, then specify information as interpreted intensionalized data, and describe knowledge as a logic over such data. At last, wisdom is treated as an ability to choose and utilize a logic necessary to solve a formulated task. The proposed intensionalized explication of DIKW notions can be considered as some generalization of traditional extensional explication of these notions.


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