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{{Definition|Information given meaning and integrated with other contents of understanding.}} | {{Definition|Information given meaning and integrated with other contents of understanding.}} | ||
{{Quotation|What differentiates '''knowledge''' from [[Information]] is the complexity of the experiences that you need to reach it. In order for a set of information to become knowledge one has to be exposed to it in different ways and one has to elaborate a personal experience about it. [...] knowledge can be expressed as a pattern whose measure of interest for the user is above a certain threshold. That is, if some information is not interesting for us it's very difficult for it to become knowledge. Knowledge is not transferable, you have to build it yourself by experiencing the information.|[Dürsteler, 2007]}} | |||
{{Quotation|[[Knowledge]] is the "justified true belief" according to Plato. According to the Oxford English Dictionary, knowledge can be defined as (i) expertise, and skills acquired by a person through experience or education; (ii) what is known in a particular field or in total; or (iii) awareness or familiarity gained by experience of a fact or situation.|[Bertini and Lalanne, 2009]}} | |||
{{Quotation|[[Data|data]] is transformed into [[Information|information]]; information provides [[Knowledge|knowledge]]; and [[Wisdom|wisdom]] is the ability to apply knowledge|[Pritchard, 2010]}} | |||
see [[Knowledge Discovery]] for an explanation of the relationship between [[Data]], [[Information]], [[Insight]], [[Model]], [[Pattern]], [[Hypothesis]], [[Knowledge]] and [[Knowledge Crystallization]]. | |||
see also: [[Data]], [[Information]], [[Knowledge]], [[Wisdom]] | |||
== References == | == References == | ||
*[Bates, 2005] Marcia J. Bates, [http://informationr.net/ir/10-4/paper239.html Information and Knowledge: An Evolutionary Framework for Information Science. Information Research | *[Bates, 2005] Marcia J. Bates, [http://informationr.net/ir/10-4/paper239.html Information and Knowledge: An Evolutionary Framework for Information Science]. ''Information Research'', 10(4), July 2005. | ||
*[Bertini and Lalanne, 2009] Bertini, E. and Lalanne, D. 2009. [http://doi.acm.org/10.1145/1562849.1562851 Surveying the complementary role of automatic data analysis and visualization in knowledge discovery]. In Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: integrating Automated Analysis with interactive Exploration (Paris, France, July 28 - 28, 2009). VAKD '09. ACM, New York, NY, 12-20 | |||
*[Dürsteler, 2007] Juan C. Dürsteler, [http://www.infovis.net/printMag.php?num=186 | |||
*[Pritchard, 2010] Tony Pritchard, The Science of Information Visualisation: a provocation, Tony Pritchard's Blog, created at: April 3, 2010, retrieved at: April 9, 2010, http://tonypritchard.wordpress.com/2010/04/03/the-science-of-information-visualization-a-provocation/ | |||
[[Category:Glossary]] | [[Category:Glossary]] | ||
Latest revision as of 13:57, 9 April 2010
Information given meaning and integrated with other contents of understanding.
What differentiates knowledge from Information is the complexity of the experiences that you need to reach it. In order for a set of information to become knowledge one has to be exposed to it in different ways and one has to elaborate a personal experience about it. [...] knowledge can be expressed as a pattern whose measure of interest for the user is above a certain threshold. That is, if some information is not interesting for us it's very difficult for it to become knowledge. Knowledge is not transferable, you have to build it yourself by experiencing the information.
[Dürsteler, 2007]
Knowledge is the "justified true belief" according to Plato. According to the Oxford English Dictionary, knowledge can be defined as (i) expertise, and skills acquired by a person through experience or education; (ii) what is known in a particular field or in total; or (iii) awareness or familiarity gained by experience of a fact or situation.
[Bertini and Lalanne, 2009]
data is transformed into information; information provides knowledge; and wisdom is the ability to apply knowledge
[Pritchard, 2010]
see Knowledge Discovery for an explanation of the relationship between Data, Information, Insight, Model, Pattern, Hypothesis, Knowledge and Knowledge Crystallization.
see also: Data, Information, Knowledge, Wisdom
References
- [Bates, 2005] Marcia J. Bates, Information and Knowledge: An Evolutionary Framework for Information Science. Information Research, 10(4), July 2005.
- [Bertini and Lalanne, 2009] Bertini, E. and Lalanne, D. 2009. Surveying the complementary role of automatic data analysis and visualization in knowledge discovery. In Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: integrating Automated Analysis with interactive Exploration (Paris, France, July 28 - 28, 2009). VAKD '09. ACM, New York, NY, 12-20
- [Dürsteler, 2007] Juan C. Dürsteler, [http://www.infovis.net/printMag.php?num=186
- [Pritchard, 2010] Tony Pritchard, The Science of Information Visualisation: a provocation, Tony Pritchard's Blog, created at: April 3, 2010, retrieved at: April 9, 2010, http://tonypritchard.wordpress.com/2010/04/03/the-science-of-information-visualization-a-provocation/