Information Overload: Data vs Knowledge vs Information
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Will the flow of networked information into and through organizations overwhelm them? Why?
Distinguish between the traditional ideas of "data", "information", and "knowledge", explain how the internet is making these distinguishes increasingly unhelpful.
With the assistance of the following readings:
-Blair, A. (2010) Information Overload, Then and Now. The Chronicle of Higher Education Review. November 28.Retrieved November 15, 2010 from http://chronicle.com/article/Information-Overload-Then-and/125479/?sid=cr&utm_source=cr&utm_medium=en
-Bellinger, G., Castro, D., & Mills, A. (2004) Data, Information, Knowledge, and Wisdom. The Way of Systems. November 15, 2010 from http://www.systems-thinking.org/dikw/dikw.htm
-Green, P. (2010 ) Social Media Is Challenging Notions of the Data, Information, Knowledge, Wisdom (DIKW) Hierarchy. CMS Wire. August 16. Retrieved November 25, 2010 from http://www.cmswire.com/cms/enterprise-20/social-media-is-challenging-notions-of-the-data-information-knowledge-wisdom-dikw-hierarchy--008320.php
-Marks, O. (2010) Information Clutter Busting & Organization. ZDNet: Collaboration 2.0. August 1. Retrieved November 25, 2010 from http://www.zdnet.com/blog/collaboration/information-clutter-busting-organization/1532
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Solution Summary
This solution discusses the differences between 'data', 'information', and knowledge; and how the advent of the Internet has made it increasingly difficult to distinguish between the three.
Solution Preview
Take the data string: 0,1,2,0,0,1,2,0,3. This is raw data and as such, apart from the fact that we accept it as data, it is largely meaningless.
Now take the same data string: 0,1,2,0,0,1,2,0,3. Let's say that these nine data points represent the average number of student absences occurring during each of the months that a traditional school is in session for an entire school district. Assuming that school starts in September, we can see that November, March and May are months with the highest average number of absences; while September, December, January and April are the months with the lowest average number of absences. Now the previously meaningless string of numbers ('data' from the previous paragraph) suddenly becomes useful 'information'.
Based on the data (at the first level) and resulting information (at the second level), we can then ask questions about the data/information we have collected so that we can develop knowledge which can be applied to real life situations. We can make some assumptions about the trend, such as the fact that absences may be low in September because the school session is new and students are trying to maintain a decent attendance record. The data/information shows however that this effort falls off over the next two months, however. December and January are also high ...
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