Results of DIKW poll

Thanks for your participation on the last Data Mining Research poll regarding the DIKW (Data, Information, Knowledge and Wisdom) hierarchy. 61 people answered to the poll. Here are the final results:

• The hierarchy is fine since the terms used have always the same meaning nowadays then before: 13%
  
  
• The hierarchy is fine, but the meaning or usage of terms should evolve (e.g. "information science" should be renamed "knowledge science"): 43%
  
  
• The hierarchy should evolve since the meaning or usage of these terms have changed: 44%

First of all, there won't be a second round, as it is for elections in France. Second, I am happy to see that not everybody has the same opinion on this question. It is not funny when everyone has the same opinion. As you may know from a previous post on Data Mining Research, I am in favor of the second choice. My main argument is that the meaning of these terms have changed, while, to my opinion, the DIKW hierarchy hasn't.

In favor of these arguments, I can point out the work of Zins (1). In his article, Zins studies the DIKW hierarchy and its key terms. According to him Information Science should be renamed "Knowledge Science". Zins also proposes a study of 130 definitions of "Data, Information and Knowledge" from the information science point of view (2).

This does not mean that Zins point of view is true. If you have arguments in favor of what is right according to you, feel free to post a comment. Especially people that have voted for the third choice, my question is: what do you think is a better hierarchy nowadays? You can post as anonymous if you want.

(1) Zins, C. (2006), Redefining information science: from information science to knowledge science, Journal of Documentation, 62(15):447-461.
(2) Zins, C. (2007), Conceptual approaches for defining data, information, and knowledge, Journal of the American Society for Information Science and Technology, 58(4):479-493.

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Poll on DIKW hierarchy

If you work in data mining, you are every day confronted to terms such as data, information and knowledge. As explained in a previous post on Data Mining Research, there exists a hierarchy on these terms. It is usually represented as shown in the following picture.


My question, regarding this terminology is: What do you think of the DIKW hierarchy? While some people may believe it is still up to date, others may think that it has evolved. You can answer through the following poll:

Don't hesitate to comment this post if you have a personal opinion on the subject.

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"Who are you" poll results

Thanks for participating to the poll "Who are you" recently proposed on this blog. It is helpful for me to better know the audience of Data Mining Research. Here are the results over 43 votes:

Data mining practitioners: 33%

Data mining researchers: 44%

People from other fields: 23%

It is a quite good mix of researchers and practitioners. I'm surprised (in good) of the high percentage of people from other fields than data mining. I guess these people come from a closely related field such as computer science in general or mathematics. Anyway, I will do my best so that any reader can regularly find interesting posts.

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Who are you?

Tools like Google Analytics are very useful to answer questions such as How many readers do you have each day? and Where do your readers come from? A less straightforward question, that is of interest for this post, is Who are you? Are you a practitioner, a researcher or someone coming from another field than data mining. You can answer simply by using the following poll:

It is very interesting for me to know who is reading this blog so I can adapt its content. Thanks in advance for your participation.

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Around the world

It is time again to have a look around the world. If you feel bad in the plane, I have some pills for you. Here are the destinations:

• Thanks to an anonymous blogger, you can yet have more details about data mining and terrorism.
  
• Will has a new poll about your use of Matlab toolboxes here.
  
• Dean is opening an interesting discussion on his blog about the complexity of data mining.
  

Have a nice trip!

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Give your mind

Today is the last post before Christmas on Data Mining Research. We are also close to new year and therefore open to new resolutions for 2007. Data Mining Research has started in June this year, although only actively in August. The aim of this blog is to discuss on various topics regarding data mining, both in the research and application point of view. Through posting on subjects such as applications, news, languages, softwares, research topics, books, other blogs, etc. the idea is to motivate discussion. After five months of existence, I'm really curious to know your mind about this blog. Every comment, positive or negative is welcomed and may be used to improve the quality of this blog. So feel free to give your real mind as well as ideas, remarks and suggestions. May you have just a word or on the contrary two pages of comments, just write it as an answer to this post. I thank you in advance and look forward to read your remarks. Merry Christmas!

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Data mining platform poll

To continue with the YALE post, I propose a poll concerning your favorite data mining platform. You are certainly using several different platforms for data mining. For this poll, the idea is to vote only for the one you prefer or most use. I think that it can give a good idea about tools used for data mining by both researchers and practitioners.

Use the scroll bar on the right to see all choices.

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