Data------->Information------->Knowledge
(Stenmark D., 2002)
(Stenmark D., 2002)
Data lies at the root level. When we add some context to data, we get information. And when we make some decision using our experience on the basis of that information, we get knowledge. I would like to explain this in terms of following example:
Statistical Analysis
In any type of survey or research, sample collection is commonly used practice, where a sample of people are asked about there opinion or answer about one or more questions. The figures collected in this process can be called as Data. Now we prepare charts by creating frequency distribution. This frequency distribution results in some type of charts, which will convey us the Information. The conclusions made from this information using experience results into Knowledge.
To illustrate the interchangeable use of the Data, Information, and Knowledge I would like to give following example.
Information Systems
The family tree of Information Systems is shown below. Now the systems at all the levels are information systems. And we know that a simple definition of Information Systems is a system which converts some input (usually termed as data) to output (usually termed as information) by applying some conversion process. At each level the, the input taken by Information System will be called as data, but that data will not be of grass root level (which does not have any meaning without a context). E.g. The KMS takes the information generated by the TPS as the input to make further more usable to make decisions to management. The MIS takes the information generated by the KMS as in the input, and so on. As we move up towards the top of the triangle, the systems will take input which will be moving from data to information then at systems at the bottom of the triangle. As well as, the output generated by the system will be moving from information to knowledge as we move up in the triangle.
(Topography of Information Systems,
Adapted from Britannica Encyclopedia Website)
Statistical Analysis
In any type of survey or research, sample collection is commonly used practice, where a sample of people are asked about there opinion or answer about one or more questions. The figures collected in this process can be called as Data. Now we prepare charts by creating frequency distribution. This frequency distribution results in some type of charts, which will convey us the Information. The conclusions made from this information using experience results into Knowledge.
To illustrate the interchangeable use of the Data, Information, and Knowledge I would like to give following example.
Information Systems
The family tree of Information Systems is shown below. Now the systems at all the levels are information systems. And we know that a simple definition of Information Systems is a system which converts some input (usually termed as data) to output (usually termed as information) by applying some conversion process. At each level the, the input taken by Information System will be called as data, but that data will not be of grass root level (which does not have any meaning without a context). E.g. The KMS takes the information generated by the TPS as the input to make further more usable to make decisions to management. The MIS takes the information generated by the KMS as in the input, and so on. As we move up towards the top of the triangle, the systems will take input which will be moving from data to information then at systems at the bottom of the triangle. As well as, the output generated by the system will be moving from information to knowledge as we move up in the triangle.
(Topography of Information Systems,
Adapted from Britannica Encyclopedia Website)
Cyclic Relationship
Data, Information, and Knowledge also have cyclic relationship between them. As mentioned above they are also used interchangeably. Following figure illustrates the cyclic relationship between them.
(Adapted from Liew A., 2007)
They are also used interchangeably. But I would like to state one rule which can help in understanding the relationship in much simpler way.
When Data, Information, and Knowledge occurs simultaneously in one place, there will be definitely difference between them. But when they appear individually then they can be understood in place of each other.
Retrieved March 1 2008 from http://www.britannica.com/eb/art-55237/Structure-of-organizational-information-systems-Information-systems-consist-of-three?articleTypeId=1
Stenmark D. (2002), "Information vs. Knowledge:The Role of intranets in Knowledge Management", 35th Hawaii International Conference on System Sciences - 2002
Leiw W. (2007), "Understanding Data, Information, Knowledge and Their Inter-Relationships", Journal of Knowledge Management Practice, Volume 8, No. 2, June 2007
Nonaka I. (1995), ‘The Knowledge-Creating Company’
Data, Information, and Knowledge also have cyclic relationship between them. As mentioned above they are also used interchangeably. Following figure illustrates the cyclic relationship between them.
(Adapted from Liew A., 2007)
The forward cycle (Date->Information->Knowledge) has been explained before. Let me talk something about the backward cycle. After the creation of the Knowledge, this knowledge can be transferred to others via some type of Communication, which Professor Nonaka calls as Socialisation in his book The Knowledge Creating Company (Nonaka, I, 1995). This transferred knowledge visa Socialisation becomes information for the recipient. This information which is being transferred, if at all can be converted to some codified format, and can be stored in some form of repository, then this information will become data (Liew A., 2007).
According to me, I think the knowledge created can also be directly transfered to Data (bypassing the information step). This is possible if the person possessing the knowledge can directly convert it into some type of stored form (may be written or digital). This will enable the organisations to preserve the knowledge possessed by the people to be available to others even if the person possessing it is not present.
According to me, I think the knowledge created can also be directly transfered to Data (bypassing the information step). This is possible if the person possessing the knowledge can directly convert it into some type of stored form (may be written or digital). This will enable the organisations to preserve the knowledge possessed by the people to be available to others even if the person possessing it is not present.
When Data, Information, and Knowledge occurs simultaneously in one place, there will be definitely difference between them. But when they appear individually then they can be understood in place of each other.
References
Retrieved March 1 2008 from http://www.britannica.com/eb/art-55237/Structure-of-organizational-information-systems-Information-systems-consist-of-three?articleTypeId=1
Stenmark D. (2002), "Information vs. Knowledge:The Role of intranets in Knowledge Management", 35th Hawaii International Conference on System Sciences - 2002
Leiw W. (2007), "Understanding Data, Information, Knowledge and Their Inter-Relationships", Journal of Knowledge Management Practice, Volume 8, No. 2, June 2007
Nonaka I. (1995), ‘The Knowledge-Creating Company’
3 comments:
I am at the stance too that Data, Information and Knowledge have a hierarchical structure between them. People have been associating data with information and also information with knowledge but thank God there has’nt been associating data with knowledge.
I like your example of the statistical analysis, it gives me more insight on the diffrence between them.
When some context is added to data we get information. Is this “Context” data also?
I do not quite agree with the hierachical relationship between data, information and knowledge. Rather i would say people 'express' their knowledge using information and/or data. On the other side new Knowledge comes from adding judgement to explicit data and information that one has read.Maybe your diagram should start from knowledge and end with knowledge. I addition i dont really understand your last comment in this post, you saying tat when these terms are palaced together they can be better understood than when they are used individually?
I still will assert on that data, information, and knowledge have a hierarchical structure. If you carefully see the example of Information Systems in an organisation, the system at the base level will be Transaction Processing System, which will certainly take data as the input. E.g. Sales Figures, Purchase Figures, etc. Now this is not knowledge at all. The output generated by them will be information(but still at a primitive level) and not knowledge. At the top of the triangle are Expert Systems, which produces knowledge which will help high level managers in making the strategic decisions. So at the bottom of the triangle we start with data, and at the top of the triangle we get knowledge.
As far as my last statement in the blog is concerned, I think you have misunderstood it. I said that when data, information, and knowledge appear differently, they can be used interchangeably in meaning (i.e. you can say that this is not data but information), but when they are used in one place altogether, they will have difference between them.
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