Anthony Liew considers present definitions of data, information, and knowledge to be anomalous as they are defined not as separate entities but in terms of each other. Data is defined in terms of information, information is defined in terms of either or both data and knowledge, and knowledge is defined in terms of data. This complicates the relationship between them, and especially between data and knowledge, making it difficult to determine what one is without considering what the others are. Yet, the very fact that they are continuously defined in terms of each other indicates the depth of the relationship that exists.
To put matters simply, data is the foundation of knowledge. Without data there cannot be knowledge, only false beliefs that are founded on erroneous information or arise out of faulty thought processes. Knowledge, on the other hand, is factual belief, belief founded on concrete information or data. In this way, knowledge cannot exist without data, yet data can exist without knowledge, and still give rise to knowledge at a later stage. Though knowledge is dependent on data, data and knowledge are not mutually dependent on each other.
Yet, knowledge can only be gained from data using sound reasoning and substantial evidence. There is a process to gaining knowledge. To gain knowledge from a dataset, one must undertake an amount of research and consideration, otherwise one is using a faulty method and gaining only a false belief, not knowledge. This process of justification is not without its flaws, as illustrated by the Gettier Problem, but it is essential nonetheless to the production of knowledge, and the Gettier Problem is an issue for another time.
What, exactly, knowledge is and what exactly data is and the nature of the relationship that exists between them is an area that one could spend a lifetime of study on and still not be satisfied with a true answer to. It is a question best left to philosophers and epistemologists, people who can devote the amount of time and energy to studying it that is appropriate for such a complex area. However, this said, it is important that the process of data becoming knowledge is one that is considered by academics and other researchers, i.e. by people who are actively engaging in the process by one means or another, inside or outside of academia. Why? Because by considering the process and relationship, an academic can gain a deeper understanding of what it is they do, though they still may find the relationship complex and murky.
To put things succinctly before finishing, knowledge comes from data, and this lies at the heart of the relationship between the two. Knowledge is, effectively, what we are left with when the data has been analysed, and data is the foundation for knowledge, gives rise to it when it is analysed and considered properly. Though their existence is not mutually dependent in that data can exist without knowledge arising from it, they do co-exist nonetheless. And this co-existence, one being the foundation of the other, is the nature of the relationship that exists between them.
Liew, Anthony. ‘Understanding Data, Information, Knowledge and Their Inter-Relationship. Journal of Knowledge Management Practice, vol. 8, no. 2, June 2007. Available at The Leadership Alliance Inc (www.tlainc.com). Web. Accessed 16 February 2017.