When it comes to defining knowledge, it really is easy to have a hard time, because there are different ways of understanding it.

There is a natural confusion between data, information and knowledge.

Data is
1) a factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation;
2) an information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful; and
3) an information in numerical form that can be digitally transmitted or processed.

Information is
1) knowledge obtained from investigation, study, or instruction;
2) intelligence, news;
3) a) facts, data; b) the attribute inherent in and communicated by one of two or more alternative sequences or arrangements of something (as nucleotides in DNA or binary digits in a computer program) that produce specific effects; c) (1): a signal or character (as in a communication system or computer) representing data (2): something (as a message, experimental data, or a picture) which justifies change in a construct (as a plan or theory) that represents physical or mental experience or another construct; d) a quantitative measure of the content of information; specifically : a numerical quantity that measures the uncertainty in the outcome of an experiment to be performed.

Knowledge is
1) the fact or condition of knowing something with familiarity gained through experience or association;
2) a) acquaintance with or understanding of a science, art, or technique; b) (1): the fact or condition of being aware of something (2): the range of one’s information or understanding; c) the circumstance or condition of apprehending truth or fact through reasoning: cognition; d) the fact or condition of having information or of being learned;
3) the sum of what is known : the body of truth, information, and principles acquired by humankind.

(Definitions from Merriam Webster)

In organisations, we hardly refer to knowledge when we talk of knowledge management. We refer to information management and in many cases we refer to data management.
This is due to the fact that there is a basic dominant assumption about what is knowledge.

When it comes to defining knowledge, one can distinguishes three dialectics: Explicit vs Tacit, Ontological vs Contextual and Private vs Public. The first one is based on the physical status of knowledge, the second one on its epistemological status and the third one on its economical status.

In a corporation it is very likely that the ‘Explicit – Ontological – Private’ understanding prevails. That is the reason why there are many processes (explicitation), data (ontology) and egoist ‘knowledge is Power’ behaviours.
Social computing is based on a radically different ground i.e. ‘tacit, contextual and public’; and Stowe Boyd one of its prominent spokesperson.
In an organisation, existing implementations show that social computing is altered in explicitable, contextual and collective to be compatible and successful.

What does that imply? Simply that social computing enriches the organisation by complementing the dominant perspective, by helping it move away from the data conception. It helps organisations have a more comprehensive approach of knowledge management. Information and knowledge are gaining ground on data and documents. It helps organisation make the cultural shift on IT: it’s not about storage, it is about access.

We all know that. The difficulty is not to store information because there are loads of techniques, tools and money for this and for ages. The difficulty is to access information because the later has contributed over the years to information overload, if not pollution. At this stage we need some serious focus on finding the ways to improve access to relevant information. Search engines are a solution but not the only one, especially in multilingual environments. Folksonomy and Tagging help people appropriating information. Social Bookmarking is a basic group feature for benefiting from like-minded people search and selection efforts. Filters such as RSS feeds, reputation and notation tools help gain a qualitative perception of content without burning time going thru (even not reading) it.