Briefly read the book Social Life of Information over the last week an one notion that stuck me was the idea of attaching meaning to data. Basically, data without meaning is not information and hence to a certain extent not useful.
What is meaning then? For most part it depends on context -- who is the subject, what conditions was the data produced in, and when that happened amongst many other things.
The contention here is that while we have gotten terribly good at the technical issues of indexing and retriving massive amounts of data at ever faster speeds, we have thus far not been as good at creating personal contexts in which the data can be interpreted at a personal level.
As a case in point, a very common example of data which can hold a wide variance of value depending on who reads it are scientific papers. Simply put, as most people thumb their way though journal articles and such, there is tremendous difficulty comprehension sometimes, much less expectation to relate to most of the concepts and ideas. In the hands of a professor of that field, little snippets of details about the paper add contextual meaning to it on top of the actual writing. Who the author(s) are, when the paper was written and other factors help a professor grapse the added level of meaning of it.
Back to the person in the street, we have to confess that the chances to pick up and read a scientific paper is extraordinarily low. But, what about common daily information that he/she has to interact with. Would added context help bring more meaning across? Would it help people better piece information together and get a better picture? Something which psychologically, humans are bad at is working with massive (or for that matter, even moderate) amounts of data and making some sense or detecting patterns in it.
Which begs the point, shouldn't we then be thinking of intelligent ways of structuring the way we work with data as well as the interfaces we rely on to help cover our cognitive blind-side?
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