I was reading claims of increased precision by software X the other day. I probably have mentioned this before (and it wasn’t original, then or now) that precision seems to me to be the enemy of serendipity.
For example, when I was an undergraduate, the library would display all the recent issues of journals on long angled shelves. So it was possible to walk along looking at the new issues in a variety of areas with ease. As a political science major I could have gone directly to journals on political science. But I would have missed the Review of Metaphysics and/or the Journal of the History of Ideas, both of which are rich sources of ideas relevant to topic maps (and information systems more generally).
But precision about the information available, a departmental page that links only to electronic versions of journals relevant to the “discipline,” reduces the opportunity to perhaps recognize relevant literature outside the confines of a discipline.
True, I still browse a lot, otherwise I would not notice titles like: k-means Approach to the Karhunen-Loéve Transform (aka PCA – Principal Component Analysis). I knew that k-means was a form of clustering that could help with gathering members of collective topics together but quite honestly did not recognize Karhunen-Loéve Transform. I know it as either PCA – Principal Component Analysis, which I inserted in my blog title to help others recognize the technique.
Of course the problem is that sometimes I really want precision, perhaps I am rushed to finish a job or need to find a reference for a standard, etc. In those cases I don’t have time to wade through a lot of search results and appreciate whatever (little) precision I can wring out of a search engine.
Whether I want more precision or more serendipity varies on a day to day basis for me. How about you?