There was an interesting article in Science recently: Strategic Reading, Ontologies, and the Future of Scientific Publishing by Allen H. Renear and Carole L. Palmer, two professors of library science. It reviews some of the literature on scholarly communication in the digital age, but for my taste is a bit speculative in its predictions for the future.
They point out that reading habits have changed in the last 20 years as digital information has grown and surpassed print to a large extent. They suggest that scientists’ aim is to move rapidly through the literature to assess and exploit content with as little actual reading as possible.
They also state that as scientists search and browse, they are making queries and selecting information in much tighter iterations. This process of dodging around, clicking forward, back and sideways in search of the right answer is compared to channel-surfing on the TV. The article cites David Nicholas, another information behaviour researcher:
In the past, information seeking was seen to be the first step to creating knowledge. Now it is a continuous process.
Other research suggests that scientists now “read” more papers, but devote a shorter time to each paper. Renear and Palmer see this as fitting in with the “channel flicking” phenomenon.
They then briefly review the history of ontologies and mention some text-mining initiatives, including my favourite Textpresso, before exploring how ontologies can support scientific publishing (and reading) as part of the semantic web.
They predict that in ten years’ time:
Scientists will still read narrative prose, even as text mining and automated processing become common; however, these reading practices will become increasingly strategic, supported by enhanced literature and ontology-aware tools. As part of the publishing workflow, scientific terminology will be indexed routinely against rich ontologies. More importantly, formalized assertions, perhaps maintained in specialized “structured abstracts”, will provide indexing and browsing tools with computational access to causal and ontological relationships.