The Key Importance of Research
In 1968, John Ziman published Public Knowledge: Essay Concerning the Social Dimension of Science (Cambridge University Press) in which he argued that science is public knowledge and that it must be as widely available as possible: “Scientific knowledge … facts and theories must survive a period of critical study and testing by other competent and disinterested individuals, and must have been found so persuasive that they are almost universally accepted. The objective of science is not just to acquire information nor to utter non-contradictory notions; its goal is a consensus of rational opinion over the widest possible field.” However, it wasn’t until the 1990s that the field of knowledge management really took off. “As is often the case in applied fields, it appears that the practices related to the phenomenon of knowledge management and knowledge creation have accelerated faster than the scholarly work to explain them,” notes Laird D. McLean in a 2010 article. Perhaps now, however, the wait is over. The advent of cloud computing, cheap storage, and the development of new data mining and semantic searching has changed all of this.
Just a day before the KNODE/Wiley announcement was made, Elsevier launched a new version of SciVal that provides dynamic real-time analytics and insights. “The research landscape is facing increasing globalization and competition, and there is growing recognition and evidence for the role that scholarly research plays in driving sustainable economic development. All academic, government and industrial research facilities are experiencing greater pressure to optimize their resources to excel in unique ways in an increasingly crowded market place. The current international research economy is so vast and complex, with more than 7 million researchers worldwide, that an evidence base is increasingly required to supplement insights drawn from personal knowledge and peer review.”
“Imagine, though, a vast, collective ‘hive mind’ that consumed, processed and disseminated all scientific knowledge instantaneously and ubiquitously, incorporating not only published works, but also raw data, ancillary analysis, and digital signatures of collaborators, resources and other critical elements,” Steinberg suggests. “Like the proverbial 100th monkey phenomenon, once the hive mind understood something, we’d all understand it. In 2012 Internet terms, the hive mind would combine the best of human intelligence (insight, opinion and crowd wisdom) and machine intelligence (big data, machine learning and semantic data mining) in a massive, automated, self-organizing, dynamic, machine- and crowd-sourced wiki of all scientific knowledge organized into topics and relationships, rigorously vetted and reviewed. It would be readable by machine for querying and analytics, and knowledge would be pushed to interested researchers, physicians, journalists, students and consumers when and where they needed it.” We can expect to hear a lot more about these products as these and more products enter this eager marketplace.
