The annual NFAIS conference is a relatively unknown gem of an event for those of us interested in the future of the information business in the business, professional, and academic markets. (Full disclosure: I was on the planning committee for this year’s event.) NFAIS, which actually dates back to the Eisenhower Administration, is still a gathering place for vendors, information scientists, and librarians from major university and government libraries from around the world. This year’s conference provided solid evidence that the information industry is at an inflection point in being able to unlock new answers from content. While this may sound like a slogan, it’s revolutionary and real. The most dramatic examples come from Big Data, applying computational techniques to large sets of content to find relationships and patterns between entities, people, and events. Google is well-known for using such techniques to continuously improve the relevance of its search, but now these computational approaches are being incorporated into scientific, business, and professional information services. At NFAIS, for example, Thomson Reuters showed how it has applied such techniques to improving search in WestlawNext, its research platform for lawyers, and in Eikon, its platform for financial professionals (One of the key people behind these breakthroughs is actually a computational biologist.) Another presenting company, Narrative Science, showed how its software can automatically write news stories from quantitative data, such as baseball box scores and company earnings reports.
This revolution is powered by a variety of tools and techniques, such as data mining, text mining, and visualization, to derive richer metadata – and doing it across larger more diverse content sets. These advances in turn drive new uses, as illustrated by some other presenters at NFAIS. Elsevier’s ClinicalKey, for example, unifies Elsevier’s medical content (i.e., books, journals, practice guidelines, patient education, and drug information) under a single taxonomy that relates previously-unrelated elements of content, thereby enabling users to discover relevant information. Another example is McGraw-Hill Construction, which has applied enhanced tagging to its database of construction reports, traditionally used to help contractors and other players identify potential projects. With its enhanced tagging, McGraw-Hill has been able to launch new analytical products that use the existing content for new purposes, such as analyzing market trends, identifying the most active developers, and understanding the market shares of construction component manufacturers.
The fact that these advances increasingly fuse structured data and unstructured content distinguishes the current revolution from previous advances, which tended to focus on improving one type of content or the other, but rarely both. Furthermore, these advances offer vendors external benefits, such as improved information discovery and other user experience improvements, as well as internal benefits, such as better intelligence about how customers actually work and which product enhancements are most worthwhile.
As in many technology revolutions, this one is happening because of the combination of off-the-shelf tools as well as the mainstreaming of knowledge about the techniques for unlocking new value from content. This revolution is becoming the new normal.
