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The Department of Education released a draft report about big data and education today. It's called "Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics," a title that's unlikely to win any converts to the notion of a data-curious* view of learning. Part of what's going to get stuck in the craw is that phrase "data mining," I reckon. Despite all the potential and all the buzz about (big) data, data-mining remains something with a fairly negative connotation. Advertisers. Political campaigns. Big government. All sifting through your personal data, trying to uncover the things that nobody knows about, trying to get you to buy or sell or vote. Add to that now the knowledge that every click we make online -- every YouTube view and Facebook like and Google query -- is eminently trackable, it's enough to make all those unsolicited phone calls and junk mail seem quite benign, not to mention old-fashioned.

Researchers can find and read papers online, rather than having to manually track down print copies.  Machines  (computers) can index the papers and extract the details (titles,  keywords etc.) in order to alert scientists to relevant material.  In addition, computers can extract factual data and meaning by "mining" the content, opening  up the possibility that machines could be used to make connections (and  even scientific discoveries) that might otherwise remain invisible to  researchers. However,  it is not generally possible today for computers to mine the content in papers due to constraints imposed by publishers.  While Open Access (OA) is improving the ability for researchers to read papers (by removing  access barriers), still only around 20% of scholarly papers are OA. The  remainder are locked  behind paywalls. As per the vast majority of subscription contracts, Subscribers may read paywalled papers, but they may not mine them. Content  mining is the way that modern technology locates digital information. Because digitized scientific information comes from hundreds of  thousands of different sources in today's globally connected scientific  community [2] and because current data sets can be measured in  terabytes,[1] it is often no longer possible to simply read a scholarly  summary in order to make scientifically significant use of such  information.[3]  A researcher must be able to copy information,  recombine it with other data and otherwise "re-use" it so as to produce  truly helpful results.  Not only is it a deductive tool to analyze  research data, it is how search engines operate to allow discovery of content. To prevent mining is therefore to force scientists into blind  alleys and silos where only limited knowledge is accessible.  Science  does not progress if it cannot incorporate the most recent findings and  move forward from there.

Insurers' interest in data mining will only grow, says Kevin Pledge, the boss of Insight Decision Solutions, an underwriting-technology consultancy based near Toronto. He has investors interested in a project to develop software to comb Facebook and Twitter for promising sales leads: a woman proud of her pregnancy might want to buy life insurance, for example. Insurance firms will also analyse grocery purchases for clues about policyholders, he predicts. But that raises some sticky questions about privacy. Mr Pledge himself has begun to forgo his supermarket loyalty-card discount on junk food and pay for his burgers in cash. Promising as data mining is, much will depend on how regulators, and consumers, react.

The web is filled with users' descriptions of the effects of psychedelic drugs. Now neuroscientists are using data mining techniques to quantify the effects of these drugs on human consciousness for the first time

The Economist has an interesting piece on insurance companies' increasingly sophisticated methods for sifting through data to judge risk. In addition to checking out public data on social networking sites, insurers can buy information from marketers that might surprise you: "aggregate data about individuals from records of things like prescription-drug and other retail sales, product warranties, consumer surveys, magazine subscriptions and, in some cases, credit-card spending."

Face à l'explosion des données, ce sont les enjeux informatiques qui sont le plus fréquemment évoqués. Pourtant, la question de l'exploitation et de l'usage de ces données est d'abord métier, car elle a un impact direct sur les revenus potentiels des entreprises.

Many entrepreneurs foresee vast profits in mining data from online activity and mobile devices. One Wharton business school professor strongly disagrees.

"Pendant que Barack Obama discute en personne avec les internautes, son adversaire Mitt Romney fait un tout autre usage des technologies numériques pour sa campagne. Comme le révèle une enquête de l'agence de presse américaine Associated Press, relayée en France par le site de La Croix, l'équipe de campagne du candidat républicain préfère se concentrer sur les données produites par les électeurs."

Comment s'informer sur Internet (au sens : acquérir des connaissances vraies et pertinentes) ? La question devrait être résolue depuis longtemps tant il existe de sociétés, consultants, logiciels, qui proposent de nous initier aux délices de la veille sociétale ou stratégique, avec bases de données, cartographie sémantique, knowledge management, crawling, data mining, curation et autres techniques qui mériteraient un bon benchmarking… Ou une bonne explication pour le commun des mortels