Infolab-Campagne

Un rappel de ce qu'il se dit un peu partout sur le terme "data science". 

Algorithms are increasingly invoked as powerful entities that control, govern, sort, regulate, and shape everything from financial trades to news media. Nevertheless, the nature and implications of such orderings are far from clear. What exactly is it that algorithms "do"? What is the role attributed to "algorithms" in these arguments? How can we turn the "problem of algorithms" into an object of productive inquiry?

Where can I find a good data scientist? What do I need to learn to become a data scientist? Or more succinctly: What is data science? L'auteur propose une taxinomie pour définir la science des données. Normalement un vrai datascientist devrait être à l'aise avec ces 5 "sphères" : Obtain, Scrub, Explore, Model, and iNterpret

Andrew McAfee, principal research scientist at the M.I.T. Center for Digital Business, led off the conference by saying that Big Data would be "the next big chapter of our business history. Big Data, said Professor Brynjolfsson, will "replace ideas, paradigms, organizations and ways of thinking about the world." The results, according to technologists and business executives, will be a smarter world, with more efficient companies, better-served consumers and superior decisions guided by data and analysis. The problem is that a math model, like a metaphor, is a simplification. This type of modeling came out of the sciences, where the behavior of particles in a fluid, for example, is predictable according to the laws of physics. Les bonnes questions à se poser quand on gère un projet de big data "How do you define the problem? What data do you need? Where does it come from? What are the assumptions behind the model that the data is fed into? How is the model different from reality?"

Ensemble des ressources documentaires

plusieurs articles à lire 

Super pearltrees sur la science des données par JC.Plantin (UTC Compiègne).

Article de Henri Verdier (Etalab) qui discute l'analogie donnée = pétrole. Il attaque Stéphane Grumbach (INRIA) indirectement? Geoffrey Delcroix de la CNIL essaye de relancer le débat...ça chauffe sur les réseaux.

Restitution d'une communication de deux de chercheurs de MineParitech sur les enjeux de l'open data.

Un article issu de l'INIST (CNRS) qui résume les principales remarques formulées par un collectif de développeurs/informaticiens sur la qualité des données et sur les efforts à réaliser pour améliorer leurs conditions d'utilisation. Le livre a été publiépar O'Reilly Média