Didactics and Technology in Education

Big Data & Society (BD&S) is an open access peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies.

The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business and government relations, expertise, methods, concepts and knowledge.

BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practices that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government and crowdsourced data.  Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes.

InBloom’s trajectory has shined a spotlight on the public’s sensitivity around what happens to student data. When it first began as a mammoth ed-tech project in 2011 by the Council of Chief State School Officers, the Bill and Melinda Gates Foundation and the Carnegie Corporation called the Shared Learning Infrastructure, the purpose was to provide open-source software to safely organize, pool, and store student data from multiple states and multiple sources in the cloud. That included everything from demographics to attendance to discipline to grades to the detailed, moment-by-moment, data produced by learning analytics programs like Dreambox and Khan Academy. An API — application programming interface — would allow software developers to connect to that data, creating applications that could, at least in theory, be used by any school in the infrastructure.