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The long read: Interconnected technology is now an inescapable reality – ordering our shopping, monitoring our cities and sucking up vast amounts of data along the way. The promise is that it will benefit us all – but how can it? Via Dr. Susan Bainbridge 
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After decades as a technological laggard, medicine has entered its data age. Mobile technologies, sensors, genome sequencing, and advances in analytic software now make it possible to capture vast amounts of information about our individual makeup and the environment around us. The sum of this information could transform medicine, turning a field aimed at treating the average patient into one that’s customized to each person while shifting more control and responsibility from doctors to patients. The question is: can big data make health care better? “There is a lot of data being gathered. That’s not enough,” says Ed Martin, interim director of the Information Services Unit at the University of California San Francisco School of Medicine. “It’s really about coming up with applications that make data actionable.” The business opportunity in making sense of that data—potentially $300 billion to $450 billion a year, according to consultants McKinsey & Company—is driving well-established companies like Apple, Qualcomm, and IBM to invest in technologies from data-capturing smartphone apps to billion-dollar analytical systems. It’s feeding the rising enthusiasm for startups as well. Venture capital firms like Greylock Partners and Kleiner Perkins Caufield & Byers, as well as the corporate venture funds of Google, Samsung, Merck, and others, have invested more than $3 billion in health-care information technology since the beginning of 2013—a rapid acceleration from previous years, according to data from Mercom Capital Group. Via nrip
Vigisys's curator insight,
July 27, 2014 4:34 AM
La collecte de données de santé tout azimut, même à l'échelle de big data, et l'analyse de grands sets de données est certainement utile pour formuler des hypothèses de départ qui guideront la recherche. Ou permettront d'optimiser certains processus pour une meilleure efficacité. Mais entre deux, une recherche raisonnée et humaine reste indispensable pour réaliser les "vraies" découvertes. De nombreuses études du passé (bien avant le big data) l'ont démontré...
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Following the previous post... The structural paradigm of Social Network Analysis (SNA) with its constitutive theory and methods, began to emerge around the 1930s, applied and influenced by a broa... Via Dr. Susan Bainbridge
Milena Bobeva's curator insight,
March 1, 2014 4:10 AM
Social Network Analysis should be a paradigm for researching, designing, and evaluating not only online learning, but the wider phenomenon of Education 3.0 
luiy's curator insight,
March 1, 2014 7:21 PM
The connections within nodes in a network facilitate exchange of “resources” which can be influenced by the quantity and quality of the linkages and interactions. Looking at online educational networks through a SNA lens is a way to establish wether the ways in which individuals connect with a particular environment may influence their access to information and knowledge. As Rita Kop states “the Web is portrayed as a democratic network on which peer to peer interaction might lead to a creative explosion and participative culture of activity” (Kop, 2012 p3) but how is this potential being exploited in education? What are the processes beyond this interaction and how can they be used to facilitate students access to information, knowledge and ideas?
The potential of social media in forming networks, extending students knowledge and translating this into academic achievement is impacted by a multitude of elements such as individuals’ attitudes (Morrison, 2002), University environment and socialisation processes (Yu et al., 2010). Other mechanisms influencing this process may be the particular educational practices and experiences, the success of connections, the dynamics in which participants negotiate the structure of the network and exchange practices and many others which can not be controlled.
This analysis can be enriched by Bordieau’s concept of “social capital”, which introduces a set of dynamics between the social dimension, the identity dimension (habitus) and the individual’s practice. In this system of reciprocal influences it is interesting to look at the transformation processes and effects of elements such as “weak ties”, “brokers”, “latent connections” and “structural holes” in the information flow within a network. |
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This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, history, economy and society. It is argued that: (1) Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and (2) there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology. Via luiy
luiy's curator insight,
January 8, 2015 11:12 AM
Whilst Jim Gray envisages the fourth paradigm of science to be data-intensive and a radically new extension of the established scientific method, others suggest that Big Data ushers in a new era of empiricism, wherein the volume of data, accompanied by techniques that can reveal their inherent truth, enables data to speak for themselves free of theory. The empiricist view has gained credence outside of the academy, especially within business circles, but its ideas have also taken root in the new field of data science and other sciences. In contrast, a new mode of data-driven science is emerging within traditional disciplines in the academy. In this section, the epistemological claims of both approaches are critically examined, mindful of the different drivers and aspirations of business and the academy, with the former preoccupied with employing data analytics to identify new products, markets and opportunities rather than advance knowledge per se, and the latter focused on how best to make sense of the world and to determine explanations as to phenomena and processes.
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Privacy concerns have put the breaks on many efforts to use "big data" in education. Why are people so skittish of education data when other kinds of digital information are readily accessible? Via luiy
luiy's curator insight,
April 15, 2014 7:50 PM
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.
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As part of the UCL Grand Challenge of Sustainable Cities, the London 2062 project is gathering evidence about the forces and factors that shape London, identifying decision points, and debating how the city will change over the five decades between London 2012 and London 2062. This process involves synthesising the diverse expertise within the academic community at UCL and elsewhere, together with London’s citizens, government, professions, artists, media and other public institutions. Via Claudia Mihai, luiy
luiy's curator insight,
December 3, 2013 8:47 AM
Imagining the Future City: London 2062 (free download) is an edited collection based on the London 2062 project from UCL’s Grand Challenge of Sustainable Cities. The London 2062 project engaged academics, policy makers and practitioners, providing a forum for serious debate about the challenges and opportunities for London in the five decades following the Olympics.
The aim of this book, and the London 2062 programme, is to open discussion about the future of London. What is the future we want to see for London? Which priorities for a global city are in opposition? How can we meet carbon emission targets and deliver new infrastructure in the 21st Century? 
Intriguing Networks's curator insight,
December 8, 2013 5:58 PM
LONDON CALLING - How will you influence the shape of your city get involved folks! Thank you @plevy |
