Category: big data

Philosophy of Data Science series – Noortje Marres: Technology and culture are becoming more and more entangled.

Mark Carrigan continues his investigation of data science with this latest interview with Noortje Marres on Digital Sociology. Growing digital awareness means lots of opportunities for collaboration between sociology and related fields and there is also a chance for sociologists to challenge the deeply-rooted narrative of a clash between technology and democracy. This interview is part of an ongoing series on the Philosophy of […]

Stand Up and Be Counted: Why social science should stop using the qualitative/quantitative dichotomy

Qualitative and quantitative research methods have long been asserted as distinctly separate, but to what end? Howard Aldrich argues the simple dichotomy fails to account for the breadth of collection and analysis techniques currently in use. But institutional norms and practices keep alive the implicit message that non-statistical approaches are somehow less rigorous than statistical ones. Over the past year, I’ve met with many doctoral students […]

Everyday webpages as scholarly source material: Interrogating the archived UK Web.

With the advances in web analysis, Adam Crymble hails the opportunity for historians to turn to the Internet as a rich source in itself. But are historians trained to take advantage of this new opportunity? Corpus linguistics, data manipulation, clustering algorithms, and distant reading will be valuable skills for dealing with this new body of historical data. The second talk […]

Data Infrastructure, Education & Sustainability: Notes from the Symposium on the Interagency Strategic Plan for Big Data

Last week, the  National Academies Board on Research Data and Information hosted a Symposium on the Interagency Strategic Plan for Big Data. Staff from the National Institutes of Health, the National Science Foundation, the U.S. Geological Survey and the National Institute for Standards and Technology presented on ongoing work to establish an interagency strategic plan […]

Call to arms for shaking up social sciences relies on false premise that science alone can solve all social problems.

A new form of ‘interdisciplinarity’ may be emerging but has so far failed to devote equal demands on the natural sciences, as well as on the social sciences. Will Davies responds to the calls for a social science shake-up by questioning the status of the social sciences in 2014 as something other than mere understudies to the natural sciences. The shared terrain […]

A systems-thinking approach to public policy eschews linear model for more holistic understanding of decision-making.

Policy-making and effective municipal intervention are embedded in a complex web of interrelationships. Joseph A. Curtatone and Mark Esposito write on how decisions in one realm have ripple effects in others. Systems-thinking looks to apply a more holistic way of addressing real-world problems. Harvard students and the city of Somerville, Massachusetts are partnering to tackle problems using a systems-focused approach. For public officials, the law […]

Data carpentry is a skilled, hands-on craft which will form a major part of data science in the future.

As data science becomes all the more relevant and indeed, profitable, attention has been placed on the value of cleaning a data set. David Mimno unpicks the term and the process and suggests that data carpentry may be a more suitable description. There is no such thing as pure or clean data buried in a thin layer of non-clean data. In reality, […]

Book Review: Managing and Sharing Research Data: A Guide to Good Practice by Louise Corti et al.

Research funders across the world are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. This guide aims to cover guidance on how to plan your research using a data management checklist, how to format and organize data, and how to publish and cite data. This is a useful guide for students and […]

Audible Impact Episode 3: Big Data and the Future of the Social Sciences

  In this podcast, Professor Patrick Dunleavy talks about how big data will affect the future of the social sciences. Say goodbye to academic siloes as we enter into a new age of cross/multi/and inter-disciplinary research. In this changing landscape, the old boundaries between physical, social and data science disintegrate. Here Professor Dunleavy talks about the Social Science of Human-Dominated […]