Open Data: What’s new in 2017?

I am now in Montréal, where I participated, last Friday, in a panel on Open Data at “Science & You” international conference. It was interesting for me to reflect on how the picture has changed since my previous panel on the same topic – in Kiev in 2012. Back then, we were busy trying to convince public administrations that data opening was good for transparency and could help improve services to communities. Since then, a lot of attempts have been made in numerous countries – local authorities often pioneering the process, followed only later by central governments (one example cited in my panel was Québec City). What is made open is typically information from public registers (first names of newborns, records of road accidents) and increasingly, from technological devices and sensors (bus traffic information).

There are some conditions to be met for a dataset to be said “open”:

  • Technically, it needs to be “raw”, detailed, digital and reusable. The French Interior Ministry released results of the first round of the recent presidential elections within a few days, at polling station level. This is sufficiently detailed (with over 69,000 polling stations throughout the country), raw (allowing aggregations, comparisons etc.), and digital/reusable (so much so that the newspaper Le Monde could develop a user-friendly application to let readers easily check results in their neighborhoods). Some would also insist that “open” data should be released in non-proprietary formats (better .csv than .xls, for example).
  • Legally, the data must come with a license that allows re-use by third parties (typically within the Creative Commons family). Ideally, no type of reuse should be ruled out (including somewhat controversially, commercial / for-profit reuse).
  • Economically, the data should be available to all for free (or at least with minimal charges if data preparation requires extra work or expenses).

If in the past few years, a lot of thought has been devoted to the “ideal” conditions for data opening and how this would positively affect public service, the data landscape has now significantly changed.

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Visualisation, mixed methods and social networks: what’s new

This morning, we had a plenary on “Visualisation and social networks in mixed-methods sociological research” at the British Sociological Association conference now going on in Manchester. This session, organized by the BSA study group on social networks that I convene with Alessio D’Angelo (BSA SNAG), builds on a special section of Sociological Research Online that we edited in 2016. Alessio and I chaired and had four top-flying speakers: Nick Crossley, Gemma Edwards (both at the University of Manchester), Bernie Hogan (Oxford Internet Institute) and Louise Ryan (University of Sheffield).

Each speaker briefly presented a case study that involved visualization, and all were great in conveying exciting albeit complex ideas in a short time span. What follows is a short summary of the main insight (as I saw it).

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A cooperative approach to platforms

I was yesterday at a nice and interesting conference in Brussels on “How to coop the collaborative economy“, organized by major actors of the Belgian cooperative movement and building on the experience of a growing network of persons and organizations to enhance a cooperative view of the internet. Several themes in connection with my studies of the collaborative economy emerged, and I’d like to summarize here what were, in my view, the main lessons learned of the day.

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Special RFS issue on Big Data

Revue Française de Sociologie invites article proposals for a special issue on “Big Data, Societies and Social Sciences”, edited by Gilles Bastin (PACTE, Sciences Po Grenoble) and myself.

Focus is on two inextricably interwoven questions: how do big data transform society? How do big data affect social science practices?

Substantive as well as epistemological / methodological contributions are welcome. We are particularly interested in proposals that examine the social effects and/or the scientific implications of big data based on first-hand experience in the field.

The deadline for submission of extended abstracts is 28 February 2017; for full contributions, it is 15 September 2017. Revue Française de Sociologie accepts articles in French or English.

Further details and guidelines for submission are in the call for papers.

Data in the public sector: Open data and research data

OpendataThe “open data” movement is radically transforming policy-making. In the name of transparency and openness the UK, US and other governments are releasing large amounts of records. It is a way to hold the government to account: in UK for example, all lobbying efforts in the form of meetings with senior officers are now publicly released. Data also enable the public to make more informed decisions: for example, using apps from public transport services to plan their journeys, or tracking indicators of, say, crime or air pollution levels in their area to decide where to buy property. Data are provided as a free resource for all, and businesses may use them for profit.

The open data movement is not limited to the censuses and surveys produced by National Statistical Institutes (NSIs), the public-sector bodies traditionally in charge of collecting, storing and analyzing data for policy purposes. It extends to other administrations such as the Department for Work and Pensions or the Department for Education in the UK, which also gather and process data, though usually through a different process, not using questionnaires but rather registers.

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Hallo world – a new blog is now live!

Hallo Data-analyst, Data-user, Data-producer or Data-curious — whatever your role, if you have the slightest interest in data, you’re welcome to this blog!

This is the first post and as is customary, it needs to tell what the whole blog is about. Well, data. Of course! But it aims to do so in an innovative, and hopefully useful, way.

DataBigAndSmall2

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