Data, Development, Critique
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Beta Release of the Open Contracting Data Standard - Open Contracting [04.09.2014]

Beta Release of the Open Contracting Data Standard - Open Contracting [04.09.2014] | Data, Development, Critique | Scoop.it

The objective of the Data Standard is to support governments to publish contracting data in a more accessible, interoperable and useful manner and to enable the widest possible range of stakeholders to use contracting data effectively.


Some of the features provided by this Beta Release include a description of the overall Open Contracting Data Standard Model and a JSON Schema for open contracting releases and records that includes a set of recommended fields.


The development of the Open Contracting Data Standard is an open process and inputs and feedback are encouraged. Although this will be an ongoing process, those comments provided before September 30, 2014 will be more likely to fully inform version 1.0 of the Standard. These comments will help refine the standard, both the structure and fields, in preparation for the initial release version.

 

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Despite Concessions to U.S. Farmers, Big Data Giants Still in Control - Karl Plume [23.06.2014]

In the tussle between U.S. farmers and Big Data purveyors, farmers are winning some control over details about crop and growing conditions on their land, but most data sellers are retaining ultimate say over how they can use the information that could be worth billions of dollars.

 

Although companies like Deere & Co and Monsanto Co's Climate Corp are giving some ground by putting legal teeth behind promises made during sales pitches, they are refusing to back away from claims they have an absolute right to all data collected as combines, tractors and other equipment work fields across the country...

 

So far, farmers have been willing to share data to gain specific details on farm conditions, and companies have said they do not intend to pay farmers for data. But with Big Data companies planning to sell customer-made seeds or peddle precise crop production estimates, farmers now want a share of the value stream.

 

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The Rise of Open Data Driven Businesses in Emerging Markets - Alla Morrison & Debra Perry [14.05.2014]

The Rise of Open Data Driven Businesses in Emerging Markets -  Alla Morrison	& Debra Perry [14.05.2014] | Data, Development, Critique | Scoop.it

In April, the Open Finances Team at the World Bank, in partnership with the International Finance Corporation (IFC), initiated research of companies in regions and countries that have been making progress in opening up their data – Latin America, Asia, Africa, India and Russia. We wanted to know how many data companies are out there and what the nature is of their businesses? How many of them use open public data? How many are tackling a social problem? We also hoped to get a glimpse of their specific needs and challenges. If we were to set up an investment facility, would there be a sufficient pipeline? What type and size of financing do these companies need? While the research is still in progress in Africa and in Russia, we have uncovered some initial noteworthy trends...

 

First, many new data companies have emerged around the world in the last few years. Of these companies, the majority use some form of government data...

 

Second, the study confirmed that data companies are in a wide range of sectors: business services/analytics, health and wellness, food and agriculture, education, finance, transport, real estate, travel and hospitality. Especially interesting, however, were a large number of data companies in sectors with high social impact and tremendous development opportunities (this is especially important for us at the Bank – given our focus on fighting poverty and increasing shared prosperity)...

 

Third, actionable pipelines of data-driven companies exist in Latin America and in Asia. The most desired type of financing is equity, followed by quasi-equity in the amounts ranging from $100,000 to $5 million, with averages of between $2 and $3 million depending on the region.

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Wanted: Urban Data Revolution for Post 2015 Sustainable Development Goals - David Satterthwaite [16.04.2014]

Wanted: Urban Data Revolution for Post 2015 Sustainable Development Goals - David Satterthwaite [16.04.2014] | Data, Development, Critique | Scoop.it

There are fundamental limitations in what data are currently gathered, from whom they are gathered and to whom they are available and useful. Governments and international agencies use national sample surveys to gather data. But these do not show where action is needed. National sample surveys produce data "for urban population" but not for each urban centre, let alone for each ward or street...

 

Censuses should provide data down to this level, but they are expensive and generally done only every ten years. In many cases the data collected are not available to local governments in a form that allows them to identify the needs...

 

What we really need is more detailed data from each urban centre that describes the deprivations that low-income people face. This must include data on housing conditions, infrastructure and service provision to each street and neighbourhood.

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Don’t Lose Sight of the People behind Big Data - Sanjana Hattotuwa [15.04.2014]

Don’t Lose Sight of the People behind Big Data - Sanjana Hattotuwa [15.04.2014] | Data, Development, Critique | Scoop.it

My primary concern stems from poor transparency and accountability. A concern over governments’ enhanced capability to infer patterns and behaviours by combining large sets of information given voluntarily by people, as well as over how private enterprises, like telecommunications companies, use such data.

In mature democracies, big data can be immensely helpful in driving greater accountability, transparency and service delivery when combined with other information often in the public domain — such as demographic data and geo-located crime statistics. But in a country like Sri Lanka it can lead to a far more restrictive, censorious and pervasive monitoring of movements, transactions and communications.

And there’s the difficult dilemma. Post-war, Sri Lanka urgently needs to exploit big data to become more people-centric and responsive by transforming its antiquated governance mechanisms. However, any such initiative will fall in the shadow of the MoD and other intelligence arms of government.

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Big Data for Development: Facts and Figures - Emmanuel Letouzé [15.04.2014]

Big Data for Development: Facts and Figures - Emmanuel Letouzé [15.04.2014] | Data, Development, Critique | Scoop.it

[T]he term big data may be a misleading misnomer: size isn’t their defining feature. For example, an Excel spreadsheet with CDRs may not be a big file; the entire World Bank Development Indicators database is a big file — but the latter results from fully controlled processes, including surveys and statistical imputations undertaken by official bodies. The difference is primarily qualitative — it’s in the kinds of information contained in the data and the way these are generated...

 

For the foreseeable future, the big data and open data movements will be the two main pillars of a larger ‘data revolution’. Both rise against a background of increased public demand for more openness, agility, transparency and accountability for public data and actions. The political overtones — so easily forgotten — are clear. And so a ‘true’ big data revolution should be one where data can be leveraged to change power structures and decision-making processes, not just create insights.

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Toward a Big Data Revolution for Sustainable Development - Robert Kirkpatrick [19.02.2014]

In choosing the term ‘revolution’, it is clear that Secretary-General Ban Ki-moon’s High Level Panel sought to convey the magnitude of the data-driven transformation required for effective development in a post-2015 world. Yet in doing so they also issued a call to action that seems deliberately open-ended, perhaps to provoke constructive debate...

Coalitions of the willing are being built to improve the quality of official statistics, improve efficiency by complementing existing methods with mobile surveys, m-health or crowdsourcing, and open up access by pushing hard on governments, UN agencies and NGOs to share more of their data in standardized machine-readable formats.

I believe that there can be no data revolution without all of these ingredients.  Yet I am also convinced that even tremendous progress on all of these fronts will not suffice to bring it about.  If we continue to rely upon the same types of information to make development decisions that we always have, we cannot move beyond linear organizational processes we have today...

 

The Industrial Revolution forever changed not only manufacturing, but nearly every aspect of daily life.   What would it take to bring about an analogous revolution in sustainable development, and how will we know when we have arrived?

 

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Development Data: How Accurate are the Figures? - Claire Melamed [31.01.2014]

Development Data: How Accurate are the Figures? - Claire Melamed [31.01.2014] | Data, Development, Critique | Scoop.it

In the absence of robust official systems for registering births and deaths, collecting health or demographic data, or the many other things that are known by governments about people in richer countries, the household survey is the foundation on which most development datais built. Numbers from the surveys are used to estimate almost all the things we think we know – from maternal mortality to school attendance to income levels. Household surveys are run by governments or by external agencies such as the World Bank, USAid or Unicef.

But it's a shaky foundation. First, to make the survey representative of the population, you need to know a lot about the population to make a good sampling frame. This knowledge comes from a population census. But only around 12 of the 49 countries in sub-Saharan Africa have held a census in the past 10 years. So there might be large population groups missing – especially in countries undergoing rapid change. There are likely to be big urban informal settlements, for example, which are not included in the most recent census, and therefore don't exist for sampling purposes. They also don't happen very often – 21 African countries haven't had a survey in the past seven years.

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Big Data and Modernization of Statistical System: Report of the Secretary-General - UN Economic and Social Council [20.12.2013]

The present report, which was prepared in accordance with Economic and Social Council decision 2013/235, offers an assessment of the current use of big data for official statistics. The report provides an overview of recent activities of the official statistical community and presents the results of the global assessment on the use of big data for official statistics conducted by the Statistics Division in 2013.

The report formulates a way forward through the creation of a working group at the global level, which builds on existing regional initiatives towards sharing with respect to methodological developments, best practices for strategic issues and training opportunities. The working group will also facilitate the international partnership for the use of big data in the transfer of technology to developing countries and in support of the post-2015 development agenda. The Statistical Commission is invited to express its views on the proposal made in the final section of the report.

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A Bottom-Up Data Revolution for Post-2015 - Ian Thorpe [10.12.2013]

A Bottom-Up Data Revolution for Post-2015 - Ian Thorpe [10.12.2013] | Data, Development, Critique | Scoop.it

Often the benefit is seen in terms of having access to better statistics, real time monitoring and feedback, big data analysis and transparent data on aid and government spending. Such a treasure trove of data could support better the monitoring and evaluation of development interventions so that aid agencies can design better programmes, donors can allocate resources more efficiently and researchers can better test their development theories.

 

But I’d argue that the most significant and also most challenging part of the data revolution will come from the bottom up. While aid transparency can help to hold funders or even partner governments to account, the area where improved accountability is most needed is with respect to those whom the aid is intended to help.

 

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Data for Development: Revolution Kicks off in Côte d’Ivoire - Mico Tatalovic [29.11.2013]

Data for Development: Revolution Kicks off in Côte d’Ivoire - Mico Tatalovic [29.11.2013] | Data, Development, Critique | Scoop.it

Mobile communications company Orange has huge amounts of data on traffic between its mobile masts, and in 2012 it decided to release some of that data from Côte d’Ivoire to researchers worldwide in a challenge to make use of that data. It anticipated 40 or 50 project applications and got 260 instead, though few came from African countries or Côte d’Ivoire itself.

The results, first released in May this year, were astounding. What had been — and largely remains — locked-up data, was analysed and presented by scientists to reveal a host of information with development applications.

Examples include better understanding of disease epidemics and their control, better traffic and parcel delivery planning, and insights into social divisions.

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Open Data and Improving Governance: Issues of Measurement - Tim Davies [14.11.2013]

It seems fair to state as a basic assumption that information does change governance. On the flight here I was reading work by Eleanor Ostrom on governance of the commons, which emphasises the central role of information in governance. Changing how information flows does impact governance – but assessing whether that impact is positive or negative involves normative questions. Right now – the impact of open data on effectively altering the flow of information across society is limited. We see highly-used apps in a limited number of settings like transport, but beyond that we see relatively few datasets that are truly available as open data. When we dig into many of the anecdotes shared about open data impacts, it often turns out that wider contextual variables are much more important in determining outcomes than the particular open properties of the data itself. And yet, policy seems to focus on a replication of a standard model of open data data publication as the primary intervention.

 

Ultimately in taking measurement forward I’d like to suggest we look in two directions. Firstly, we need to drill down thematically, focussing on data in context in particular settings, looking to generate actionable knowledge for practitioners in these sectors that will help them to advocate bottom-up for open data – rather than focussing on over-generalised measurement that seeks to promises generalised open data impacts without understanding differences of subject matter and context. Secondly, we need to explore developing rigorous shared case study methodologies that can enable us to build measurement and research through controlled cross-case comparisons, informing macro-level assessments, but focussing on micro-level effects and theories of change around open data.

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My Data Revolution is Not Your Data Revolution - Margo Cointreau & Mahesh Subedi [07.11.2013]

My Data Revolution is Not Your Data Revolution - Margo Cointreau & Mahesh Subedi [07.11.2013] | Data, Development, Critique | Scoop.it

First, the data revolution will mean something different in each country, but that doesn’t preclude developing useful tools and approaches. Our Guidelines for developing National Strategies for the Development of Statistics (NSDSs) offer an instructive example...

Second, we should respond to existing demands and build “coalitions of the willing” to begin tackling emerging challenges... We are already developing an action plan to respond to specific demands that emerged. In both cases, the lessons learned can be shared more broadly and help convince the not-so-willing to get engaged in new areas of the data revolution.

Third, the “leave no one behind” agenda is itself a call for diversity – diversity of data production along, for instance, gender, geographic and demographic lines. Though widely embraced, it is rooted in the specific historical and cultural mosaic of individual countries and, as such, should be supported by national and regional authorities.

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Big Data Climate Challenge Winners Show How Big Data Can Drive Climate Action [03.09.2014]

Big Data Climate Challenge Winners Show How Big Data Can Drive Climate Action [03.09.2014] | Data, Development, Critique | Scoop.it

The Challenge is a global competition hosted by United Nations Global Pulse, an initiative of the Secretary-General on big data. The Challenge was launched in May 2014 to unearth fresh evidence of the economic dimensions of climate change around the world using data and analytics. Submissions were received from 40 countries, representing more than 20 topics — from forestry, biodiversity and transportation to renewable energy and green data centers.

 

Two overall Big Data Climate Challenge winners and seven “Projects to Watch” were selected by a high-level Advisory Board and Technical Committee of global experts in climate science, sustainable development and big data. Submissions were evaluated on their use of big data, economic relevance, stakeholder engagement, originality and scalability. The “Projects to Watch” were chosen to highlight particularly innovative uses of big data in emerging topics and geographic regions...

 

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On Taxis and Rainbows - Vijay Pandurangan [21.06.2014]

On Taxis and Rainbows - Vijay Pandurangan [21.06.2014] | Data, Development, Critique | Scoop.it

These [trip and fare log] data are a veritable trove for people who love cities, transit, and data visualization. But there’s a big problem: the personally identifiable information (the driver’s licence number and taxi number) hasn’t been anonymized properly — what’s worse, it’s trivial to undo, and with other publicly available data, one can even figure out which person drove each trip. In the rest of this post, I’ll describe the structure of the data, what the person/people who released the data did wrong, how easy it is to deanonymize, and the lessons other agencies should learn from this...

 

Security researchers have been warning for a while that simply using hash functions is an ineffective way to anonymize data. In this case, it’s substantially worse because of the structured format of the input data. This anonymization is so poor that anyone could, with less then 2 hours work, figure which driver drove every single trip in this entire dataset. It would be even be easy to calculate drivers’ gross income, or infer where they live.

 

 

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Ag+Data - Paco Nathan [21.04.2014]

Ag+Data - Paco Nathan [21.04.2014] | Data, Development, Critique | Scoop.it

In the US much of our agricultural base has been consolidated into corporate farms. While the corporate farms are terrified to release their data, they have an almost single-minded focus on increasing yield. Monsanto and other tech giants insist on obtaining data, with an almost single-minded focus on promising to increase yield. Finance wants the data to place bets about yield. In the best of scenarios a stalemate ensues; more likely outcomes are considerably less positive. That tension gets caused because of the data, and how we as a society determine its appropriate use.

 

Meanwhile, Monsanto itself may become well-positioned as a large and uniquely powerful hedge fund in the near future: consider that the firm has begun to pin-point crop yields, per-plot, at the time of harvest. How readily could data products based on that vantage point be played in commodity markets?

 

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Open Data and the United Nations: Experts Reflect on Current Open Data Challenges within the UN and Outline a Path Forward - Asiya Wadud [16.04.2014]

On April 2, the Governance Lab (the GovLab) and the United States Mission to the United Nations (USUN) convened a meeting to reflect upon a wide array of issues pertaining to the value of open data – with a particular focus on the United Nations. The meeting brought together technology experts, academics, United Nations officials, and officials from the U.S. Mission to the UN (see below for a full list of participants) to discuss how the UN currently uses open data; reflect on open data initiatives both inside and outside the UN to draw comparative analyses; discuss the value proposition for using open data within the UN; and determine the gaps and additional areas of consideration.

 

 

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Big Obstacles ahead for Big Data for Development - Jan Piotrowski [15.04.2014]

Big Obstacles ahead for Big Data for Development - Jan Piotrowski [15.04.2014] | Data, Development, Critique | Scoop.it

“At the moment, the explosion of big data has far-outpaced our ability to make sense of it in all countries, but most of all in poorer nations that already lack human and technical capacity,” says Claire Melamed, head of the growth, poverty and inequality programme at the Overseas Development Institute, United Kingdom.
 
“We are all running to catch up with the technology.”
 
The question is how best to make up the ground. What are the capacity gaps that need filling, what are potential uses and limitations, and who are the key players that need support to make it happen?...

 

Barring exceptions such as Indonesia, where social media use is high, the few people that use the internet regularly in developing nations are predominantly young and wealthy, she says. So any attempts to draw broad conclusions on the status of the ‘internet population’ will be skewed.
 
The dangers of drawing conclusions from unrepresentative data are illustrated by an attempt to apply Google Flu Trends — a mapping exercise in the United States based on flu-related internet searches — to Bolivia, she says. Attempts to determine the prevalence of flu from digital activity in Bolivia failed because its population relies on doctors or traditional healers to diagnose flu, in contrast to a high number of Americans going online.

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The Specter of Big Data is Haunting the World, but has the Data Revolution Already Occurred? - Prasanna Lal Das [05.03.2014]

The Specter of Big Data is Haunting the World, but has the Data Revolution Already Occurred? - Prasanna Lal Das [05.03.2014] | Data, Development, Critique | Scoop.it

The data revolution conversation is largely dominated by traditional forces (despite the contradiction in terms!) – mostly official agencies, recognized think tanks, and universities that have the mandate to collect, curate, and distribute essential data (though there has been concerted effort to include new players)... 

 

The question thus inevitably is whether the revolution has already left such agencies in its wake or do they still have a chance to make up lost ground? I would like to say that the official agencies will continue to be vital, but some traditional partnerships may include several new faces...

Why do we need a data revolution? At least some of the discussion around the data revolution has focused on ‘supply side’ issues such as data gaps and quality, better documentation, technology infrastructure for data, the usability and openness of data, and the challenge of big data. The discussion on demand has centered on ‘evidence’, ‘accountability’ and ‘decision making’ but is this a gap that ‘official’ data revolutionaries can fill better than let’s say the private sector?


The groups in charge of the data revolution hope for an orderly transition, a change of order that follows today’s rules, a gradual evolution that accretes into a revolution. Outside the development world, a parallel revolution may already be underway however.

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Is Big Data a Silver Bullet for Development? - Kaz Janowski [31.01.2014]

Is Big Data a Silver Bullet for Development? - Kaz Janowski [31.01.2014] | Data, Development, Critique | Scoop.it

“Data is not a silver bullet,” warned Olav Kjorven, special advisor to the UNDP administrator on the post-2015 development agenda. “The data revolution is ultimately a political issue — not just a technical issue.”

To stress that global partnership is the order of the day, he added: “Nobody will emerge a hero of the data revolution by going it alone”...

 

Data is crucial to development, we heard, because it provides a movie rather than a snapshot of what’s happening on the ground. I liked that, but immediately thought that movies are not reality, rather they create an illusion of reality. Is this something to be concerned about?

A PowerPoint slide of a gushing oil well introduced another metaphor. “Data is the oil of the twenty-first century” — it fuels and lubricates society, it needs refining and, to this end, it needs data scientists.

 

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From Open Data to Development Impact: The Crucial Role of the Private Sector - Prasanna Lal Das & Alla Morrison [08.01.2014]

Can open data lead to reduced energy consumption (and therefore slow down climate change)? Can open data help improve maternal health services (and thus improve facets of public delivery of services)? Can open data help farmers and crop insurers make better crop predictions (and thus lead to smarter investment decisions in agriculture)? Can open data empower citizens to fight back against police corruption (and thus help promote the rule of law)?...

The answer to all the questions above is a resounding YES – at least far as the developed economies go. The private sector is constantly building new businesses and services that use public data to provide services that are not only commercially viable but also create positive development impact...


The question at the table is what can development organizations do to catalyze this market and hasten the associated development outcomes, especially in developing countries? How can governments and private sector companies in developing countries work together to take advantage of commercial and development opportunities in what McKinsey estimates is a $3 trillion+ open data market? How do we make sure that the growing amount of open data is truly used in new and interesting ways that early open data pioneers had hoped for?

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Open Data and Transparency: A Look Back at 2013 - Zoe Smith [19.12.2013]

Open Data and Transparency: A Look Back at 2013 - Zoe Smith [19.12.2013] | Data, Development, Critique | Scoop.it

But just the extent to which transparency and open data can actually deliver on its revolutionary potential has also been called into question. Governments and donors agencies can release data but if the power structures within which this data is consumed and acted upon do not shift is there really any chance of significant social change?

The complexity of the challenge is illustrated by the case of Mexico which, in 2014, will succeed Indonesia as chair of the Open Government Partnership. At this year's London summit, Mexico's acting civil service minister, spoke of the great strides his country has made in opening up the public procurement process, which accounts for around 10% of GDP and is a key area in which transparency and accountability can help tackle corruption...

 

As Vergara-Camus cautions, "the complexity of delivering transparency and accountability depends a great deal on the presence or absence of independent, and I stress the independent, civil society organisations and social movements."

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How to Engineer a Data-for-Development Revolution? - Mico Tatalovic [02.12.2013]

How to Engineer a Data-for-Development Revolution? - Mico Tatalovic [02.12.2013] | Data, Development, Critique | Scoop.it

So what is actually needed to get better use of digital data in development?
 
The key messages coming out of the meeting were that support needs to be given not only to the national statistical offices in developing countries that are currently ill-equipped and reluctant to partake in such a revolution, but also to make sure there is a demand for such data from citizens and that the final packaging of data is easy to use and practical for improving delivery of public services and improving lives.
 
As one participant said, the key is to make data usable, “otherwise data will remain just data”.

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The Importance of Open Data Critiques - Thoughts and Context - David Eaves [18.11.2013]

The Importance of Open Data Critiques - Thoughts and Context - David Eaves [18.11.2013] | Data, Development, Critique | Scoop.it

We – open data advocates – are now complicit it what many of the above (mostly) men decide to do around open data. Hence the importance of Rob’s post. Previously those with power were dismissive of open data – you had to scream to get their attention. Today, those same actors want to act now and go far. Point them (or the institutions they represent) in the wrong direction and/or frame an issue incorrectly and you could have a serious problem on your hands. Consequently, the responsibility of advocates has never been greater. This is even more the case as open data has spread. Local variations matter. What works in Vancouver may not always be appropriate in Nairobi or London.

I shouldn’t have to say this but I will, because it matters so much:

 

Read the critiques. They matter. They will make you better, smarter, and above all, more responsible.

 

 

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Four Critiques of Open Data Initiatives - Rob Kitchin [09.11.2013]

Open data initiatives hold much promise and value.  They are radically altering access to publicly produced data and making new kinds of analysis possible.  They are creating new forms of transparency and accountability, fostering new form of social participation and evidence-informed modes of governance, and promoting innovation and wealth generation. 

 

At the same time, much more critical attention needs to be paid to how open data projects are developing as complex socio-technical systems with diverse stakeholders and agendas. To date, efforts have concentrated on the political and technical work of establishing open data projects, and not enough on studying these discursive and material moves and their consequences.  As a result, we lack detailed case studies of open data projects in action, the assemblages surrounding and shaping them, and the messy, contingent and relational ways in which they unfold. 

 

It is only through such studies that are more complete picture of open data will emerge, one that reveals both the positive and negatives of such projects, and which will provide answers to more normative questions concerning how they should be implemented and to what ends.

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