In defense of “slacktivism”: The Human Rights Campaign Facebook logo as digital activism

Curated on Posted on by Stefaan Verhulst

Stephanie Vie in First Monday: “This paper examines the Human Rights Campaign (HRC) Marriage Equality logo as an example of a meme to further understandings of memetic transmission in social media technologies. The HRC meme is an important example of how even seemingly insignificant moves such as adopting a logo and displaying it online can serve to combat microaggressions, or the damaging results of everyday bias and discrimination against marginalized groups. This article suggests that even small moves of support, such as changing one’s Facebook status to a memetic image, assist by demonstrating a supportive environment for those who identify with marginalized groups and by drawing awareness to important causes. Often dismissed as “slacktivism,” I argue instead that the digital activism made possible through social media memes can build awareness of crucial issues, which can then lead to action.”

How Cities Can Be Designed to Help—or Hinder—Sharing

Curated on Posted on by Stefaan Verhulst

Jay Walljasper in Yes!: Centuries before someone first uttered the words “sharing economy,” the steady rise of cities embodied both the principles and promise of that phrase. The reason more than half the people on earth now live in urban areas is the advantages that come from sharing resources, infrastructure, and lives with other people. Essential commons belonging to all of us, ranging from transportation systems to public health safeguards to plentiful social connections, are easier to create and maintain in a populated area.
Think about typical urban dwellers. They are more likely to reside in an apartment building, shared household, or compact living unit (saving on heating, utilities, original construction costs, and other expenses), walk or take transit (saving the environment as well as money), know a wide range of people (expanding their circle of friends and colleagues), and encounter new experiences (increasing their knowledge and skills).
Access to these opportunities for sharing offers economic, social, environmental, and educational rewards. But living in a populated area does not automatically mean more sharing. Indeed, the classic suburban lifestyle—a big, single-family house and a big yard isolated from everything else and reachable only by automobile—makes sharing extremely difficult….
“The suburbs were designed as a landscape to maximize consumption,” Fisher explains. “It worked against sharing of any kind. People had all this stuff in their houses and garages, which was going unused most of the time.”
Autos replaced streetcars. Kids rode school buses instead of walking to school.
Everyone bought their own lawn mower, shovels, tools, sports equipment, and grills.
Even the proverbial cup of sugar borrowed from a neighbor disappeared in favor of the 10-pound bag bought at the supermarket.
As our spending grew, our need for social connections shrank. “Mass consumption was good for the economy, but bad for our well-being,” Fisher notes. He now sees changes ahead for our communities as the economy evolves.
“The new economy is all about innovation, which depends on maximizing interaction, not consumption.”
This means redesigning our communities to bring people together by giving everyone more opportunities to “walk, live close together, and share.”
This shift can already be seen in farmers markets, co-working spaces, tool libraries, bike sharing systems, co-ops, credit unions, public spaces, and other sharing projects everywhere.
“Creative people in cities around the world are rising up…” declares Neal Gorenflo, co-founder of Shareable magazine. “We are not protesting, and we are not asking for permission, and we are not waiting—we are building a people-powered economy right under everyone’s noses.”
Excited by this emerging grassroots movement, Shareable recently launched the Sharing Cities Network to be an independent resource “for sharing innovators to discover together how to create as many sharing cities around the world as fast as possible.”
The aim is to help empower and connect local initiatives around the world through online forums, peer learning, and other ways to boost collaboration, share best practices, and catalyze new projects.”

Why Are Rich Countries Democratic?

Curated on Posted on by Stefaan Verhulst

Ricardo Hausmann at Project Syndicate: “When Adam Smith was 22, he famously proclaimed that, “Little else is requisite to carry a state to the highest degree of opulence from the lowest barbarism, but peace, easy taxes, and a tolerable administration of justice: all the rest being brought about by the natural course of things.” Today, almost 260 years later, we know that nothing could be further from the truth.
The disappearance of Malaysia Airlines Flight 370 shows how wrong Smith was, for it highlights the intricate interaction between modern production and the state. To make air travel feasible and safe, states ensure that pilots know how to fly and that aircraft pass stringent tests. They build airports and provide radar and satellites that can track planes, air traffic controllers to keep them apart, and security services to keep terrorists on the ground. And, when something goes wrong, it is not peace, easy taxes, and justice that are called in to assist; it is professional, well-resourced government agencies.
All advanced economies today seem to need much more than the young Smith assumed. And their governments are not only large and complex, comprising thousands of agencies that administer millions of pages of rules and regulations; they are also democratic – and not just because they hold elections every so often. Why?
By the time he published The Wealth of Nations, at age 43, Smith had become the first complexity scientist. He understood that the economy was a complex system that needed to coordinate the work of thousands of people just to make things as simple as a meal or a suit.
But Smith also understood that while the economy was too intricate to be organized by anybody, it has the capacity to self-organize. It possesses an “invisible hand,” which operates through market prices to provide an information system that can be used to calculate whether using resources for a given purpose is worthwhile – that is, profitable.
Profit is an incentive system that leads firms and individuals to respond to the information provided by prices. And capital markets are a resource-mobilization system that provides money to those companies and projects that are expected to be profitable – that is, the ones that respond adequately to market prices.
But modern production requires many inputs that markets do not provide. And, as in the case of airlines, these inputs – rules, standards, certifications, infrastructure, schools and training centers, scientific labs, security services, among others – are deeply complementary to the ones that can be procured in markets. They interact in the most intricate ways with the activities that markets organize.
So here’s the question: Who controls the provision of the publicly provided inputs? The prime minister? The legislature? Which country’s top judges have read the millions of pages of legislation or considered how they complement or contradict each other, much less applied them to the myriad different activities that comprise the economy? Even a presidential executive cannot be fully aware of the things that are done or not done by the thousands of government agencies and how they affect each part of society.
This is an information-rich problem, and, like the social-coordination challenge that the market addresses, it does not allow for centralized control. What is needed is something like the invisible hand of the market: a mechanism for self-organization. Elections clearly are not enough, because they typically occur at two- or four-year intervals and collect very little information per voter.
Instead, successful political systems have had to create an alternative invisible hand – a system that decentralizes the power to identify problems, propose solutions, and monitor performance, such that decisions are made with much more information.
To take just one example, the United States’ federal government accounts for just 537 of the country’s roughly 500,000 elected positions. Clearly, there is much more going on elsewhere.
The US Congress has 100 senators with 40 aides each, and 435 representatives with 25 aides each. They are organized into 42 committees and 182 subcommittees, meaning that there are 224 parallel conversations going on. And this group of more than 15,000 people is not alone. Facing them are some 22,000 registered lobbyists, whose mission is (among other goals) to sit down with legislators and draft legislation.
This, together with a free press, is part of the structure that reads the millions of pages of legislation and monitors what government agencies do and do not do. It generates the information and the incentives to respond to it. It affects the allocation of budgetary resources. It is an open system in which anybody can create news or find a lobbyist to make his case, whether it is to save the whales or to eat them.
Without such a mechanism, the political system cannot provide the kind of environment that modern economies need. That is why all rich countries are democracies, and it is why some countries, like my own (Venezuela), are becoming poorer. Although some of these countries do hold elections, they tend to stumble at even the simplest of coordination problems. Lining up to vote is no guarantee that citizens will not also have to line up for toilet paper.”

Big data: are we making a big mistake?

Curated on Posted on by Stefaan Verhulst

Tim Harford in the Financial Times: “Cheerleaders for big data have made four exciting claims, each one reflected in the success of Google Flu Trends: that data analysis produces uncannily accurate results; that every single data point can be captured, making old statistical sampling techniques obsolete; that it is passé to fret about what causes what, because statistical correlation tells us what we need to know; and that scientific or statistical models aren’t needed because, to quote “The End of Theory”, a provocative essay published in Wired in 2008, “with enough data, the numbers speak for themselves”. Unfortunately, these four articles of faith are at best optimistic oversimplifications. At worst, according to David Spiegelhalter, Winton Professor of the Public Understanding of Risk at Cambridge university, they can be “complete bollocks. Absolute nonsense.”…
But big data do not solve the problem that has obsessed statisticians and scientists for centuries: the problem of insight, of inferring what is going on, and figuring out how we might intervene to change a system for the better.
“We have a new resource here,” says Professor David Hand of Imperial College London. “But nobody wants ‘data’. What they want are the answers.”
To use big data to produce such answers will require large strides in statistical methods.
“It’s the wild west right now,” says Patrick Wolfe of UCL. “People who are clever and driven will twist and turn and use every tool to get sense out of these data sets, and that’s cool. But we’re flying a little bit blind at the moment.”
Statisticians are scrambling to develop new methods to seize the opportunity of big data. Such new methods are essential but they will work by building on the old statistical lessons, not by ignoring them.
Recall big data’s four articles of faith. Uncanny accuracy is easy to overrate if we simply ignore false positives, as with Target’s pregnancy predictor. The claim that causation has been “knocked off its pedestal” is fine if we are making predictions in a stable environment but not if the world is changing (as with Flu Trends) or if we ourselves hope to change it. The promise that “N = All”, and therefore that sampling bias does not matter, is simply not true in most cases that count. As for the idea that “with enough data, the numbers speak for themselves” – that seems hopelessly naive in data sets where spurious patterns vastly outnumber genuine discoveries.
“Big data” has arrived, but big insights have not. The challenge now is to solve new problems and gain new answers – without making the same old statistical mistakes on a grander scale than ever.”

The data gold rush

Curated on Posted on by Stefaan Verhulst

Neelie KROES (European Commission):  “Nearly 200 years ago, the industrial revolution saw new networks take over. Not just a new form of transport, the railways connected industries, connected people, energised the economy, transformed society.
Now we stand facing a new industrial revolution: a digital one.
With cloud computing its new engine, big data its new fuel. Transporting the amazing innovations of the internet, and the internet of things. Running on broadband rails: fast, reliable, pervasive.
My dream is that Europe takes its full part. With European industry able to supply, European citizens and businesses able to benefit, European governments able and willing to support. But we must get all those components right.
What does it mean to say we’re in the big data era?
First, it means more data than ever at our disposal. Take all the information of humanity from the dawn of civilisation until 2003 – nowadays that is produced in just two days. We are also acting to have more and more of it become available as open data, for science, for experimentation, for new products and services.
Second, we have ever more ways – not just to collect that data – but to manage it, manipulate it, use it. That is the magic to find value amid the mass of data. The right infrastructure, the right networks, the right computing capacity and, last but not least, the right analysis methods and algorithms help us break through the mountains of rock to find the gold within.
Third, this is not just some niche product for tech-lovers. The impact and difference to people’s lives are huge: in so many fields.
Transforming healthcare, using data to develop new drugs, and save lives. Greener cities with fewer traffic jams, and smarter use of public money.
A business boost: like retailers who communicate smarter with customers, for more personalisation, more productivity, a better bottom line.
No wonder big data is growing 40% a year. No wonder data jobs grow fast. No wonder skills and profiles that didn’t exist a few years ago are now hot property: and we need them all, from data cleaner to data manager to data scientist.
This can make a difference to people’s lives. Wherever you sit in the data ecosystem – never forget that. Never forget that real impact and real potential.
Politicians are starting to get this. The EU’s Presidents and Prime Ministers have recognised the boost to productivity, innovation and better services from big data and cloud computing.
But those technologies need the right environment. We can’t go on struggling with poor quality broadband. With each country trying on its own. With infrastructure and research that are individual and ineffective, separate and subscale. With different laws and practices shackling and shattering the single market. We can’t go on like that.
Nor can we continue in an atmosphere of insecurity and mistrust.
Recent revelations show what is possible online. They show implications for privacy, security, and rights.
You can react in two ways. One is to throw up your hands and surrender. To give up and put big data in the box marked “too difficult”. To turn away from this opportunity, and turn your back on problems that need to be solved, from cancer to climate change. Or – even worse – to simply accept that Europe won’t figure on this mapbut will be reduced to importing the results and products of others.
Alternatively: you can decide that we are going to master big data – and master all its dependencies, requirements and implications, including cloud and other infrastructures, Internet of things technologies as well as privacy and security. And do it on our own terms.
And by the way – privacy and security safeguards do not just have to be about protecting and limiting. Data generates value, and unlocks the door to new opportunities: you don’t need to “protect” people from their own assets. What you need is to empower people, give them control, give them a fair share of that value. Give them rights over their data – and responsibilities too, and the digital tools to exercise them. And ensure that the networks and systems they use are affordable, flexible, resilient, trustworthy, secure.
One thing is clear: the answer to greater security is not just to build walls. Many millennia ago, the Greek people realised that. They realised that you can build walls as high and as strong as you like – it won’t make a difference, not without the right awareness, the right risk management, the right security, at every link in the chain. If only the Trojans had realised that too! The same is true in the digital age: keep our data locked up in Europe, engage in an impossible dream of isolation, and we lose an opportunity; without gaining any security.
But master all these areas, and we would truly have mastered big data. Then we would have showed technology can take account of democratic values; and that a dynamic democracy can cope with technology. Then we would have a boost to benefit every European.
So let’s turn this asset into gold. With the infrastructure to capture and process. Cloud capability that is efficient, affordable, on-demand. Let’s tackle the obstacles, from standards and certification, trust and security, to ownership and copyright. With the right skills, so our workforce can seize this opportunity. With new partnerships, getting all the right players together. And investing in research and innovation. Over the next two years, we are putting 90 million euros on the table for big data and 125 million for the cloud.
I want to respond to this economic imperative. And I want to respond to the call of the European Council – looking at all the aspects relevant to tomorrow’s digital economy.
You can help us build this future. All of you. Helping to bring about the digital data-driven economy of the future. Expanding and depening the ecosystem around data. New players, new intermediaries, new solutions, new jobs, new growth….”

Coordinating the Commons: Diversity & Dynamics in Open Collaborations

Curated on Posted on by Stefaan Verhulst

Dissertation by Jonathan T. Morgan: “The success of Wikipedia demonstrates that open collaboration can be an effective model for organizing geographically-distributed volunteers to perform complex, sustained work at a massive scale. However, Wikipedia’s history also demonstrates some of the challenges that large, long-term open collaborations face: the core community of Wikipedia editors—the volunteers who contribute most of the encyclopedia’s content and ensure that articles are correct and consistent — has been gradually shrinking since 2007, in part because Wikipedia’s social climate has become increasingly inhospitable for newcomers, female editors, and editors from other underrepresented demographics. Previous research studies of change over time within other work contexts, such as corporations, suggests that incremental processes such as bureaucratic formalization can make organizations more rule-bound and less adaptable — in effect, less open— as they grow and age. There has been little research on how open collaborations like Wikipedia change over time, and on the impact of those changes on the social dynamics of the collaborating community and the way community members prioritize and perform work. Learning from Wikipedia’s successes and failures can help researchers and designers understand how to support open collaborations in other domains — such as Free/Libre Open Source Software, Citizen Science, and Citizen Journalism.

In this dissertation, I examine the role of openness, and the potential antecedents and consequences of formalization, within Wikipedia through an analysis of three distinct but interrelated social structures: community-created rules within the Wikipedia policy environment, coordination work and group dynamics within self-organized open teams called WikiProjects, and the socialization mechanisms that Wikipedia editors use to teach new community members how to participate.To inquire further, I have designed a new editor peer support space, the Wikipedia Teahouse, based on the findings from my empirical studies. The Teahouse is a volunteer-driven project that provides a welcoming and engaging environment in which new editors can learn how to be productive members of the Wikipedia community, with the goal of increasing the number and diversity of newcomers who go on to make substantial contributions to Wikipedia …”

Overcoming 'Tragedies of the Commons' with a Self-Regulating, Participatory Market Society

Curated on Posted on by Stefaan Verhulst

Paper by Dirk Helbing; “Our society is fundamentally changing. These days, almost nothing works without a computer chip. Processing power doubles every 18 months and will exceed the capabilities of human brains in about ten years from now. Some time ago, IBM’s Big Blue computer already beat the best chess player. Meanwhile, computers perform about 70 percent of all financial transactions, and IBM’s Watson advises customers better than human telephone hotlines. Will computers and robots soon replace skilled labor? In many European countries, unemployment is reaching historical heights. The forthcoming economic and social impact of future information and communication technologies (ICT) will be huge – probably more significant than that caused by the steam engine, or by nano- or biotechnology.
The storage capacity for data is growing even faster than computational capacity. Within just a year we will soon generate more data than in the entire history of humankind. The “Internet of Things” will network trillions of sensors. Unimaginable amounts of data will be collected. Big Data is already being praised as the “oil of the 21st century”. What opportunities and risks does this create for our society, economy, and environment?”

Three ways digital leaders can operate successfully in local government

Curated on Posted on by Stefaan Verhulst

in The Guardian: “The landscape of digital is constantly changing and being redefined with every new development, technology breakthrough, success and failure. We need digital public sector leaders who can properly navigate this environment, and follow these three guidelines.
1. Champion open data
We need leaders who can ensure that information and data is open by default, and secure when absolutely required. Too often councils commission digital programmes only to find the data generated does not easily integrate with other systems, or that data is not council-owned and can only be accessed at further cost.
2. Don’t get distracted by flashy products
Leaders must adopt an agnostic approach to technology, and not get seduced by the ever-increasing number of digital technologies and lose sight of real user and business needs.
3. Learn from research
Tales of misplaced IT investments plague the public sector, and senior leaders are understandably hesitant when considering future investments. To avoid causing even more disruption, we should learn from research findings such as those of the New Local Government Network’s recent digital roundtables on what works.
Making the decision to properly invest in digital leadership will not just improve decision making about digital solutions and strategies. It will also bring in the knowledge needed to navigate the complex security requirements that surround public-sector IT. And it will ensure that practices honed in the digital environment become embedded in the council more generally.
In Devon, for example, we are making sure all the services we offer online are based on the experience and behaviour of users. This has led service teams to refocus on the needs of citizens rather than those of the organisation. And our experiences of future proofing, agility and responsiveness are informing service design throughout the council.
What’s holding us back?
Across local government there is still a fragmented approach to collaboration. In central government, the Government Digital Service is charged with providing the right environment for change across all government departments. However, in local government, digital leaders often work alone without a unifying strategy across the sector. It is important to understand and recognise that the Government Digital Service is more than just a team pushing and promoting digital in central government: they are the future of central government, attempting to transform everything.
Initiatives such as LocalGov Digital, (O2’s Local Government Digital Fund), Forum (the DCLG’s local digital alliance) and the Guardian’s many public sector forums and networks are all helping to push forward debate, spread good practice and build a sense of urgent optimism around the local government digital agenda. But at present there is no equivalent to the unified force of the Government Digital Service.”

Open Data (Updated and Expanded)

Curated on Posted on by Andrew Young

As part of an ongoing effort to build a knowledge base for the field of opening governance by organizing and disseminating its learnings, the GovLab Selected Readings series provides an annotated and curated collection of recommended works on key opening governance topics. We start our series with a focus on Open Data. To suggest additional readings on this or any other topic, please email biblio@thegovlab.org.

Data and its uses for GovernanceOpen data refers to data that is publicly available for anyone to use and which is licensed in a way that allows for its re-use. The common requirement that open data be machine-readable not only means that data is distributed via the Internet in a digitized form, but can also be processed by computers through automation, ensuring both wide dissemination and ease of re-use. Much of the focus of the open data advocacy community is on government data and government-supported research data. For example, in May 2013, the US Open Data Policy defined open data as publicly available data structured in a way that enables the data to be fully discoverable and usable by end users, and consistent with a number of principles focused on availability, accessibility and reusability.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)
Fox, Mark S. “City Data: Big, Open and Linked.” Working Paper, Enterprise Integration Laboratory (2013). http://bit.ly/1bFr7oL.

  • This paper examines concepts that underlie Big City Data using data from multiple cities as examples. It begins by explaining the concepts of Open, Unified, Linked, and Grounded data, which are central to the Semantic Web. Fox then explore Big Data as an extension of Data Analytics, and provide case examples of good data analytics in cities.
  • Fox concludes that we can develop the tools that will enable anyone to analyze data, both big and small, by adopting the principles of the Semantic Web:
    • Data being openly available over the internet,
    • Data being unifiable using common vocabularies,
    • Data being linkable using International Resource Identifiers,
    • Data being accessible using a common data structure, namely triples,
    • Data being semantically grounded using Ontologies.

Foulonneau, Muriel, Sébastien Martin, and Slim Turki. “How Open Data Are Turned into Services?” In Exploring Services Science, edited by Mehdi Snene and Michel Leonard, 31–39. Lecture Notes in Business Information Processing 169. Springer International Publishing, 2014. http://bit.ly/1fltUmR.

  • In this chapter, the authors argue that, considering the important role the development of new services plays as a motivation for open data policies, the impact of new services created through open data should play a more central role in evaluating the success of open data initiatives.
  • Foulonneau, Martin and Turki argue that the following metrics should be considered when evaluating the success of open data initiatives: “the usage, audience, and uniqueness of the services, according to the changes it has entailed in the public institutions that have open their data…the business opportunity it has created, the citizen perception of the city…the modification to particular markets it has entailed…the sustainability of the services created, or even the new dialog created with citizens.”

Goldstein, Brett, and Lauren Dyson. Beyond Transparency: Open Data and the Future of Civic Innovation. 1 edition. (Code for America Press: 2013). http://bit.ly/15OAxgF

  • This “cross-disciplinary survey of the open data landscape” features stories from practitioners in the open data space — including Michael Flowers, Brett Goldstein, Emer Colmeman and many others — discussing what they’ve accomplished with open civic data. The book “seeks to move beyond the rhetoric of transparency for transparency’s sake and towards action and problem solving.”
  • The book’s editors seek to accomplish the following objectives:
    • Help local governments learn how to start an open data program
    • Spark discussion on where open data will go next
    • Help community members outside of government better engage with the process of governance
    • Lend a voice to many aspects of the open data community.
  • The book is broken into five sections: Opening Government Data, Building on Open Data, Understanding Open Data, Driving Decisions with Data and Looking Ahead.

Granickas, Karolis. “Understanding the Impact of Releasing and Re-using Open Government Data.” European Public Sector Information Platform, ePSIplatform Topic Report No. 2013/08, (2013). http://bit.ly/GU0Nx4.

  • This paper examines the impact of open government data by exploring the latest research in the field, with an eye toward enabling  an environment for open data, as well as identifying the benefits of open government data and its political, social, and economic impacts.
  • Granickas concludes that to maximize the benefits of open government data: a) further research is required that structure and measure potential benefits of open government data; b) “government should pay more attention to creating feedback mechanisms between policy implementers, data providers and data-re-users”; c) “finding a balance between demand and supply requires mechanisms of shaping demand from data re-users and also demonstration of data inventory that governments possess”; and lastly, d) “open data policies require regular monitoring.”

Gurin, Joel. Open Data Now: The Secret to Hot Startups, Smart Investing, Savvy Marketing, and Fast Innovation, (New York: McGraw-Hill, 2014). http://amzn.to/1flubWR.

  • In this book, GovLab Senior Advisor and Open Data 500 director Joel Gurin explores the broad realized and potential benefit of Open Data, and how, “unlike Big Data, Open Data is transparent, accessible, and reusable in ways that give it the power to transform business, government, and society.”
  • The book provides “an essential guide to understanding all kinds of open databases – business, government, science, technology, retail, social media, and more – and using those resources to your best advantage.”
  • In particular, Gurin discusses a number of applications of Open Data with very real potential benefits:
    • “Hot Startups: turn government data into profitable ventures;
    • Savvy Marketing: understanding how reputational data drives your brand;
    • Data-Driven Investing: apply new tools for business analysis;
    • Consumer Information: connect with your customers using smart disclosure;
    • Green Business: use data to bet on sustainable companies;
    • Fast R&D: turn the online world into your research lab;
    • New Opportunities: explore open fields for new businesses.”

Jetzek, Thorhildur, Michel Avital, and Niels Bjørn-Andersen. “Generating Value from Open Government Data.” Thirty Fourth International Conference on Information Systems, 5. General IS Topics 2013. http://bit.ly/1gCbQqL.

  • In this paper, the authors “developed a conceptual model portraying how data as a resource can be transformed to value.”
  • Jetzek, Avital and Bjørn-Andersen propose a conceptual model featuring four Enabling Factors (openness, resource governance, capabilities and technical connectivity) acting on four Value Generating Mechanisms (efficiency, innovation, transparency and participation) leading to the impacts of Economic and Social Value.
  • The authors argue that their research supports that “all four of the identified mechanisms positively influence value, reflected in the level of education, health and wellbeing, as well as the monetary value of GDP and environmental factors.”

Kassen, Maxat. “A promising phenomenon of open data: A case study of the Chicago open data project.” Government Information Quarterly (2013). http://bit.ly/1ewIZnk.

  • This paper uses the Chicago open data project to explore the “empowering potential of an open data phenomenon at the local level as a platform useful for promotion of civic engagement projects and provide a framework for future research and hypothesis testing.”
  • Kassen argues that “open data-driven projects offer a new platform for proactive civic engagement” wherein governments can harness “the collective wisdom of the local communities, their knowledge and visions of the local challenges, governments could react and meet citizens’ needs in a more productive and cost-efficient manner.”
  • The paper highlights the need for independent IT developers to network in order for this trend to continue, as well as the importance of the private sector in “overall diffusion of the open data concept.”

Keen, Justin, Radu Calinescu, Richard Paige, John Rooksby. “Big data + politics = open data: The case of health care data in England.” Policy and Internet 5 (2), (2013): 228–243. http://bit.ly/1i231WS.

  • This paper examines the assumptions regarding open datasets, technological infrastructure and access, using healthcare systems as a case study.
  • The authors specifically address two assumptions surrounding enthusiasm about Big Data in healthcare: the assumption that healthcare datasets and technological infrastructure are up to task, and the assumption of access to this data from outside the healthcare system.
  • By using the National Health Service in England as an example, the authors identify data, technology, and information governance challenges. They argue that “public acceptability of third party access to detailed health care datasets is, at best, unclear,” and that the prospects of Open Data depend on Open Data policies, which are inherently political, and the government’s assertion of property rights over large datasets. Thus, they argue that the “success or failure of Open Data in the NHS may turn on the question of trust in institutions.”

Kulk, Stefan and Bastiaan Van Loenen. “Brave New Open Data World?” International Journal of Spatial Data Infrastructures Research, May 14, 2012. http://bit.ly/15OAUYR.

  • This paper examines the evolving tension between the open data movement and the European Union’s privacy regulations, especially the Data Protection Directive.
  • The authors argue, “Technological developments and the increasing amount of publicly available data are…blurring the lines between non-personal and personal data. Open data may not seem to be personal data on first glance especially when it is anonymised or aggregated. However, it may become personal by combining it with other publicly available data or when it is de-anonymised.”

Kundra, Vivek. “Digital Fuel of the 21st Century: Innovation through Open Data and the Network Effect.” Joan Shorenstein Center on the Press, Politics and Public Policy, Harvard College: Discussion Paper Series, January 2012, http://hvrd.me/1fIwsjR.

  • In this paper, Vivek Kundra, the first Chief Information Officer of the United States, explores the growing impact of open data, and argues that, “In the information economy, data is power and we face a choice between democratizing it and holding on to it for an asymmetrical advantage.”
  • Kundra offers four specific recommendations to maximize the impact of open data: Citizens and NGOs must demand open data in order to fight government corruption, improve accountability and government services; Governments must enact legislation to change the default setting of government to open, transparent and participatory; The press must harness the power of the network effect through strategic partnerships and crowdsourcing to cut costs and provide better insights; and Venture capitalists should invest in startups focused on building companies based on public sector data.

Noveck, Beth Simone and Daniel L. Goroff. “Information for Impact: Liberating Nonprofit Sector Data.” The Aspen Institute Philanthropy & Social Innovation Publication Number 13-004. 2013. http://bit.ly/WDxd7p.

  • This report is focused on “obtaining better, more usable data about the nonprofit sector,” which encompasses, as of 2010, “1.5 million tax-exempt organizations in the United States with $1.51 trillion in revenues.”
  • Toward that goal, the authors propose liberating data from the Form 990, an Internal Revenue Service form that “gathers and publishes a large amount of information about tax-exempt organizations,” including information related to “governance, investments, and other factors not directly related to an organization’s tax calculations or qualifications for tax exemption.”
  • The authors recommend a two-track strategy: “Pursuing the longer-term goal of legislation that would mandate electronic filing to create open 990 data, and pursuing a shorter-term strategy of developing a third party platform that can demonstrate benefits more immediately.”

Robinson, David G., Harlan Yu, William P. Zeller, and Edward W. Felten, “Government Data and the Invisible Hand.” Yale Journal of Law & Technology 11 (2009), http://bit.ly/1c2aDLr.

  • This paper proposes a new approach to online government data that “leverages both the American tradition of entrepreneurial self-reliance and the remarkable low-cost flexibility of contemporary digital technology.”
  • “In order for public data to benefit from the same innovation and dynamism that characterize private parties’ use of the Internet, the federal government must reimagine its role as an information provider. Rather than struggling, as it currently does, to design sites that meet each end-user need, it should focus on creating a simple, reliable and publicly accessible infrastructure that ‘exposes’ the underlying data.”
Ubaldi, Barbara. “Open Government Data: Towards Empirical Analysis of Open Government Data Initiatives.” OECD Working Papers on Public Governance. Paris: Organisation for Economic Co-operation and Development, May 27, 2013. http://bit.ly/15OB6qP.

  • This working paper from the OECD seeks to provide an all-encompassing look at the principles, concepts and criteria framing open government data (OGD) initiatives.
  • Ubaldi also analyzes a variety of challenges to implementing OGD initiatives, including policy, technical, economic and financial, organizational, cultural and legal impediments.
  • The paper also proposes a methodological framework for evaluating OGD Initiatives in OECD countries, with the intention of eventually “developing a common set of metrics to consistently assess impact and value creation within and across countries.”

Worthy, Ben. “David Cameron’s Transparency Revolution? The Impact of Open Data in the UK.” SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, November 29, 2013. http://bit.ly/NIrN6y.

  • In this article, Worthy “examines the impact of the UK Government’s Transparency agenda, focusing on the publication of spending data at local government level. It measures the democratic impact in terms of creating transparency and accountability, public participation and everyday information.”
  • Worthy’s findings, based on surveys of local authorities, interviews and FOI requests, are disappointing. He finds that:
    • Open spending data has led to some government accountability, but largely from those already monitoring government, not regular citizens.
    • Open Data has not led to increased participation, “as it lacks the narrative or accountability instruments to fully bring such effects.”
    • It has also not “created a new stream of information to underpin citizen choice, though new innovations offer this possibility. The evidence points to third party innovations as the key.
  • Despite these initial findings, “Interviewees pointed out that Open Data holds tremendous opportunities for policy-making. Joined up data could significantly alter how policy is made and resources targeted. From small scale issues e.g. saving money through prescriptions to targeting homelessness or health resources, it can have a transformative impact. “

Zuiderwijk, Anneke, Marijn Janssen, Sunil Choenni, Ronald Meijer and Roexsana Sheikh Alibaks. “Socio-technical Impediments of Open Data.” Electronic Journal of e-Government 10, no. 2 (2012). http://bit.ly/17yf4pM.

  • This paper to seeks to identify the socio-technical impediments to open data impact based on a review of the open data literature, as well as workshops and interviews.
  • The authors discovered 118 impediments across ten categories: 1) availability and access; 2) find-ability; 3) usability; 4) understandability; 5) quality; 6) linking and combining data; 7) comparability and compatibility; 8) metadata; 9) interaction with the data provider; and 10) opening and uploading.

Zuiderwijk, Anneke and Marijn Janssen. “Open Data Policies, Their Implementation and Impact: A Framework for Comparison.” Government Information Quarterly 31, no. 1 (January 2014): 17–29. http://bit.ly/1bQVmYT.

  • In this article, Zuiderwijk and Janssen argue that “currently there is a multiplicity of open data policies at various levels of government, whereas very little systematic and structured research [being] done on the issues that are covered by open data policies, their intent and actual impact.”
  • With this evaluation deficit in mind, the authors propose a new framework for comparing open data policies at different government levels using the following elements for comparison:
    • Policy environment and context, such as level of government organization and policy objectives;
    • Policy content (input), such as types of data not publicized and technical standards;
    • Performance indicators (output), such as benefits and risks of publicized data; and
    • Public values (impact).

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