Fifteen open data insights

Curated on Posted on by Stefaan Verhulst

Tim Davies from ODRN: “…below are the 15 points from the three-page briefing version, and you can find a full write-up of these points for download. You can also find reports from all the individual project partners, including a collection of quick-read research posters over on the Open Data Research Network website.

15 insights into open data supply, use and impacts

(1) There are many gaps to overcome before open data availability, can lead to widespread effective use and impact. Open data can lead to change through a ‘domino effect’, or by creating ripples of change that gradually spread out. However, often many of the key ‘domino pieces’ are missing, and local political contexts limit the reach of ripples. Poor data quality, low connectivity, scarce technical skills, weak legal frameworks and political barriers may all prevent open data triggering sustainable change. Attentiveness to all the components of open data impact is needed when designing interventions.
(2) There is a frequent mismatch between open data supply and demand in developing countries. Counting datasets is a poor way of assessing the quality of an open data initiative. The datasets published on portals are often the datasets that are easiest to publish, not the datasets most in demand. Politically sensitive datasets are particularly unlikely to be published without civil society pressure. Sometimes the gap is on the demand side – as potential open data users often do not articulate demands for key datasets.
(3) Open data initiatives can create new spaces for civil society to pursue government accountability and effectiveness. The conversation around transparency and accountability that ideas of open data can support is as important as the datasets in some developing countries.
(4) Working on open data projects can change how government creates, prepares and uses its own data. The motivations behind an open data initiative shape how government uses the data itself. Civil society and entrepreneurs interacting with government through open data projects can help shape government data practices. This makes it important to consider which intermediaries gain insider roles shaping data supply.
(5) Intermediaries are vital to both the supply and the use of open data. Not all data needed for governance in developing countries comes from government. Intermediaries can create data, articulate demands for data, and help translate open data visions from political leaders into effective implementations. Traditional local intermediaries are an important source of information, in particular because they are trusted parties.
(6) Digital divides create data divides in both the supply and use of data. In some developing countries key data is not digitised, or a lack of technical staff has left data management patchy and inconsistent. Where Internet access is scarce, few citizens can have direct access to data or services built with it. Full access is needed for full empowerment, but offline intermediaries, including journalists and community radio stations, also play a vital role in bridging the gaps between data and citizens.
(7) Where information is already available and used, the shift to open data involves data evolution rather than data revolution. Many NGOs and intermediaries already access the information which is now becoming available as data. Capacity building should start from existing information and data practices in organisations, and should look for the step-by-step gains to be made from a data-driven approach.
(8) Officials’ fears about the integrity of data are a barrier to more machine-readable data being made available. The publication of data as PDF or in scanned copies is often down to a misunderstanding of how open data works. Only copies can be changed, and originals can be kept authoritative. Helping officials understand this may help increase the supply of data.
(9) Very few datasets are clearly openly licensed, and there is low understanding of what open licenses entail. There are mixed opinions on the importance of a focus on licensing in different contexts. Clear licenses are important to building a global commons of interoperable data, but may be less relevant to particular uses of data on the ground. In many countries wider conversation about licensing are yet to take place.
(10) Privacy issues are not on the radar of most developing country open data projects, although commercial confidentiality does arise as a reason preventing greater data transparency. Much state held data is collected either from citizens or from companies. Few countries in the ODDC study have weak or absent privacy laws and frameworks, yet participants in the studies raised few personal privacy considerations. By contrast, a lack of clarity, and officials’ concerns, about potential breaches of commercial confidentiality when sharing data gathered from firms was a barrier to opening data.
(11) There is more to open data than policies and portals. Whilst central open data portals act as a visible symbol of open data initiatives, a focus on portal building can distract attention from wider reforms. Open data elements can also be built on existing data sharing practices, and data made available through the locations where citizens, NGOs are businesses already go to access information.
(12) Open data advocacy should be aware of, and build upon, existing policy foundations in specific countries and sectors. Sectoral transparency policies for local government, budget and energy industry regulation, amongst others, could all have open data requirements and standards attached, drawing on existing mechanisms to secure sustainable supplies of relevant open data in developing countries. In addition, open data conversations could help make existing data collection and disclosure requirements fit better with the information and data demands of citizens.
(13) Open data is not just a central government issue: local government data, city data, and data from the judicial and legislative branches are all important. Many open data projects focus on the national level, and only on the executive branch. However, local government is closer to citizens, urban areas bring together many of the key ingredients for successful open data initiatives, and transparency in other branches of government is important to secure citizens democratic rights.
(14) Flexibility is needed in the application of definitions of open data to allow locally relevant and effective open data debates and advocacy to emerge. Open data is made up of various elements, including proactive publication, machine-readability and permissions to re-use. Countries at different stages of open data development may choose to focus on one or more of these, but recognising that adopting all elements at once could hinder progress. It is important to find ways to both define open data clearly, and to avoid a reductive debate that does not recognise progressive steps towards greater openness.
(15) There are many different models for an open data initiative: including top-down, bottom-up and sector-specific. Initiatives may also be state-led, civil society-led and entrepreneur-led in their goals and how they are implemented – with consequences for the resources and models required to make them sustainable. There is no one-size-fits-all approach to open data. More experimentation, evaluation and shared learning on the components, partners and processes for putting open data ideas into practice must be a priority for all who want to see a world where open-by-default data drives real social, political and economic change.
You can read more about each of these points in the full report.”

Using predictive analytics and rapid-cycle evaluation to improve program design and results

Curated on Posted on by Stefaan Verhulst

An interview with Scott Cody, Vice President, Mathematica Policy Research and GovInnovator Blog  (Podcast: Play in new window | Download): “What are predictive analytics and rapid-cycle evaluation and how can public agencies and programs use them to improve program delivery and outcomes? To explore these questions, we’re joined by Scott Cody. He’s a Vice President of Mathematica Policy Research and the co-author, with Andrew Asher, of a recent paper “Smarter, Better, Faster: The Potential for Predictive Analytics and Rapid-Cycle Evaluation to Improve Program Development and Outcomes,” published by the Hamilton Project at the Brookings Institution.”

Selected Readings on Economic Impact of Open Data

Curated on Posted on by admin

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of open data was originally published in 2014.

Open data is publicly available data – often released by governments, scientists, and occasionally private companies – that is made available for anyone to use, in a machine-readable format, free of charge. Considerable attention has been devoted to the economic potential of open data for businesses and other organizations, and it is now widely accepted that open data plays an important role in spurring innovation, growth, and job creation. From new business models to innovation in local governance, open data is being quickly adopted as a valuable resource at many levels.

Measuring and analyzing the economic impact of open data in a systematic way is challenging, and governments as well as other providers of open data seek to provide access to the data in a standardized way. As governmental transparency increases and open data changes business models and activities in many economic sectors, it is important to understand best practices for releasing and using non-proprietary, public information. Costs, social challenges, and technical barriers also influence the economic impact of open data.

These selected readings are intended as a first step in the direction of answering the question of if we can and how we consider if opening data spurs economic impact.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Bonina, Carla. New Business Models and the Values of Open Data: Definitions, Challenges, and Opportunities. NEMODE 3K – Small Grants Call 2013. http://bit.ly/1xGf9oe

  • In this paper, Dr. Carla Bonina provides an introduction to open data and open data business models, evaluating their potential economic value and identifying future challenges for the effectiveness of open data, such as personal data and privacy, the emerging data divide, and the costs of collecting, producing and releasing open (government) data.

Carpenter, John and Phil Watts. Assessing the Value of OS OpenData™ to the Economy of Great Britain – Synopsis. June 2013. Accessed July 25, 2014. http://bit.ly/1rTLVUE

  • John Carpenter and Phil Watts of Ordnance Survey undertook a study to examine the economic impact of open data to the economy of Great Britain. Using a variety of methods such as case studies, interviews, downlad analysis, adoption rates, impact calculation, and CGE modeling, the authors estimates that the OS OpenData initiative will deliver a net of increase in GDP of £13 – 28.5 million for Great Britain in 2013.

Capgemini Consulting. The Open Data Economy: Unlocking Economic Value by Opening Government and Public Data. Capgemini Consulting. Accessed July 24, 2014. http://bit.ly/1n7MR02

  • This report explores how governments are leveraging open data for economic benefits. Through using a compariative approach, the authors study important open data from organizational, technological, social and political perspectives. The study highlights the potential of open data to drive profit through increasing the effectiveness of benchmarking and other data-driven business strategies.

Deloitte. Open Growth: Stimulating Demand for Open Data in the UK. Deloitte Analytics. December 2012. Accessed July 24, 2014. http://bit.ly/1oeFhks

  • This early paper on open data by Deloitte uses case studies and statistical analysis on open government data to create models of businesses using open data. They also review the market supply and demand of open government data in emerging sectors of the economy.

Gruen, Nicholas, John Houghton and Richard Tooth. Open for Business: How Open Data Can Help Achieve the G20 Growth Target.  Accessed July 24, 2014, http://bit.ly/UOmBRe

  • This report highlights the potential economic value of the open data agenda in Australia and the G20. The report provides an initial literature review on the economic value of open data, as well as a asset of case studies on the economic value of open data, and a set of recommendations for how open data can help the G20 and Australia achieve target objectives in the areas of trade, finance, fiscal and monetary policy, anti-corruption, employment, energy, and infrastructure.

Heusser, Felipe I. Understanding Open Government Data and Addressing Its Impact (draft version). World Wide Web Foundation. http://bit.ly/1o9Egym

  • The World Wide Web Foundation, in collaboration with IDRC has begun a research network to explore the impacts of open data in developing countries. In addition to the Web Foundation and IDRC, the network includes the Berkman Center for Internet and Society at Harvard, the Open Development Technology Alliance and Practical Participation.

Howard, Alex. San Francisco Looks to Tap Into the Open Data Economy. O’Reilly Radar: Insight, Analysis, and Reach about Emerging Technologies.  October 19, 2012.  Accessed July 24, 2014. http://oreil.ly/1qNRt3h

  • Alex Howard points to San Francisco as one of the first municipalities in the United States to embrace an open data platform.  He outlines how open data has driven innovation in local governance.  Moreover, he discusses the potential impact of open data on job creation and government technology infrastructure in the City and County of San Francisco.

Huijboom, Noor and Tijs Van den Broek. Open Data: An International Comparison of Strategies. European Journal of ePractice. March 2011. Accessed July 24, 2014.  http://bit.ly/1AE24jq

  • This article examines five countries and their open data strategies, identifying key features, main barriers, and drivers of progress for of open data programs. The authors outline the key challenges facing European, and other national open data policies, highlighting the emerging role open data initiatives are playing in political and administrative agendas around the world.

Manyika, J., Michael Chui, Diana Farrell, Steve Van Kuiken, Peter Groves, and Elizabeth Almasi Doshi. Open Data: Unlocking Innovation and Performance with Liquid Innovation. McKinsey Global Institute. October 2013. Accessed July 24, 2014.  http://bit.ly/1lgDX0v

  • This research focuses on quantifying the potential value of open data in seven “domains” in the global economy: education, transportation, consumer products, electricity, oil and gas, health care, and consumer finance.

Moore, Alida. Congressional Transparency Caucus: How Open Data Creates Jobs. April 2, 2014. Accessed July 30, 2014. Socrata. http://bit.ly/1n7OJpp

  • Socrata provides a summary of the March 24th briefing of the Congressional Transparency Caucus on the need to increase government transparency through adopting open data initiatives. They include key takeaways from the panel discussion, as well as their role in making open data available for businesses.

Stott, Andrew. Open Data for Economic Growth. The World Bank. June 25, 2014. Accessed July 24, 2014. http://bit.ly/1n7PRJF

  • In this report, The World Bank examines the evidence for the economic potential of open data, holding that the economic potential is quite large, despite a variation in the published estimates, and difficulties assessing its potential methodologically. They provide five archetypes of businesses using open data, and provides recommendations for governments trying to maximize economic growth from open data.

How to harness the wisdom of crowds to improve public service delivery and policymaking

Curated on Posted on by Stefaan Verhulst

Eddie Copeland in PolicyBytes: “…In summary, government has used technology to streamline transactions and better understand the public’s opinions. Yet it has failed to use it to radically change the way it works. Have public services been reinvented? Is government smaller and leaner? Have citizens, businesses and civic groups been offered the chance to take part in the work of government and improve their own communities? On all counts the answer is unequivocally, no. What is needed, therefore, is a means to enable citizens to provide data to government to inform policymaking and to improve – or even help deliver – public services. What is needed is a Government Data Marketplace.

Government Data Marketplace

A Government Data Marketplace (GDM) would be a website that brought together public sector bodies that needed data, with individuals, businesses and other organisations that could provide it. Imagine an open data portal in reverse: instead of government publishing its own datasets to be used by citizens and businesses, it would instead publish its data needs and invite citizens, businesses or community groups to provide that data (for free or in return for payment). Just as open data portals aim to provide datasets in standard, machine-readable formats, GDM would operate according to strict open standards, and provide a consistent and automated way to deliver data to government through APIs.
How would it work? Imagine a local council that wished to know where instances of graffiti occurred within its borough. The council would create an account on GDM and publish a new request, outlining the data it required (not dissimilar to someone posting a job on a site like Freelancer). Citizens, businesses and other organisations would be able to view that request on GDM and bid to offer the service. For example, an app-development company could offer to build an app that would enable citizens to photograph and locate instances of graffiti in the borough. The app would be able to upload the data to GDM. The council could connect its own IT system to GDM to pass the data to their own database.
Importantly, the app-development company would specify via GDM how much it would charge to provide the data. Other companies and organisations could offer competing bids for delivering the same – or an even better service – at different prices. Supportive local civic hacker groups could even offer to provide the data for free. Either way, the council would get the data it needed without having to collect it for itself, whilst also ensuring it paid the best price from a number of competing providers.
Since GDM would be a public marketplace, other local authorities would be able to see that a particular company had designed a graffiti-reporting solution for one council, and could ask for the same data to be collected in their own boroughs. This would be quick and easy for the developer, as instead of having to create a bespoke solution to work with each council’s IT system, they could connect to all of them using one common interface via GDM. That would good for the company, as they could sell to a much larger market (the same solution would work for one council or all), and good for the councils, as they would benefit from cheaper prices generated from economies of scale. And since GDM would use open standards, if a council was unhappy with the data provided by one supplier, it could simply look to another company to provide the same information.
What would be the advantages of such a system? Firstly, innovation. GDM would free government from having to worry about what software it needed, and instead allow it to focus on the data it required to provide a service. To be clear: councils themselves do not need a graffiti app – they need data on where graffiti is. By focusing attention on its data needs, the public sector could let the market innovate to find the best solutions for providing it. That might be via an app, perhaps via a website, social media, or Internet of Things sensors, or maybe even using a completely new service that collected information in a radically different way. It will not matter – the right information would be provided in a common format via GDM.
Secondly, the potential cost savings of this approach would be many and considerable. At the very least, by creating a marketplace, the public sector would be able to source data at a competitive price. If several public sector bodies needed the same service via GDM, companies providing that data would be able to offer much cheaper prices for all, as instead of having to deal with hundreds of different organisations (and different interfaces) they could create one solution that worked for all of them. As prices became cheaper for standard solutions, this would in turn encourage more public sector bodies to converge on common ways of working, driving down costs still further. Yet these savings would be dwarfed by those possible if GDM could be used to source data that public sectors bodies currently have to manually collect themselves. Imagine if instead of having teams of inspectors to locate instances X, Y or Z, it could instead source the same data from citizens via GDM?
There would no limit to the potential applications to which GDM could be put by central and local government and other public sector bodies: for graffiti, traffic levels, environmental issues, education or welfare. It could be used to crowdsource facts, figures, images, map coordinates, text – anything that can be collected as data. Government could request information on areas on which it previously had none, helping them to assign their finite resources and money in a much more targeted way. New York City’s Mayor’s Office of Data Analytics has demonstrated that up to 500% increases in the efficiency of providing some public services can be achieved, if only the right data is available.
For the private sector, GDM would stimulate the growth of innovative new companies offering community data, and make it easier for them to sell data solutions across the whole of the public sector. They could pioneer in new data methods, and potentially even take over the provision of entire services which the public sector currently has to provide itself. For citizens, it would offer a means to genuinely get involved in solving issues that matter to their local communities, either by using apps made by businesses, or working to provide the data themselves.
And what about the benefits for policymaking? It is important to acknowledge that the idea of harnessing the wisdom of crowds for policymaking is currently experimental. In the case of Policy Futures Markets, some applications have also been considered to be highly controversial. So which methods would be most effective? What would they look like? In what policy domains would they provide most value? The simple fact is that we do not know. What is certain, however, is that innovation in open policymaking and crowdsourcing ideas will never be achieved until a platform is available that allows such ideas to be tried and tested. GDM could be that platform.
Public sector bodies could experiment with asking citizens for information or answers to particular, fact-based questions, or even for predictions on future outcomes, to help inform their policymaking activities. The market could then innovate to develop solutions to source that data from citizens, using the many different models for harnessing the wisdom of crowds. The effectiveness of those initiatives could then be judged, and the techniques honed. In the worst case scenario that it did not work, money would not have been wasted on building the wrong platform – GDM would continue to have value in providing data for public service needs as described above….”

Crowdsourcing Ideas to Accelerate Economic Growth and Prosperity through a Strategy for American Innovation

Curated on Posted on by Stefaan Verhulst

Jason Miller and Tom Kalil at the White House Blog: “America’s future economic growth and international competitiveness depend crucially on our capacity to innovate. Creating the jobs and industries of the future will require making the right investments to unleash the unmatched creativity and imagination of the American people.
We want to gather bold ideas for how we as a nation can build on and extend into the future our historic strengths in innovation and discovery. Today we are calling on thinkers, doers, and entrepreneurs across the country to submit their proposals for promising new initiatives or pressing needs for renewed investment to be included in next year’s updated Strategy for American Innovation.
What will the next Strategy for American Innovation accomplish? In part, it’s up to you. Your input will help guide the Administration’s efforts to catalyze the transformative innovation in products, processes, and services that is the hallmark of American ingenuity.
Today, we released a set of questions for your comment, which you can access here and on Quora – an online platform that allows us to crowdsource ideas from the American people.

  Calling on America’s Inventors and Innovators for Great Ideas
Among the questions we are posing today to innovators across the country are:

  • What specific policies or initiatives should the Administration consider prioritizing in the next version of the Strategy for American Innovation?
  • What are the biggest challenges to, and opportunities for, innovation in the United States that will generate long-term economic growth and rising standards of living for more Americans?
  • What additional opportunities exist to develop high-impact platform technologies that reduce the time and cost associated with the “design, build, test” cycle for important classes of materials, products, and systems?
  • What investments, strategies, or technological advancements, across both the public and private sectors, are needed to rebuild the U.S. “industrial commons” (i.e., regional manufacturing capabilities) and ensure the latest technologies can be produced here?
  • What partnerships or novel models for collaboration between the Federal Government and regions should the Administration consider in order to promote innovation and the development of regional innovation ecosystems?

 
In today’s world of rapidly evolving technology, the Administration is adapting its approach to innovation-driven economic growth to reflect the emergence of new and exciting possibilities. Now is the time to gather input from the American people in order to envision and shape the innovations of the future. The full Request for Information can be found here and the 2011 Strategy for American Innovation can be found here. Comments are due by September 23, 2014, and can be sent to [email protected].  We look forward to hearing your ideas!”

Request for Proposals: Exploring the Implications of Government Release of Large Datasets

Curated on Posted on by Stefaan Verhulst

“The Berkeley Center for Law & Technology and Microsoft are issuing this request for proposals (RFP) to fund scholarly inquiry to examine the civil rights, human rights, security and privacy issues that arise from recent initiatives to release large datasets of government information to the public for analysis and reuse.  This research may help ground public policy discussions and drive the development of a framework to avoid potential abuses of this data while encouraging greater engagement and innovation.
This RFP seeks to:

    • Gain knowledge of the impact of the online release of large amounts of data generated by citizens’ interactions with government
    • Imagine new possibilities for technical, legal, and regulatory interventions that avoid abuse
    • Begin building a body of research that addresses these issues

– BACKGROUND –

 
Governments at all levels are releasing large datasets for analysis by anyone for any purpose—“Open Data.”  Using Open Data, entrepreneurs may create new products and services, and citizens may use it to gain insight into the government.  A plethora of time saving and other useful applications have emerged from Open Data feeds, including more accurate traffic information, real-time arrival of public transportation, and information about crimes in neighborhoods.  Sometimes governments release large datasets in order to encourage the development of unimagined new applications.  For instance, New York City has made over 1,100 databases available, some of which contain information that can be linked to individuals, such as a parking violation database containing license plate numbers and car descriptions.
Data held by the government is often implicitly or explicitly about individuals—acting in roles that have recognized constitutional protection, such as lobbyist, signatory to a petition, or donor to a political cause; in roles that require special protection, such as victim of, witness to, or suspect in a crime; in the role as businessperson submitting proprietary information to a regulator or obtaining a business license; and in the role of ordinary citizen.  While open government is often presented as an unqualified good, sometimes Open Data can identify individuals or groups, leading to a more transparent citizenry.  The citizen who foresees this growing transparency may be less willing to engage in government, as these transactions may be documented and released in a dataset to anyone to use for any imaginable purpose—including to deanonymize the database—forever.  Moreover, some groups of citizens may have few options or no choice as to whether to engage in governmental activities.  Hence, open data sets may have a disparate impact on certain groups. The potential impact of large-scale data and analysis on civil rights is an area of growing concern.  A number of civil rights and media justice groups banded together in February 2014 to endorse the “Civil Rights Principles for the Era of Big Data” and the potential of new data systems to undermine longstanding civil rights protections was flagged as a “central finding” of a recent policy review by White House adviser John Podesta.
The Berkeley Center for Law & Technology (BCLT) and Microsoft are issuing this request for proposals in an effort to better understand the implications and potential impact of the release of data related to U.S. citizens’ interactions with their local, state and federal governments. BCLT and Microsoft will fund up to six grants, with a combined total of $300,000.  Grantees will be required to participate in a workshop to present and discuss their research at the Berkeley Technology Law Journal (BTLJ) Spring Symposium.  All grantees’ papers will be published in a dedicated monograph.  Grantees’ papers that approach the issues from a legal perspective may also be published in the BTLJ. We may also hold a followup workshop in New York City or Washington, DC.
While we are primarily interested in funding proposals that address issues related to the policy impacts of Open Data, many of these issues are intertwined with general societal implications of “big data.” As a result, proposals that explore Open Data from a big data perspective are welcome; however, proposals solely focused on big data are not.  We are open to proposals that address the following difficult question.  We are also open to methods and disciplines, and are particularly interested in proposals from cross-disciplinary teams.

    • To what extent does existing Open Data made available by city and state governments affect individual profiling?  Do the effects change depending on the level of aggregation (neighborhood vs. cities)?  What releases of information could foreseeably cause discrimination in the future? Will different groups in society be disproportionately impacted by Open Data?
    • Should the use of Open Data be governed by a code of conduct or subject to a review process before being released? In order to enhance citizen privacy, should governments develop guidelines to release sampled or perturbed data, instead of entire datasets? When datasets contain potentially identifiable information, should there be a notice-and-comment proceeding that includes proposed technological solutions to anonymize, de-identify or otherwise perturb the data?
    • Is there something fundamentally different about government services and the government’s collection of citizen’s data for basic needs in modern society such as power and water that requires governments to exercise greater due care than commercial entities?
    • Companies have legal and practical mechanisms to shield data submitted to government from public release.  What mechanisms do individuals have or should have to address misuse of Open Data?  Could developments in the constitutional right to information policy as articulated in Whalen and Westinghouse Electric Co address Open Data privacy issues?
    • Collecting data costs money, and its release could affect civil liberties.  Yet it is being given away freely, sometimes to immensely profitable firms.  Should governments license data for a fee and/or impose limits on its use, given its value?
    • The privacy principle of “collection limitation” is under siege, with many arguing that use restrictions will be more efficacious for protecting privacy and more workable for big data analysis.  Does the potential of Open Data justify eroding state and federal privacy act collection limitation principles?   What are the ethical dimensions of a government system that deprives the data subject of the ability to obscure or prevent the collection of data about a sensitive issue?  A move from collection restrictions to use regulation raises a number of related issues, detailed below.
    • Are use restrictions efficacious in creating accountability?  Consumer reporting agencies are regulated by use restrictions, yet they are not known for their accountability.  How could use regulations be implemented in the context of Open Data efficaciously?  Can a self-learning algorithm honor data use restrictions?
    • If an Open Dataset were regulated by a use restriction, how could individuals police wrongful uses?   How would plaintiffs overcome the likely defenses or proof of facts in a use regulation system, such as a burden to prove that data were analyzed and the product of that analysis was used in a certain way to harm the plaintiff?  Will plaintiffs ever be able to beat first amendment defenses?
    • The President’s Council of Advisors on Science and Technology big data report emphasizes that analysis is not a “use” of data.  Such an interpretation suggests that NSA metadata analysis and large-scale scanning of communications do not raise privacy issues.  What are the ethical and legal implications of the “analysis is not use” argument in the context of Open Data?
    • Open Data celebrates the idea that information collected by the government can be used by another person for various kinds of analysis.  When analysts are not involved in the collection of data, they are less likely to understand its context and limitations.  How do we ensure that this knowledge is maintained in a use regulation system?
    • Former President William Clinton was admitted under a pseudonym for a procedure at a New York Hospital in 2004.  The hospital detected 1,500 attempts by its own employees to access the President’s records.  With snooping such a tempting activity, how could incentives be crafted to cause self-policing of government data and the self-disclosure of inappropriate uses of Open Data?
    • It is clear that data privacy regulation could hamper some big data efforts.  However, many examples of big data successes hail from highly regulated environments, such as health care and financial services—areas with statutory, common law, and IRB protections.  What are the contours of privacy law that are compatible with big data and Open Data success and which are inherently inimical to it?
    • In recent years, the problem of “too much money in politics” has been addressed with increasing disclosure requirements.  Yet, distrust in government remains high, and individuals identified in donor databases have been subjected to harassment.  Is the answer to problems of distrust in government even more Open Data?
    • What are the ethical and epistemological implications of encouraging government decision-making based upon correlation analysis, without a rigorous understanding of cause and effect?  Are there decisions that should not be left to just correlational proof? While enthusiasm for data science has increased, scientific journals are elevating their standards, with special scrutiny focused on hypothesis-free, multiple comparison analysis. What could legal and policy experts learn from experts in statistics about the nature and limits of open data?…
      To submit a proposal, visit the Conference Management Toolkit (CMT) here.
      Once you have created a profile, the site will allow you to submit your proposal.
      If you have questions, please contact Chris Hoofnagle, principal investigator on this project.”

Chief Executive of Nesta on the Future of Government Innovation

Curated on Posted on by Stefaan Verhulst

Interview between Rahim Kanani and Geoff Mulgan, CEO of NESTA and member of the MacArthur Research Network on Opening Governance: “Our aspiration is to become a global center of expertise on all kinds of innovation, from how to back creative business start-ups and how to shape innovations tools such as challenge prizes, to helping governments act as catalysts for new solutions,” explained Geoff Mulgan, chief executive of Nesta, the UK’s innovation foundation. In an interview with Mulgan, we discussed their new report, published in partnership with Bloomberg Philanthropies, which highlights 20 of the world’s top innovation teams in government. Mulgan and I also discussed the founding and evolution of Nesta over the past few years, and leadership lessons from his time inside and outside government.
Rahim Kanani: When we talk about ‘innovations in government’, isn’t that an oxymoron?
Geoff Mulgan: Governments have always innovated. The Internet and World Wide Web both originated in public organizations, and governments are constantly developing new ideas, from public health systems to carbon trading schemes, online tax filing to high speed rail networks.  But they’re much less systematic at innovation than the best in business and science.  There are very few job roles, especially at senior levels, few budgets, and few teams or units.  So although there are plenty of creative individuals in the public sector, they succeed despite, not because of the systems around them. Risk-taking is punished not rewarded.   Over the last century, by contrast, the best businesses have learned how to run R&D departments, product development teams, open innovation processes and reasonably sophisticated ways of tracking investments and returns.
Kanani: This new report, published in partnership with Bloomberg Philanthropies, highlights 20 of the world’s most effective innovation teams in government working to address a range of issues, from reducing murder rates to promoting economic growth. Before I get to the results, how did this project come about, and why is it so important?
Mulgan: If you fail to generate new ideas, test them and scale the ones that work, it’s inevitable that productivity will stagnate and governments will fail to keep up with public expectations, particularly when waves of new technology—from smart phones and the cloud to big data—are opening up dramatic new possibilities.  Mayor Bloomberg has been a leading advocate for innovation in the public sector, and in New York he showed the virtues of energetic experiment, combined with rigorous measurement of results.  In the UK, organizations like Nesta have approached innovation in a very similar way, so it seemed timely to collaborate on a study of the state of the field, particularly since we were regularly being approached by governments wanting to set up new teams and asking for guidance.
Kanani: Where are some of the most effective innovation teams working on these issues, and how did you find them?
Mulgan: In our own work at Nesta, we’ve regularly sought out the best innovation teams that we could learn from and this study made it possible to do that more systematically, focusing in particular on the teams within national and city governments.  They vary greatly, but all the best ones are achieving impact with relatively slim resources.  Some are based in central governments, like Mindlab in Denmark, which has pioneered the use of design methods to reshape government services, from small business licensing to welfare.  SITRA in Finland has been going for decades as a public technology agency, and more recently has switched its attention to innovation in public services. For example, providing mobile tools to help patients manage their own healthcare.   In the city of Seoul, the Mayor set up an innovation team to accelerate the adoption of ‘sharing’ tools, so that people could share things like cars, freeing money for other things.  In south Australia the government set up an innovation agency that has been pioneering radical ways of helping troubled families, mobilizing families to help other families.
Kanani: What surprised you the most about the outcomes of this research?
Mulgan: Perhaps the biggest surprise has been the speed with which this idea is spreading.  Since we started the research, we’ve come across new teams being created in dozens of countries, from Canada and New Zealand to Cambodia and Chile.  China has set up a mobile technology lab for city governments.  Mexico City and many others have set up labs focused on creative uses of open data.  A batch of cities across the US supported by Bloomberg Philanthropy—from Memphis and New Orleans to Boston and Philadelphia—are now showing impressive results and persuading others to copy them.
 

Selected Readings on Sentiment Analysis

Curated on Posted on by sophie

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of sentiment analysis was originally published in 2014.

Sentiment Analysis is a field of Computer Science that uses techniques from natural language processing, computational linguistics, and machine learning to predict subjective meaning from text. The term opinion mining is often used interchangeably with Sentiment Analysis, although it is technically a subfield focusing on the extraction of opinions (the umbrella under which sentiment, evaluation, appraisal, attitude, and emotion all lie).

The rise of Web 2.0 and increased information flow has led to an increase in interest towards Sentiment Analysis — especially as applied to social networks and media. Events causing large spikes in media — such as the 2012 Presidential Election Debates — are especially ripe for analysis. Such analyses raise a variety of implications for the future of crowd participation, elections, and governance.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Choi, Eunsol et al. “Hedge detection as a lens on framing in the GMO debates: a position paper.” Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics 13 Jul. 2012: 70-79. http://bit.ly/1wweftP

  • Understanding the ways in which participants in public discussions frame their arguments is important for understanding how public opinion is formed. This paper adopts the position that it is time for more computationally-oriented research on problems involving framing. In the interests of furthering that goal, the authors propose the following question: In the controversy regarding the use of genetically-modified organisms (GMOs) in agriculture, do pro- and anti-GMO articles differ in whether they choose to adopt a more “scientific” tone?
  • Prior work on the rhetoric and sociology of science suggests that hedging may distinguish popular-science text from text written by professional scientists for their colleagues. The paper proposes a detailed approach to studying whether hedge detection can be used to understand scientific framing in the GMO debates, and provides corpora to facilitate this study. Some of the preliminary analyses suggest that hedges occur less frequently in scientific discourse than in popular text, a finding that contradicts prior assertions in the literature.

Michael, Christina, Francesca Toni, and Krysia Broda. “Sentiment analysis for debates.” (Unpublished MSc thesis). Department of Computing, Imperial College London (2013). http://bit.ly/Wi86Xv

  • This project aims to expand on existing solutions used for automatic sentiment analysis on text in order to capture support/opposition and agreement/disagreement in debates. In addition, it looks at visualizing the classification results for enhancing the ease of understanding the debates and for showing underlying trends. Finally, it evaluates proposed techniques on an existing debate system for social networking.

Murakami, Akiko, and Rudy Raymond. “Support or oppose?: classifying positions in online debates from reply activities and opinion expressions.” Proceedings of the 23rd International Conference on Computational Linguistics: Posters 23 Aug. 2010: 869-875. https://bit.ly/2Eicfnm

  • In this paper, the authors propose a method for the task of identifying the general positions of users in online debates, i.e., support or oppose the main topic of an online debate, by exploiting local information in their remarks within the debate. An online debate is a forum where each user posts an opinion on a particular topic while other users state their positions by posting their remarks within the debate. The supporting or opposing remarks are made by directly replying to the opinion, or indirectly to other remarks (to express local agreement or disagreement), which makes the task of identifying users’ general positions difficult.
  • A prior study has shown that a link-based method, which completely ignores the content of the remarks, can achieve higher accuracy for the identification task than methods based solely on the contents of the remarks. In this paper, it is shown that utilizing the textual content of the remarks into the link-based method can yield higher accuracy in the identification task.

Pang, Bo, and Lillian Lee. “Opinion mining and sentiment analysis.” Foundations and trends in information retrieval 2.1-2 (2008): 1-135. http://bit.ly/UaCBwD

  • This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. Its focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. It includes material on summarization of evaluative text and on broader issues regarding privacy, manipulation, and economic impact that the development of opinion-oriented information-access services gives rise to. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided.

Ranade, Sarvesh et al. “Online debate summarization using topic directed sentiment analysis.” Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining 11 Aug. 2013: 7. http://bit.ly/1nbKtLn

  • Social networking sites provide users a virtual community interaction platform to share their thoughts, life experiences and opinions. Online debate forum is one such platform where people can take a stance and argue in support or opposition of debate topics. An important feature of such forums is that they are dynamic and grow rapidly. In such situations, effective opinion summarization approaches are needed so that readers need not go through the entire debate.
  • This paper aims to summarize online debates by extracting highly topic relevant and sentiment rich sentences. The proposed approach takes into account topic relevant, document relevant and sentiment based features to capture topic opinionated sentences. ROUGE (Recall-Oriented Understudy for Gisting Evaluation, which employ a set of metrics and a software package to compare automatically produced summary or translation against human-produced onces) scores are used to evaluate the system. This system significantly outperforms several baseline systems and show improvement over the state-of-the-art opinion summarization system. The results verify that topic directed sentiment features are most important to generate effective debate summaries.

Schneider, Jodi. “Automated argumentation mining to the rescue? Envisioning argumentation and decision-making support for debates in open online collaboration communities.” http://bit.ly/1mi7ztx

  • Argumentation mining, a relatively new area of discourse analysis, involves automatically identifying and structuring arguments. Following a basic introduction to argumentation, the authors describe a new possible domain for argumentation mining: debates in open online collaboration communities.
  • Based on our experience with manual annotation of arguments in debates, the authors propose argumentation mining as the basis for three kinds of support tools, for authoring more persuasive arguments, finding weaknesses in others’ arguments, and summarizing a debate’s overall conclusions.

Demos for Democracy

Curated on Posted on by Stefaan Verhulst

The GovLab presents Demos for Democracy, an ongoing series of live, interactive online demos featuring designers and builders of the latest innovative governance platforms, tools or methods to foster greater openness and collaboration to how we govern.
Who: remesh, founded by PhD students Andrew Konya and Aaron Slodov, is an online public platform that offers a community, group, nation or planet of people the ability to speak with one voice that represents the collective thinking of all people within the group. remesh was prototyped at a HacKSU hackathon early in 2013 and has been under development over the past year.
What: Join us for a live demonstration of how remesh works before their official public launch. Participants will be given a link to test the platform during the live Google hangout.  More information on what remesh does can be found here.
When: July 29, 2014, 2:00 – 2:30 PM EST
Where: Online via Google Hangouts on Air. To RSVP and join, go to the Hangout Link. This event will be live tweeted at #democracydemos.
Bios:
Andrew Konya (CEO/Founder) is a PhD student in computational/theoretical physics at Kent State University. With extensive experience developing and implementing mathematical models for natural and man-made systems, Andrew brings a creative yet and versatile technical toolbox. This expertise, in concert with his passion for linguistics, led him to develop the first mathematical framework for collective speech. His goal is the completion of a conversation platform, built on this framework, which can make conversations between countries in conflict a viable alternative to war.
Aaron Slodov (COO/Founder) is a current power systems engineering PhD student at Case Western Reserve University. A previous engineer at both Google and Meetup.com, Aaron is experienced in the tech landscape, and understands many of the current problems in the space. By enabling remesh technology he hopes to bring significant paradigm-shifting change to the way we communicate and interact with our world.
RSVP and JOIN
We hope to see you on Tuesday! If you have any questions, email us at [email protected].

Recent progress in Open Data production and consumption

Curated on Posted on by Stefaan Verhulst

Examples from a Governmental institute (SMHI) and a collaborative EU research project (SWITCH-ON) by Arheimer, Berit; and Falkenroth, Esa: “The Swedish Meteorological and Hydrological Institute (SMHI) has a long tradition both in producing and consuming open data on a national, European and global scale. It is also promoting community building among water scientists in Europe by participating in and initiating collaborative projects. This presentation will exemplify the contemporary European movement imposed by the INSPIRE directive and the Open Data Strategy, by showing the progress in openness and shift in attitudes during the last decade when handling Research Data and Public Sector Information at a national European institute. Moreover, the presentation will inform about a recently started collaborative project (EU FP7 project No 603587) coordinated by SMHI and called SWITCH-ON http://water-switch-on.eu/. The project addresses water concerns and currently untapped potential of open data for improved water management across the EU. The overall goal of the project is to make use of open data, and add value to society by repurposing and refining data from various sources. SWITCH-ON will establish new forms of water research and facilitate the development of new products and services based on principles of sharing and community building in the water society. The SWITCH-ON objectives are to use open data for implementing: 1) an innovative spatial information platform with open data tailored for direct water assessments, 2) an entirely new form of collaborative research for water-related sciences, 3) fourteen new operational products and services dedicated to appointed end-users, 4) new business and knowledge to inform individual and collective decisions in line with the Europe’s smart growth and environmental objectives. The presentation will discuss challenges, progress and opportunities with the open data strategy, based on the experiences from working both at a Governmental institute and being part of the global research community.”