Selected Readings on Economic Impact of Open Data

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.

  • 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.

  • 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.

  • 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.

  • 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,

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

Selected Readings on Sentiment Analysis

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.

  • 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).

  • 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.

  • 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.

  • 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.

  • 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.”

  • 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.

Selected Readings on Crowdsourcing Expertise

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 crowdsourcing was originally published in 2014.

Crowdsourcing enables leaders and citizens to work together to solve public problems in new and innovative ways. New tools and platforms enable citizens with differing levels of knowledge, expertise, experience and abilities to collaborate and solve problems together. Identifying experts, or individuals with specialized skills, knowledge or abilities with regard to a specific topic, and incentivizing their participation in crowdsourcing information, knowledge or experience to achieve a shared goal can enhance the efficiency and effectiveness of problem solving.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Börner, Katy, Michael Conlon, Jon Corson-Rikert, and Ying Ding. “VIVO: A Semantic Approach to Scholarly Networking and Discovery.” Synthesis Lectures on the Semantic Web: Theory and Technology 2, no. 1 (October 17, 2012): 1–178.

  • This e-book “provides an introduction to VIVO…a tool for representing information about research and researchers — their scholarly works, research interests, and organizational relationships.”
  • VIVO is a response to the fact that, “Information for scholars — and about scholarly activity — has not kept pace with the increasing demands and expectations. Information remains siloed in legacy systems and behind various access controls that must be licensed or otherwise negotiated before access. Information representation is in its infancy. The raw material of scholarship — the data and information regarding previous work — is not available in common formats with common semantics.”
  • Providing access to structured information on the work and experience of a diversity of scholars enables improved expert finding — “identifying and engaging experts whose scholarly works is of value to one’s own. To find experts, one needs rich data regarding one’s own work and the work of potential related experts. The authors argue that expert finding is of increasing importance since, “[m]ulti-disciplinary and inter-disciplinary investigation is increasingly required to address complex problems. 

Bozzon, Alessandro, Marco Brambilla, Stefano Ceri, Matteo Silvestri, and Giuliano Vesci. “Choosing the Right Crowd: Expert Finding in Social Networks.” In Proceedings of the 16th International Conference on Extending Database Technology, 637–648. EDBT  ’13. New York, NY, USA: ACM, 2013.

  • This paper explores the challenge of selecting experts within the population of social networks by considering the following problem: “given an expertise need (expressed for instance as a natural language query) and a set of social network members, who are the most knowledgeable people for addressing that need?”
  • The authors come to the following conclusions:
    • “profile information is generally less effective than information about resources that they directly create, own or annotate;
    • resources which are produced by others (resources appearing on the person’s Facebook wall or produced by people that she follows on Twitter) help increasing the assessment precision;
    • Twitter appears the most effective social network for expertise matching, as it very frequently outperforms all other social networks (either combined or alone);
    • Twitter appears as well very effective for matching expertise in domains such as computer engineering, science, sport, and technology & games, but Facebook is also very effective in fields such as locations, music, sport, and movies & tv;
    • surprisingly, LinkedIn appears less effective than other social networks in all domains (including computer science) and overall.”

Brabham, Daren C. “The Myth of Amateur Crowds.” Information, Communication & Society 15, no. 3 (2012): 394–410.

  • Unlike most of the related literature, this paper focuses on bringing attention to the expertise already being tapped by crowdsourcing efforts rather than determining ways to identify more dormant expertise to improve the results of crowdsourcing.
  • Brabham comes to two central conclusions: “(1) crowdsourcing is discussed in the popular press as a process driven by amateurs and hobbyists, yet empirical research on crowdsourcing indicates that crowds are largely self-selected professionals and experts who opt-in to crowdsourcing arrangements; and (2) the myth of the amateur in crowdsourcing ventures works to label crowds as mere hobbyists who see crowdsourcing ventures as opportunities for creative expression, as entertainment, or as opportunities to pass the time when bored. This amateur/hobbyist label then undermines the fact that large amounts of real work and expert knowledge are exerted by crowds for relatively little reward and to serve the profit motives of companies. 

Dutton, William H. Networking Distributed Public Expertise: Strategies for Citizen Sourcing Advice to Government. One of a Series of Occasional Papers in Science and Technology Policy, Science and Technology Policy Institute, Institute for Defense Analyses, February 23, 2011.

  • In this paper, a case is made for more structured and well-managed crowdsourcing efforts within government. Specifically, the paper “explains how collaborative networking can be used to harness the distributed expertise of citizens, as distinguished from citizen consultation, which seeks to engage citizens — each on an equal footing.” Instead of looking for answers from an undefined crowd, Dutton proposes “networking the public as advisors” by seeking to “involve experts on particular public issues and problems distributed anywhere in the world.”
  • Dutton argues that expert-based crowdsourcing can be successfully for government for a number of reasons:
    • Direct communication with a diversity of independent experts
    • The convening power of government
    • Compatibility with open government and open innovation
    • Synergy with citizen consultation
    • Building on experience with paid consultants
    • Speed and urgency
    • Centrality of documents to policy and practice.
  • He also proposes a nine-step process for government to foster bottom-up collaboration networks:
    • Do not reinvent the technology
    • Focus on activities, not the tools
    • Start small, but capable of scaling up
    • Modularize
    • Be open and flexible in finding and going to communities of experts
    • Do not concentrate on one approach to all problems
    • Cultivate the bottom-up development of multiple projects
    • Experience networking and collaborating — be a networked individual
    • Capture, reward, and publicize success.

Goel, Gagan, Afshin Nikzad and Adish Singla. “Matching Workers with Tasks: Incentives in Heterogeneous Crowdsourcing Markets.” Under review by the International World Wide Web Conference (WWW). 2014.

  • Combining the notions of crowdsourcing expertise and crowdsourcing tasks, this paper focuses on the challenge within platforms like Mechanical Turk related to intelligently matching tasks to workers.
  • The authors’ call for more strategic assignment of tasks in crowdsourcing markets is based on the understanding that “each worker has certain expertise and interests which define the set of tasks she can and is willing to do.”
  • Focusing on developing meaningful incentives based on varying levels of expertise, the authors sought to create a mechanism that, “i) is incentive compatible in the sense that it is truthful for agents to report their true cost, ii) picks a set of workers and assigns them to the tasks they are eligible for in order to maximize the utility of the requester, iii) makes sure total payments made to the workers doesn’t exceed the budget of the requester.

Gubanov, D., N. Korgin, D. Novikov and A. Kalkov. E-Expertise: Modern Collective Intelligence. Springer, Studies in Computational Intelligence 558, 2014.

  • In this book, the authors focus on “organization and mechanisms of expert decision-making support using modern information and communication technologies, as well as information analysis and collective intelligence technologies (electronic expertise or simply e-expertise).”
  • The book, which “addresses a wide range of readers interested in management, decision-making and expert activity in political, economic, social and industrial spheres, is broken into five chapters:
    • Chapter 1 (E-Expertise) discusses the role of e-expertise in decision-making processes. The procedures of e-expertise are classified, their benefits and shortcomings are identified, and the efficiency conditions are considered.
    • Chapter 2 (Expert Technologies and Principles) provides a comprehensive overview of modern expert technologies. A special emphasis is placed on the specifics of e-expertise. Moreover, the authors study the feasibility and reasonability of employing well-known methods and approaches in e-expertise.
    • Chapter 3 (E-Expertise: Organization and Technologies) describes some examples of up-to-date technologies to perform e-expertise.
    • Chapter 4 (Trust Networks and Competence Networks) deals with the problems of expert finding and grouping by information and communication technologies.
    • Chapter 5 (Active Expertise) treats the problem of expertise stability against any strategic manipulation by experts or coordinators pursuing individual goals.

Holst, Cathrine. “Expertise and Democracy.” ARENA Report No 1/14, Center for European Studies, University of Oslo.

  • This report contains a set of 16 papers focused on the concept of “epistocracy,” meaning the “rule of knowers.” The papers inquire into the role of knowledge and expertise in modern democracies and especially in the European Union (EU). Major themes are: expert-rule and democratic legitimacy; the role of knowledge and expertise in EU governance; and the European Commission’s use of expertise.
    • Expert-rule and democratic legitimacy
      • Papers within this theme concentrate on issues such as the “implications of modern democracies’ knowledge and expertise dependence for political and democratic theory.” Topics include the accountability of experts, the legitimacy of expert arrangements within democracies, the role of evidence in policy-making, how expertise can be problematic in democratic contexts, and “ethical expertise” and its place in epistemic democracies.
    • The role of knowledge and expertise in EU governance
      • Papers within this theme concentrate on “general trends and developments in the EU with regard to the role of expertise and experts in political decision-making, the implications for the EU’s democratic legitimacy, and analytical strategies for studying expertise and democratic legitimacy in an EU context.”
    • The European Commission’s use of expertise
      • Papers within this theme concentrate on how the European Commission uses expertise and in particular the European Commission’s “expertgroup system.” Topics include the European Citizen’s Initiative, analytic-deliberative processes in EU food safety, the operation of EU environmental agencies, and the autonomy of various EU agencies.

King, Andrew and Karim R. Lakhani. “Using Open Innovation to Identify the Best Ideas.” MIT Sloan Management Review, September 11, 2013.

  • In this paper, King and Lakhani examine different methods for opening innovation, where, “[i]nstead of doing everything in-house, companies can tap into the ideas cloud of external expertise to develop new products and services.”
  • The three types of open innovation discussed are: opening the idea-creation process, competitions where prizes are offered and designers bid with possible solutions; opening the idea-selection process, ‘approval contests’ in which outsiders vote to determine which entries should be pursued; and opening both idea generation and selection, an option used especially by organizations focused on quickly changing needs.

Long, Chengjiang, Gang Hua and Ashish Kapoor. Active Visual Recognition with Expertise Estimation in Crowdsourcing. 2013 IEEE International Conference on Computer Vision. December 2013.

  • This paper is focused on improving the crowdsourced labeling of visual datasets from platforms like Mechanical Turk. The authors note that, “Although it is cheap to obtain large quantity of labels through crowdsourcing, it has been well known that the collected labels could be very noisy. So it is desirable to model the expertise level of the labelers to ensure the quality of the labels. The higher the expertise level a labeler is at, the lower the label noises he/she will produce.”
  • Based on the need for identifying expert labelers upfront, the authors developed an “active classifier learning system which determines which users to label which unlabeled examples” from collected visual datasets.
  • The researchers’ experiments in identifying expert visual dataset labelers led to findings demonstrating that the “active selection” of expert labelers is beneficial in cutting through the noise of crowdsourcing platforms.

Noveck, Beth Simone. “’Peer to Patent’: Collective Intelligence, Open Review, and Patent Reform.” Harvard Journal of Law & Technology 20, no. 1 (Fall 2006): 123–162.

  • This law review article introduces the idea of crowdsourcing expertise to mitigate the challenge of patent processing. Noveck argues that, “access to information is the crux of the patent quality problem. Patent examiners currently make decisions about the grant of a patent that will shape an industry for a twenty-year period on the basis of a limited subset of available information. Examiners may neither consult the public, talk to experts, nor, in many cases, even use the Internet.”
  • Peer-to-Patent, which launched three years after this article, is based on the idea that, “The new generation of social software might not only make it easier to find friends but also to find expertise that can be applied to legal and policy decision-making. This way, we can improve upon the Constitutional promise to promote the progress of science and the useful arts in our democracy by ensuring that only worth ideas receive that ‘odious monopoly’ of which Thomas Jefferson complained.”

Ober, Josiah. “Democracy’s Wisdom: An Aristotelian Middle Way for Collective Judgment.” American Political Science Review 107, no. 01 (2013): 104–122.

  • In this paper, Ober argues that, “A satisfactory model of decision-making in an epistemic democracy must respect democratic values, while advancing citizens’ interests, by taking account of relevant knowledge about the world.”
  • Ober describes an approach to decision-making that aggregates expertise across multiple domains. This “Relevant Expertise Aggregation (REA) enables a body of minimally competent voters to make superior choices among multiple options, on matters of common interest.”

Sims, Max H., Jeffrey Bigham, Henry Kautz and Marc W. Halterman. Crowdsourcing medical expertise in near real time.” Journal of Hospital Medicine 9, no. 7, July 2014.

  • In this article, the authors discuss the develoment of a mobile application called DocCHIRP, which was developed due to the fact that, “although the Internet creates unprecedented access to information, gaps in the medical literature and inefficient searches often leave healthcare providers’ questions unanswered.”
  • The DocCHIRP pilot project used a “system of point-to-multipoint push notifications designed to help providers problem solve by crowdsourcing from their peers.”
  • Healthcare providers (HCPs) sought to gain intelligence from the crowd, which included 85 registered users, on questions related to medication, complex medical decision making, standard of care, administrative, testing and referrals.
  • The authors believe that, “if future iterations of the mobile crowdsourcing applications can address…adoption barriers and support the organic growth of the crowd of HCPs,” then “the approach could have a positive and transformative effect on how providers acquire relevant knowledge and care for patients.”

Spina, Alessandro. “Scientific Expertise and Open Government in the Digital Era: Some Reflections on EFSA and Other EU Agencies.” in Foundations of EU Food Law and Policy, eds. A. Alemmano and S. Gabbi. Ashgate, 2014.

  • In this paper, Spina “presents some reflections on how the collaborative and crowdsourcing practices of Open Government could be integrated in the activities of EFSA [European Food Safety Authority] and other EU agencies,” with a particular focus on “highlighting the benefits of the Open Government paradigm for expert regulatory bodies in the EU.”
  • Spina argues that the “crowdsourcing of expertise and the reconfiguration of the information flows between European agencies and teh public could represent a concrete possibility of modernising the role of agencies with a new model that has a low financial burden and an almost immediate effect on the legal governance of agencies.”
  • He concludes that, “It is becoming evident that in order to guarantee that the best scientific expertise is provided to EU institutions and citizens, EFSA should strive to use the best organisational models to source science and expertise.”

Selected Readings on Crowdsourcing Tasks and Peer Production

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 crowdsourcing was originally published in 2014.

Technological advances are creating a new paradigm by which institutions and organizations are increasingly outsourcing tasks to an open community, allocating specific needs to a flexible, willing and dispersed workforce. “Microtasking” platforms like Amazon’s Mechanical Turk are a burgeoning source of income for individuals who contribute their time, skills and knowledge on a per-task basis. In parallel, citizen science projects – task-based initiatives in which citizens of any background can help contribute to scientific research – like Galaxy Zoo are demonstrating the ability of lay and expert citizens alike to make small, useful contributions to aid large, complex undertakings. As governing institutions seek to do more with less, looking to the success of citizen science and microtasking initiatives could provide a blueprint for engaging citizens to help accomplish difficult, time-consuming objectives at little cost. Moreover, the incredible success of peer-production projects – best exemplified by Wikipedia – instills optimism regarding the public’s willingness and ability to complete relatively small tasks that feed into a greater whole and benefit the public good. You can learn more about this new wave of “collective intelligence” by following the MIT Center for Collective Intelligence and their annual Collective Intelligence Conference.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Benkler, Yochai. The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale University Press, 2006.

  • In this book, Benkler “describes how patterns of information, knowledge, and cultural production are changing – and shows that the way information and knowledge are made available can either limit or enlarge the ways people can create and express themselves.”
  • In his discussion on Wikipedia – one of many paradigmatic examples of people collaborating without financial reward – he calls attention to the notable ongoing cooperation taking place among a diversity of individuals. He argues that, “The important point is that Wikipedia requires not only mechanical cooperation among people, but a commitment to a particular style of writing and describing concepts that is far from intuitive or natural to people. It requires self-discipline. It enforces the behavior it requires primarily through appeal to the common enterprise that the participants are engaged in…”

Brabham, Daren C. Using Crowdsourcing in Government. Collaborating Across Boundaries Series. IBM Center for The Business of Government, 2013.

  • In this report, Brabham categorizes government crowdsourcing cases into a “four-part, problem-based typology, encouraging government leaders and public administrators to consider these open problem-solving techniques as a way to engage the public and tackle difficult policy and administrative tasks more effectively and efficiently using online communities.”
  • The proposed four-part typology describes the following types of crowdsourcing in government:
    • Knowledge Discovery and Management
    • Distributed Human Intelligence Tasking
    • Broadcast Search
    • Peer-Vetted Creative Production
  • In his discussion on Distributed Human Intelligence Tasking, Brabham argues that Amazon’s Mechanical Turk and other microtasking platforms could be useful in a number of governance scenarios, including:
    • Governments and scholars transcribing historical document scans
    • Public health departments translating health campaign materials into foreign languages to benefit constituents who do not speak the native language
    • Governments translating tax documents, school enrollment and immunization brochures, and other important materials into minority languages
    • Helping governments predict citizens’ behavior, “such as for predicting their use of public transit or other services or for predicting behaviors that could inform public health practitioners and environmental policy makers”

Boudreau, Kevin J., Patrick Gaule, Karim Lakhani, Christoph Reidl, Anita Williams Woolley. “From Crowds to Collaborators: Initiating Effort & Catalyzing Interactions Among Online Creative Workers.” Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 14-060. January 23, 2014.

  • In this working paper, the authors explore the “conditions necessary for eliciting effort from those affecting the quality of interdependent teamwork” and “consider the the role of incentives versus social processes in catalyzing collaboration.”
  • The paper’s findings are based on an experiment involving 260 individuals randomly assigned to 52 teams working toward solutions to a complex problem.
  • The authors determined the level of effort in such collaborative undertakings are sensitive to cash incentives. However, collaboration among teams was driven more by the active participation of teammates, rather than any monetary reward.

Franzoni, Chiara, and Henry Sauermann. “Crowd Science: The Organization of Scientific Research in Open Collaborative Projects.” Research Policy (August 14, 2013).

  • In this paper, the authors explore the concept of crowd science, which they define based on two important features: “participation in a project is open to a wide base of potential contributors, and intermediate inputs such as data or problem solving algorithms are made openly available.” The rationale for their study and conceptual framework is the “growing attention from the scientific community, but also policy makers, funding agencies and managers who seek to evaluate its potential benefits and challenges. Based on the experiences of early crowd science projects, the opportunities are considerable.”
  • Based on the study of a number of crowd science projects – including governance-related initiatives like Patients Like Me – the authors identify a number of potential benefits in the following categories:
    • Knowledge-related benefits
    • Benefits from open participation
    • Benefits from the open disclosure of intermediate inputs
    • Motivational benefits
  • The authors also identify a number of challenges:
    • Organizational challenges
    • Matching projects and people
    • Division of labor and integration of contributions
    • Project leadership
    • Motivational challenges
    • Sustaining contributor involvement
    • Supporting a broader set of motivations
    • Reconciling conflicting motivations

Kittur, Aniket, Ed H. Chi, and Bongwon Suh. “Crowdsourcing User Studies with Mechanical Turk.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 453–456. CHI ’08. New York, NY, USA: ACM, 2008.

  • In this paper, the authors examine “[m]icro-task markets, such as Amazon’s Mechanical Turk, [which] offer a potential paradigm for engaging a large number of users for low time and monetary costs. [They] investigate the utility of a micro-task market for collecting user measurements, and discuss design considerations for developing remote micro user evaluation tasks.”
  • The authors conclude that in addition to providing a means for crowdsourcing small, clearly defined, often non-skill-intensive tasks, “Micro-task markets such as Amazon’s Mechanical Turk are promising platforms for conducting a variety of user study tasks, ranging from surveys to rapid prototyping to quantitative measures. Hundreds of users can be recruited for highly interactive tasks for marginal costs within a timeframe of days or even minutes. However, special care must be taken in the design of the task, especially for user measurements that are subjective or qualitative.”

Kittur, Aniket, Jeffrey V. Nickerson, Michael S. Bernstein, Elizabeth M. Gerber, Aaron Shaw, John Zimmerman, Matthew Lease, and John J. Horton. “The Future of Crowd Work.” In 16th ACM Conference on Computer Supported Cooperative Work (CSCW 2013), 2012.

  • In this paper, the authors discuss paid crowd work, which “offers remarkable opportunities for improving productivity, social mobility, and the global economy by engaging a geographically distributed workforce to complete complex tasks on demand and at scale.” However, they caution that, “it is also possible that crowd work will fail to achieve its potential, focusing on assembly-line piecework.”
  • The authors argue that seven key challenges must be met to ensure that crowd work processes evolve and reach their full potential:
    • Designing workflows
    • Assigning tasks
    • Supporting hierarchical structure
    • Enabling real-time crowd work
    • Supporting synchronous collaboration
    • Controlling quality

Madison, Michael J. “Commons at the Intersection of Peer Production, Citizen Science, and Big Data: Galaxy Zoo.” In Convening Cultural Commons, 2013.

  • This paper explores a “case of commons governance grounded in research in modern astronomy. The case, Galaxy Zoo, is a leading example of at least three different contemporary phenomena. In the first place, Galaxy Zoo is a global citizen science project, in which volunteer non-scientists have been recruited to participate in large-scale data analysis on the Internet. In the second place, Galaxy Zoo is a highly successful example of peer production, some times known as crowdsourcing…In the third place, is a highly visible example of data-intensive science, sometimes referred to as e-science or Big Data science, by which scientific researchers develop methods to grapple with the massive volumes of digital data now available to them via modern sensing and imaging technologies.”
  • Madison concludes that the success of Galaxy Zoo has not been the result of the “character of its information resources (scientific data) and rules regarding their usage,” but rather, the fact that the “community was guided from the outset by a vision of a specific organizational solution to a specific research problem in astronomy, initiated and governed, over time, by professional astronomers in collaboration with their expanding universe of volunteers.”

Malone, Thomas W., Robert Laubacher and Chrysanthos Dellarocas. “Harnessing Crowds: Mapping the Genome of Collective Intelligence.” MIT Sloan Research Paper. February 3, 2009.

  • In this article, the authors describe and map the phenomenon of collective intelligence – also referred to as “radical decentralization, crowd-sourcing, wisdom of crowds, peer production, and wikinomics – which they broadly define as “groups of individuals doing things collectively that seem intelligent.”
  • The article is derived from the authors’ work at MIT’s Center for Collective Intelligence, where they gathered nearly 250 examples of Web-enabled collective intelligence. To map the building blocks or “genes” of collective intelligence, the authors used two pairs of related questions:
    • Who is performing the task? Why are they doing it?
    • What is being accomplished? How is it being done?
  • The authors concede that much work remains to be done “to identify all the different genes for collective intelligence, the conditions under which these genes are useful, and the constraints governing how they can be combined,” but they believe that their framework provides a useful start and gives managers and other institutional decisionmakers looking to take advantage of collective intelligence activities the ability to “systematically consider many possible combinations of answers to questions about Who, Why, What, and How.”

Mulgan, Geoff. “True Collective Intelligence? A Sketch of a Possible New Field.” Philosophy & Technology 27, no. 1. March 2014.

  • In this paper, Mulgan explores the concept of a collective intelligence, a “much talked about but…very underdeveloped” field.
  • With a particular focus on health knowledge, Mulgan “sets out some of the potential theoretical building blocks, suggests an experimental and research agenda, shows how it could be analysed within an organisation or business sector and points to possible intellectual barriers to progress.”
  • He concludes that the “central message that comes from observing real intelligence is that intelligence has to be for something,” and that “turning this simple insight – the stuff of so many science fiction stories – into new theories, new technologies and new applications looks set to be one of the most exciting prospects of the next few years and may help give shape to a new discipline that helps us to be collectively intelligent about our own collective intelligence.”

Sauermann, Henry and Chiara Franzoni. “Participation Dynamics in Crowd-Based Knowledge Production: The Scope and Sustainability of Interest-Based Motivation.” SSRN Working Papers Series. November 28, 2013.

  • In this paper, Sauremann and Franzoni explore the issue of interest-based motivation in crowd-based knowledge production – in particular the use of the crowd science platform Zooniverse – by drawing on “research in psychology to discuss important static and dynamic features of interest and deriv[ing] a number of research questions.”
  • The authors find that interest-based motivation is often tied to a “particular object (e.g., task, project, topic)” not based on a “general trait of the person or a general characteristic of the object.” As such, they find that “most members of the installed base of users on the platform do not sign up for multiple projects, and most of those who try out a project do not return.”
  • They conclude that “interest can be a powerful motivator of individuals’ contributions to crowd-based knowledge production…However, both the scope and sustainability of this interest appear to be rather limited for the large majority of contributors…At the same time, some individuals show a strong and more enduring interest to participate both within and across projects, and these contributors are ultimately responsible for much of what crowd science projects are able to accomplish.”

Schmitt-Sands, Catherine E. and Richard J. Smith. “Prospects for Online Crowdsourcing of Social Science Research Tasks: A Case Study Using Amazon Mechanical Turk.” SSRN Working Papers Series. January 9, 2014.

  • In this paper, the authors describe an experiment involving the nascent use of Amazon’s Mechanical Turk as a social science research tool. “While researchers have used crowdsourcing to find research subjects or classify texts, [they] used Mechanical Turk to conduct a policy scan of local government websites.”
  • Schmitt-Sands and Smith found that “crowdsourcing worked well for conducting an online policy program and scan.” The microtasked workers were helpful in screening out local governments that either did not have websites or did not have the types of policies and services for which the researchers were looking. However, “if the task is complicated such that it requires ongoing supervision, then crowdsourcing is not the best solution.”

Shirky, Clay. Here Comes Everybody: The Power of Organizing Without Organizations. New York: Penguin Press, 2008.

  • In this book, Shirky explores our current era in which, “For the first time in history, the tools for cooperating on a global scale are not solely in the hands of governments or institutions. The spread of the Internet and mobile phones are changing how people come together and get things done.”
  • Discussing Wikipedia’s “spontaneous division of labor,” Shirky argues that the process is like, “the process is more like creating a coral reef, the sum of millions of individual actions, than creating a car. And the key to creating those individual actions is to hand as much freedom as possible to the average user.”

Silvertown, Jonathan. “A New Dawn for Citizen Science.” Trends in Ecology & Evolution 24, no. 9 (September 2009): 467–471.

  • This article discusses the move from “Science for the people,” a slogan adopted by activists in the 1970s to “’Science by the people,’ which is “a more inclusive aim, and is becoming a distinctly 21st century phenomenon.”
  • Silvertown identifies three factors that are responsible for the explosion of activity in citizen science, each of which could be similarly related to the crowdsourcing of skills by governing institutions:
    • “First is the existence of easily available technical tools for disseminating information about products and gathering data from the public.
    • A second factor driving the growth of citizen science is the increasing realisation among professional scientists that the public represent a free source of labour, skills, computational power and even finance.
    • Third, citizen science is likely to benefit from the condition that research funders such as the National Science Foundation in the USA and the Natural Environment Research Council in the UK now impose upon every grantholder to undertake project-related science outreach. This is outreach as a form of public accountability.”

Szkuta, Katarzyna, Roberto Pizzicannella, David Osimo. “Collaborative approaches to public sector innovation: A scoping study.” Telecommunications Policy. 2014.

  • In this article, the authors explore cases where government collaboratively delivers online public services, with a focus on success factors and “incentives for services providers, citizens as users and public administration.”
  • The authors focus on six types of collaborative governance projects:
    • Services initiated by government built on government data;
    • Services initiated by government and making use of citizens’ data;
    • Services initiated by civil society built on open government data;
    • Collaborative e-government services; and
    • Services run by civil society and based on citizen data.
  • The cases explored “are all designed in the way that effectively harnesses the citizens’ potential. Services susceptible to collaboration are those that require computing efforts, i.e. many non-complicated tasks (e.g. citizen science projects – Zooniverse) or citizens’ free time in general (e.g. time banks). Those services also profit from unique citizens’ skills and their propensity to share their competencies.”

Selected Readings on Behavioral Economics: Nudges

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 behavioral economics was originally published in 2014.

The 2008 publication of Richard Thaler and Cass Sunstein’s Nudge ushered in a new era of behavioral economics, and since then, policy makers in the United States and elsewhere have been applying behavioral economics to the field of public policy. Like Smart Disclosure, behavioral economics can be used in the public sector to improve the decisionmaking ability of citizens without relying on regulatory interventions. In the six years since Nudge was published, the United Kingdom has created the Behavioural Insights Team (also known as the Nudge Unit), a cross-ministerial organization that uses behavioral economics to inform public policy, and the White House has recently followed suit by convening a team of behavioral economists to create a behavioral insights-driven team in the United States. Policymakers have been using behavioral insights to design more effective interventions in the fields of long term unemployment; roadway safety; enrollment in retirement plans; and increasing enrollment in organ donation registries, to name some noteworthy examples. The literature of this nascent field provides a look at the growing optimism in the potential of applying behavioral insights in the public sector to improve people’s lives.

Selected Reading List (in alphabetical order)

  • John Beshears, James Choi, David Laibson and Brigitte C. Madrian – The Importance of Default Options for Retirement Savings Outcomes: Evidence from the United States – a paper examining the role default options play in encouraging intelligent retirement savings decisionmaking.
  • Cabinet Office and Behavioural Insights Team, United Kingdom – Applying Behavioural Insights to Healtha paper outlining some examples of behavioral economics being applied to the healthcare landscape using cost-efficient interventions.
  • Matthew Darling, Saugato Datta and Sendhil Mullainathan – The Nature of the BEast: What Behavioral Economics Is Not – a paper discussing why control and behavioral economics are not as closely aligned as some think, reiterating the fact that the field is politically agnostic.
  • Antoinette Schoar and Saugato Datta – The Power of Heuristics – a paper exploring the concept of “heuristics,” or rules of thumb, which can provide helpful guidelines for pushing people toward making “reasonably good” decisions without a full understanding of the complexity of a situation.
  • Richard H. Thaler and Cass R. Sunstein – Nudge: Improving Decisions About Health, Wealth, and Happiness – an influential book describing the many ways in which the principles of behavioral economics can be and have been used to influence choices and behavior through the development of new “choice architectures.” 
  • U.K. Parliament Science and Technology Committee – Behaviour Changean exploration of the government’s attempts to influence the behaviour of its citizens through nudges, with a focus on comparing the effectiveness of nudges to that of regulatory interventions.

Annotated Selected Reading List (in alphabetical order)

Beshears, John, James Choi, David Laibson and Brigitte C. Madrian. “The Importance of Default Options for Retirement Savings Outcomes: Evidence from the United States.” In Jeffrey R. Brown, Jeffrey B. Liebman and David A. Wise, editors, Social Security Policy in a Changing Environment, Cambridge: National Bureau of Economic Research, 2009.

  • This paper examines the role default options play in pushing people toward making intelligent decisions regarding long-term savings and retirement planning.
  • Importantly, the authors provide evidence that a strategically oriented default setting from the outset is likely not enough to fully nudge people toward the best possible decisions in retirement savings. They find that the default settings in every major dimension of the savings process (from deciding whether to participate in a 401(k) to how to withdraw money at retirement) have real and distinct effects on behavior.

Cabinet Office and Behavioural Insights Team, United Kingdom. “Applying Behavioural Insights to Health.” December 2010.

  • In this report, the United Kingdom’s Behavioural Insights Team does not attempt to “suggest that behaviour change techniques are the silver bullet that can solve every problem.” Rather, they explore a variety of examples where local authorities, charities, government and the private-sector are using behavioural interventions to encourage healthier behaviors.  
  • The report features case studies regarding behavioral insights ability to affect the following public health issues:
    • Smoking
    • Organ donation
    • Teenage pregnancy
    • Alcohol
    • Diet and weight
    • Diabetes
    • Food hygiene
    • Physical activity
    • Social care
  • The report concludes with a call for more experimentation and knowledge gathering to determine when, where and how behavioural interventions can be most effective in helping the public become healthier.

Darling, Matthew, Saugato Datta and Sendhil Mullainathan. “The Nature of the BEast: What Behavioral Economics Is Not.” The Center for Global Development. October 2013.

  • In this paper, Darling, Datta and Mullainathan outline the three most pervasive myths that abound within the literature about behavioral economics:
    • First, they dispel the relationship between control and behavioral economics.  Although tools used within behavioral economics can convince people to make certain choices, the goal is to nudge people to make the choices they want to make. For example, studies find that when retirement savings plans change the default to opt-in rather than opt-out, more workers set up 401K plans. This is an example of a nudge that guides people to make a choice that they already intend to make.
    • Second, they reiterate that the field is politically agnostic. Both liberals and conservatives have adopted behavioral economics and its approach is neither liberal nor conservative. President Obama embraces behavioral economics but the United Kingdom’s conservative party does, too.
    • And thirdly, the article highlights that irrationality actually has little to do with behavioral economics. Context is an important consideration when one considers what behavior is rational and what behavior is not. Rather than use the term “irrational” to describe human beings, the authors assert that humans are “infinitely complex” and behavior that is often considered irrational is entirely situational.

Schoar, Antoinette and Saugato Datta. “The Power of Heuristics.” Ideas42. January 2014.

  • This paper explores the notion that being presented with a bevy of options can be desirable in many situations, but when making an intelligent decision requires a high-level understanding of the nuances of vastly different financial aid packages, for example, options can overwhelm. Heuristics (rules of thumb) provide helpful guidelines that “enable people to make ‘reasonably good’ decisions without needing to understand all the complex nuances of the situation.”
  • The underlying goal heuristics in the policy space involves giving people the type of “rules of thumb” that enable make good decisionmaking regarding complex topics such as finance, healthcare and education. The authors point to the benefit of asking individuals to remember smaller pieces of knowledge by referencing a series of studies conducted by psychologists Beatty and Kahneman that showed people were better able to remember long strings of numbers when they were broken into smaller segments.
  • Schoar and Datta recommend these four rules when implementing heuristics:
    • Use heuristics where possible, particularly in complex situation;
    • Leverage new technology (such as text messages and Internet-based tools) to implement heuristics.
    • Determine where heuristics can be used in adult training programs and replace in-depth training programs with heuristics where possible; and
    • Consider how to apply heuristics in situations where the exception is the rule. The authors point to the example of savings and credit card debt. In most instances, saving a portion of one’s income is a good rule of thumb. However, when one has high credit card debt, paying off debt could be preferable to building one’s savings.

Thaler, Richard H. and Cass R. Sunstein. Nudge: Improving Decisions About Health, Wealth, and Happiness. Yale University Press, 2008.

  • This book, likely the single piece of scholarship most responsible for bringing the concept of nudges into the public consciousness, explores how a strategic “choice architecture” can help people make the best decisions.
  • Thaler and Sunstein, while advocating for the wider and more targeted use of nudges to help improve people’s lives without resorting to overly paternal regulation, look to five common nudges for lessons and inspiration:
    • The design of menus gets you to eat (and spend) more;
    • “Flies” in urinals improve, well, aim;
    • Credit card minimum payments affect repayment schedules;
    • Automatic savings programs increase savings rate; and
    • “Defaults” can improve rates of organ donation.
  • In the simplest terms, the authors propose the wider deployment of choice architectures that follow “the golden rule of libertarian paternalism: offer nudges that are most likely to help and least likely to inflict harm.”

U.K. Parliament Science and Technology Committee. “Behaviour Change.” July 2011.

  • This report from the U.K.’s Science and Technology Committee explores the government’s attempts to influence the behavior of its citizens through nudges, with a focus on comparing the effectiveness of nudges to that of regulatory interventions.
  • The author’s central conclusion is that, “non-regulatory measures used in isolation, including ‘nudges,’ are less likely to be effective. Effective policies often use a range of interventions.”
  • The report’s other major findings and recommendations are:
    • Government must invest in gathering more evidence about what measures work to influence population behaviour change;
    • They should appoint an independent Chief Social Scientist to provide them with robust and independent scientific advice;
    • The Government should take steps to implement a traffic light system of nutritional labelling on all food packaging; and
    • Current voluntary agreements with businesses in relation to public health have major failings. They are not a proportionate response to the scale of the problem of obesity and do not reflect the evidence about what will work to reduce obesity. If effective agreements cannot be reached, or if they show minimal benefit, the Government should pursue regulation.”

Selected Readings on Personal Data: Security and Use

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 personal data was originally published in 2014.

Advances in technology have greatly increased the potential for policymakers to utilize the personal data of large populations for the public good. However, the proliferation of vast stores of useful data has also given rise to a variety of legislative, political, and ethical concerns surrounding the privacy and security of citizens’ personal information, both in terms of collection and usage. Challenges regarding the governance and regulation of personal data must be addressed in order to assuage individuals’ concerns regarding the privacy, security, and use of their personal information.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Cavoukian, Ann. “Personal Data Ecosystem (PDE) – A Privacy by Design Approach to an Individual’s Pursuit of Radical Control.” Privacy by Design, October 15, 2013.

  • In this paper, Cavoukian describes the Personal Data Ecosystem (PDE), an “emerging landscape of companies and organizations that believe individuals should be in control of their personal data, and make available a growing number of tools and technologies to enable this control.” She argues that, “The right to privacy is highly compatible with the notion of PDE because it enables the individual to have a much greater degree of control – “Radical Control” – over their personal information than is currently possible today.”
  • To ensure that the PDE reaches its privacy-protection potential, Cavouckian argues that it must practice The 7 Foundational Principles of Privacy by Design:
    • Proactive not Reactive; Preventative not Remedial
    • Privacy as the Default Setting
    • Privacy Embedded into Design
    • Full Functionality – Positive-Sum, not Zero-Sum
    • End-to-End Security – Full Lifecycle Protection
    • Visibility and Transparency – Keep it Open
    • Respect for User Privacy – Keep it User-Centric

Kirkham, T., S. Winfield, S. Ravet, and S. Kellomaki. “A Personal Data Store for an Internet of Subjects.” In 2011 International Conference on Information Society (i-Society). 92–97.

  • This paper examines various factors involved in the governance of personal data online, and argues for a shift from “current service-oriented applications where often the service provider is in control of the person’s data” to a person centric architecture where the user is at the center of personal data control.
  • The paper delves into an “Internet of Subjects” concept of Personal Data Stores, and focuses on implementation of such a concept on personal data that can be characterized as either “By Me” or “About Me.”
  • The paper also presents examples of how a Personal Data Store model could allow users to both protect and present their personal data to external applications, affording them greater control.

OECD. The 2013 OECD Privacy Guidelines. 2013.

  • This report is indicative of the “important role in promoting respect for privacy as a fundamental value and a condition for the free flow of personal data across borders” played by the OECD for decades. The guidelines – revised in 2013 for the first time since being drafted in 1980 – are seen as “[t]he cornerstone of OECD work on privacy.”
  • The OECD framework is built around eight basic principles for personal data privacy and security:
    • Collection Limitation
    • Data Quality
    • Purpose Specification
    • Use Limitation
    • Security Safeguards
    • Openness
    • Individual Participation
    • Accountability

Ohm, Paul. “Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization.” UCLA Law Review 57, 1701 (2010).

  • This article explores the implications of the “astonishing ease” with which scientists have demonstrated the ability to “reidentify” or “deanonmize” supposedly anonymous personal information.
  • Rather than focusing exclusively on whether personal data is “anonymized,” Ohm offers five factors for governments and other data-handling bodies to use for assessing the risk of privacy harm: data-handling techniques, private versus public release, quantity, motive and trust.

Polonetsky, Jules and Omer Tene. “Privacy in the Age of Big Data: A Time for Big Decisions.” Stanford Law Review Online 64 (February 2, 2012): 63.

  • In this article, Tene and Polonetsky argue that, “The principles of privacy and data protection must be balanced against additional societal values such as public health, national security and law enforcement, environmental protection, and economic efficiency. A coherent framework would be based on a risk matrix, taking into account the value of different uses of data against the potential risks to individual autonomy and privacy.”
  • To achieve this balance, the authors believe that, “policymakers must address some of the most fundamental concepts of privacy law, including the definition of ‘personally identifiable information,’ the role of consent, and the principles of purpose limitation and data minimization.”

Shilton, Katie, Jeff Burke, Deborah Estrin, Ramesh Govindan, Mark Hansen, Jerry Kang, and Min Mun. “Designing the Personal Data Stream: Enabling Participatory Privacy in Mobile Personal Sensing”. TPRC, 2009.

  • This article argues that the Codes of Fair Information Practice, which have served as a model for data privacy for decades, do not take into account a world of distributed data collection, nor the realities of data mining and easy, almost uncontrolled, dissemination.
  • The authors suggest “expanding the Codes of Fair Information Practice to protect privacy in this new data reality. An adapted understanding of the Codes of Fair Information Practice can promote individuals’ engagement with their own data, and apply not only to governments and corporations, but software developers creating the data collection programs of the 21st century.”
  • In order to achieve this change in approach, the paper discusses three foundational design principles: primacy of participants, data legibility, and engagement of participants throughout the data life cycle.

Selected Readings on Big Data

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 big data was originally published in 2014.

Big Data refers to the wide-scale collection, aggregation, storage, analysis and use of data. Government is increasingly in control of a massive amount of raw data that, when analyzed and put to use, can lead to new insights on everything from public opinion to environmental concerns. The burgeoning literature on Big Data argues that it generates value by: creating transparency; enabling experimentation to discover needs, expose variability, and improve performance; segmenting populations to customize actions; replacing/supporting human decision making with automated algorithms; and innovating new business models, products and services. The insights drawn from data analysis can also be visualized in a manner that passes along relevant information, even to those without the tech savvy to understand the data on its own terms (see The GovLab Selected Readings on Data Visualization).

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Australian Government Information Management Office. The Australian Public Service Big Data Strategy: Improved Understanding through Enhanced Data-analytics Capability Strategy Report. August 2013.

  • This Big Data Strategy produced for Australian Government senior executives with responsibility for delivering services and developing policy is aimed at ingraining in government officials that the key to increasing the value of big data held by government is the effective use of analytics. Essentially, “the value of big data lies in [our] ability to extract insights and make better decisions.”
  • This positions big data as a national asset that can be used to “streamline service delivery, create opportunities for innovation, identify new service and policy approaches as well as supporting the effective delivery of existing programs across a broad range of government operations.”

Bollier, David. The Promise and Peril of Big Data. The Aspen Institute, Communications and Society Program, 2010.

  • This report captures insights from the 2009 Roundtable exploring uses of Big Data within a number of important consumer behavior and policy implication contexts.
  • The report concludes that, “Big Data presents many exciting opportunities to improve modern society. There are incalculable opportunities to make scientific research more productive, and to accelerate discovery and innovation. People can use new tools to help improve their health and well-being, and medical care can be made more efficient and effective. Government, too, has a great stake in using large databases to improve the delivery of government services and to monitor for threats to national security.
  • However, “Big Data also presents many formidable challenges to government and citizens precisely because data technologies are becoming so pervasive, intrusive and difficult to understand. How shall society protect itself against those who would misuse or abuse large databases? What new regulatory systems, private-law innovations or social practices will be capable of controlling anti-social behaviors–and how should we even define what is socially and legally acceptable when the practices enabled by Big Data are so novel and often arcane?”

Boyd, Danah and Kate Crawford. “Six Provocations for Big Data.” A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society. September 2011

  • In this paper, Boyd and Crawford raise challenges to unchecked assumptions and biases regarding big data. The paper makes a number of assertions about the “computational culture” of big data and pushes back against those who consider big data to be a panacea.
  • The authors’ provocations for big data are:
    • Automating Research Changes the Definition of Knowledge
    • Claims to Objectivity and Accuracy are Misleading
    • Big Data is not always Better Data
    • Not all Data is Equivalent
    • Just Because it is accessible doesn’t make it ethical
    • Limited Access to Big Data creates New Digital Divide

The Economist Intelligence Unit. Big Data and the Democratisation of Decisions. October 2012.

  • This report from the Economist Intelligence Unit focuses on the positive impact of big data adoption in the private sector, but its insights can also be applied to the use of big data in governance.
  • The report argues that innovation can be spurred by democratizing access to data, allowing a diversity of stakeholders to “tap data, draw lessons and make business decisions,” which in turn helps companies and institutions respond to new trends and intelligence at varying levels of decision-making power.

Manyika, James, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, and Angela Hung Byers. Big Data: The Next Frontier for Innovation, Competition, and Productivity.  McKinsey & Company. May 2011.

  • This report argues that big data “will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, and that “leaders in every sector will have to grapple with the implications of big data.” 
  • The report offers five broad ways in which using big data can create value:
    • First, big data can unlock significant value by making information transparent and usable at much higher frequency.
    • Second, as organizations create and store more transactional data in digital form, they can collect more accurate and detailed performance information on everything from product inventories to sick days, and therefore expose variability and boost performance.
    • Third, big data allows ever-narrower segmentation of customers and therefore much more precisely tailored products or services.
    • Fourth, big sophisticated analytics can substantially improve decision-making.
    • Finally, big data can be used to improve the development of the next generation of products and services.

The Partnership for Public Service and the IBM Center for The Business of Government. “From Data to Decisions II: Building an Analytics Culture.” October 17, 2012.

  • This report discusses strategies for better leveraging data analysis to aid decision-making. The authors argue that, “Organizations that are successful at launching or expanding analytics program…systematically examine their processes and activities to ensure that everything they do clearly connects to what they set out to achieve, and they use that examination to pinpoint weaknesses or areas for improvement.”
  • While the report features many strategies for government decisions-makers, the central recommendation is that, “leaders incorporate analytics as a way of doing business, making data-driven decisions transparent and a fundamental approach to day-to-day management. When an analytics culture is built openly, and the lessons are applied routinely and shared widely, an agency can embed valuable management practices in its DNA, to the mutual benet of the agency and the public it serves.”

TechAmerica Foundation’s Federal Big Data Commission. “Demystifying Big Data: A Practical Guide to Transforming the Business of Government.” 2013.

  • This report presents key big data imperatives that government agencies must address, the challenges and the opportunities posed by the growing volume of data and the value Big Data can provide. The discussion touches on the value of big data to businesses and organizational mission, presents case study examples of big data applications, technical underpinnings and public policy applications.
  • The authors argue that new digital information, “effectively captured, managed and analyzed, has the power to change every industry including cyber security, healthcare, transportation, education, and the sciences.” To ensure that this opportunity is realized, the report proposes a detailed big data strategy framework with the following steps: define, assess, plan, execute and review.

World Economic Forum. “Big Data, Big Impact: New Possibilities for International Development.” 2012.

  • This report examines the potential for channeling the “flood of data created every day by the interactions of billions of people using computers, GPS devices, cell phones, and medical devices” into “actionable information that can be used to identify needs, provide services, and predict and prevent crises for the benefit of low-income populations”
  • The report argues that, “To realise the mutual benefits of creating an environment for sharing mobile-generated data, all ecosystem actors must commit to active and open participation. Governments can take the lead in setting policy and legal frameworks that protect individuals and require contractors to make their data public. Development organisations can continue supporting governments and demonstrating both the public good and the business value that data philanthropy can deliver. And the private sector can move faster to create mechanisms for the sharing data that can benefit the public.”

Selected Readings on Data Visualization

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 data visualization was originally published in 2013.

Data visualization is a response to the ever-increasing amount of  information in the world. With big data, informatics and predictive analytics, we have an unprecedented opportunity to revolutionize policy-making. Yet data by itself can be overwhelming. New tools and techniques for visualizing information can help policymakers clearly articulate insights drawn from data. Moreover, the rise of open data is enabling those outside of government to create informative and visually arresting representations of public information that can be used to support decision-making by those inside or outside governing institutions.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Duke, D.J., K.W. Brodlie, D.A. Duce and I. Herman. “Do You See What I Mean? [Data Visualization].” IEEE Computer Graphics and Applications 25, no. 3 (2005): 6–9.

  • In this paper, the authors argue that a more systematic ontology for data visualization to ensure the successful communication of meaning. “Visualization begins when someone has data that they wish to explore and interpret; the data are encoded as input to a visualization system, which may in its turn interact with other systems to produce a representation. This is communicated back to the user(s), who have to assess this against their goals and knowledge, possibly leading to further cycles of activity. Each phase of this process involves communication between two parties. For this to succeed, those parties must share a common language with an agreed meaning.”
  • That authors “believe that now is the right time to consider an ontology for visualization,” and “as visualization move from just a private enterprise involving data and tools owned by a research team into a public activity using shared data repositories, computational grids, and distributed collaboration…[m]eaning becomes a shared responsibility and resource. Through the Semantic Web, there is both the means and motivation to develop a shared picture of what we see when we turn and look within our own field.”

Friendly, Michael. “A Brief History of Data Visualization.” In Handbook of Data Visualization, 15–56. Springer Handbooks Comp.Statistics. Springer Berlin Heidelberg, 2008.

  • In this paper, Friendly explores the “deep roots” of modern data visualization. “These roots reach into the histories of the earliest map making and visual depiction, and later into thematic cartography, statistics and statistical graphics, medicine and other fields. Along the way, developments in technologies (printing, reproduction), mathematical theory and practice, and empirical observation and recording enabled the wider use of graphics and new advances in form and content.”
  • Just as the general the visualization of data is far from a new practice, Friendly shows that the graphical representation of government information has a similarly long history. “The collection, organization and dissemination of official government statistics on population, trade and commerce, social, moral and political issues became widespread in most of the countries of Europe from about 1825 to 1870. Reports containing data graphics were published with some regularity in France, Germany, Hungary and Finland, and with tabular displays in Sweden, Holland, Italy and elsewhere.”

Graves, Alvaro and James Hendler. “Visualization Tools for Open Government Data.” In Proceedings of the 14th Annual International Conference on Digital Government Research, 136–145. Dg.o ’13. New York, NY, USA: ACM, 2013.

  • In this paper, the authors argue that, “there is a gap between current Open Data initiatives and an important part of the stakeholders of the Open Government Data Ecosystem.” As it stands, “there is an important portion of the population who could benefit from the use of OGD but who cannot do so because they cannot perform the essential operations needed to collect, process, merge, and make sense of the data. The reasons behind these problems are multiple, the most critical one being a fundamental lack of expertise and technical knowledge. We propose the use of visualizations to alleviate this situation. Visualizations provide a simple mechanism to understand and communicate large amounts of data.”
  • The authors also describe a prototype of a tool to create visualizations based on OGD with the following capabilities:
    • Facilitate visualization creation
    • Exploratory mechanisms
    • Viralization and sharing
    • Repurpose of visualizations

Hidalgo, César A. “Graphical Statistical Methods for the Representation of the Human Development Index and Its Components.” United Nations Development Programme Human Development Reports, September 2010.

  • In this paper for the United Nations Human Development Programme, Hidalgo argues that “graphical statistical methods could be used to help communicate complex data and concepts through universal cognitive channels that are heretofore underused in the development literature.”
  • To support his argument, representations are provided that “show how graphical methods can be used to (i) compare changes in the level of development experienced by countries (ii) make it easier to understand how these changes are tied to each one of the components of the Human Development Index (iii) understand the evolution of the distribution of countries according to HDI and its components and (iv) teach and create awareness about human development by using iconographic representations that can be used to graphically narrate the story of countries and regions.”

Stowers, Genie. “The Use of Data Visualization in Government.” IBM Center for The Business of Government, Using Technology Series, 2013.

  • This report seeks “to help public sector managers understand one of the more important areas of data analysis today — data visualization. Data visualizations are more sophisticated, fuller graphic designs than the traditional spreadsheet charts, usually with more than two variables and, typically, incorporating interactive features.”
  • Stowers also offers numerous examples of “visualizations that include geographical and health data, or population and time data, or financial data represented in both absolute and relative terms — and each communicates more than simply the data that underpin it. In addition to these many examples of visualizations, the report discusses the history of this technique, and describes tools that can be used to create visualizations from many different kinds of data sets.”

Selected Readings on Crowdsourcing Data

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 crowdsourcing data was originally published in 2013.

As institutions seek to improve decision-making through data and put public data to use to improve the lives of citizens, new tools and projects are allowing citizens to play a role in both the collection and utilization of data. Participatory sensing and other citizen data collection initiatives, notably in the realm of disaster response, are allowing citizens to crowdsource important data, often using smartphones, that would be either impossible or burdensomely time-consuming for institutions to collect themselves. Civic hacking, often performed in hackathon events, on the other hand, is a growing trend in which governments encourage citizens to transform data from government and other sources into useful tools to benefit the public good.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Baraniuk, Chris. “Power Politechs.” New Scientist 218, no. 2923 (June 29, 2013): 36–39.

  • In this article, Baraniuk discusses civic hackers, “an army of volunteer coders who are challenging preconceptions about hacking and changing the way your government operates. In a time of plummeting budgets and efficiency drives, those in power have realised they needn’t always rely on slow-moving, expensive outsourcing and development to improve public services. Instead, they can consider running a hackathon, at which tech-savvy members of the public come together to create apps and other digital tools that promise to enhace the provision of healthcare, schools or policing.”
  • While recognizing that “civic hacking has established a pedigree that demonstrates its potential for positive impact,” Baraniuk argues that a “more rigorous debate over how this activity should evolve, or how authorities ought to engage in it” is needed.

Barnett, Brandon, Muki Hansteen Izora, and Jose Sia. “Civic Hackathon Challenges Design Principles: Making Data Relevant and Useful for Individuals and Communities.” Hack for Change,

  • In this paper, researchers from Intel Labs offer “guiding principles to support the efforts of local civic hackathon organizers and participants as they seek to design actionable challenges and build useful solutions that will positively benefit their communities.”
  • The authors proposed design principles are:
    • Focus on the specific needs and concerns of people or institutions in the local community. Solve their problems and challenges by combining different kinds of data.
    • Seek out data far and wide (local, municipal, state, institutional, non-profits, companies) that is relevant to the concern or problem you are trying to solve.
    • Keep it simple! This can’t be overstated. Focus [on] making data easily understood and useful to those who will use your application or service.
    • Enable users to collaborate and form new communities and alliances around data.

Buhrmester, Michael, Tracy Kwang, and Samuel D. Gosling. “Amazon’s Mechanical Turk A New Source of Inexpensive, Yet High-Quality, Data?” Perspectives on Psychological Science 6, no. 1 (January 1, 2011): 3–5.

  • This article examines the capability of Amazon’s Mechanical Turk to act a source of data for researchers, in addition to its traditional role as a microtasking platform.
  • The authors examine the demographics of MTurkers and find that “MTurk participants are slightly more demographically diverse than are standard Internet samples and are significantly more diverse than typical American college samples; (b) participation is affected by compensation rate and task length, but participants can still be recruited rapidly and inexpensively; (c) realistic compensation rates do not affect data quality; and (d) the data obtained are at least as reliable as those obtained via traditional methods.”
  • The paper concludes that, just as MTurk can be a strong tool for crowdsourcing tasks, data derived from MTurk can be high quality while also being inexpensive and obtained rapidly.

Goodchild, Michael F., and J. Alan Glennon. “Crowdsourcing Geographic Information for Disaster Response: a Research Frontier.” International Journal of Digital Earth 3, no. 3 (2010): 231–241.

  • This article examines issues of data quality in the face of the new phenomenon of geographic information being generated by citizens, in order to examine whether this data can play a role in emergency management.
  • The authors argue that “[d]ata quality is a major concern, since volunteered information is asserted and carries none of the assurances that lead to trust in officially created data.”
  • Due to the fact that time is crucial during emergencies, the authors argue that, “the risks associated with volunteered information are often outweighed by the benefits of its use.”
  • The paper examines four wildfires in Santa Barbara in 2007-2009 to discuss current challenges with volunteered geographical data, and concludes that further research is required to answer how volunteer citizens can be used to provide effective assistance to emergency managers and responders.

Hudson-Smith, Andrew, Michael Batty, Andrew Crooks, and Richard Milton. “Mapping for the Masses Accessing Web 2.0 Through Crowdsourcing.” Social Science Computer Review 27, no. 4 (November 1, 2009): 524–538.

  • This article describes the way in which “we are harnessing the power of web 2.0 technologies to create new approaches to collecting, mapping, and sharing geocoded data.”
  • The authors examine GMapCreator and MapTube, which allow users to do a range of map-related functions such as create new maps, archive existing maps, and share or produce bottom-up maps through crowdsourcing.
  • They conclude that “these tools are helping to define a neogeography that is essentially ‘mapping for the masses,’ while noting that there are many issues of quality, accuracy, copyright, and trust that will influence the impact of these tools on map-based communication.”

Kanhere, Salil S. “Participatory Sensing: Crowdsourcing Data from Mobile Smartphones in Urban Spaces.” In Distributed Computing and Internet Technology, edited by Chittaranjan Hota and Pradip K. Srimani, 19–26. Lecture Notes in Computer Science 7753. Springer Berlin Heidelberg. 2013.

  • This paper provides a comprehensive overview of participatory sensing — a “new paradigm for monitoring the urban landscape” in which “ordinary citizens can collect multi-modal data streams from the surrounding environment using their mobile devices and share the same using existing communications infrastructure.”
  • In addition to examining a number of innovative applications of participatory sensing, Kanhere outlines the following key research challenges:
    • Dealing with incomplete samples
    •  Inferring user context
    • Protecting user privacy
    • Evaluating data trustworthiness
    • Conserving energy

Selected Readings on Smart Disclosure

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 smart disclosure was originally published in 2013.

While much attention is paid to open data, data transparency need not be managed by a simple On/Off switch: It’s often desirable to make specific data available to the public or individuals in targeted ways. A prime example is the use of government data in Smart Disclosure, which provides consumers with data they need to make difficult marketplace choices in health care, financial services, and other important areas. Governments collect two kinds of data that can be used for Smart Disclosure: First, governments collect information on services of high interest to consumers, and are increasingly releasing this kind of data to the public. In the United States, for example, the Department of Health and Human Services collects and releases online data on health insurance options, while the Department of Education helps consumers understand the true cost (after financial aid) of different colleges. Second, state, local, or national governments hold information on consumers themselves that can be useful to them. In the U.S., for example, the Blue Button program was launched to help veterans easily access their own medical records.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Better Choices: Better Deals Report on Progress in the Consumer Empowerment Strategy. Progress Report. Consumer Empowerment Strategy. United Kingdom: Department for Business Innovation & Skills, December 2012.

  • The report details the progress made through the United Kingdom’s consumer empowerment strategy, Better Choices: Better Deals. The plan seeks to mitigate knowledge imbalances through information disclosure programs and targeted nudges.
  • The empowerment strategy’s four sections demonstrate the potential benefits of Smart Disclosure: 1. The power of information; 2. The power of the crowd; 3. Helping the vulnerable; and 4. A new approach to Government working with business.
Braunstein, Mark L.,. “Empowering the Patient.” In Health Informatics in the Cloud, 67–79. Springer Briefs in Computer Science. Springer New York Heidelberg Dordrecht London, 2013.
  • This book discusses the application of computing to healthcare delivery, public health and community based clinical research.
  • Braunstein asks and seeks to answer critical questions such as: Who should make the case for smart disclosure when the needs of consumers are not being met? What role do non-profits play in the conversation on smart disclosure especially when existing systems (or lack thereof) of information provision do not work or are unsafe?

Brodi, Elisa. “Product-Attribute Information” and “Product-Use Information”: Smart Disclosure and New Policy Implications for Consumers’ Protection. SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, September 4, 2012.

  • This paper from the Research Area of the Bank of Italy’s Law and Economics Department “surveys the literature on product use information and analyzes whether and to what extent Italian regulator is trying to ensure consumers’ awareness as to their use pattern.” Rather than focusing on the type of information governments can release to citizens, Brodi proposes that governments require private companies to provide valuable use pattern information to citizens to inform decision-making.
  • The form of regulation proposed by Brodi and other proponents “is based on a basic concept: consumers can be protected if companies are forced to disclose data on the customers’ consumption history through electronic files.”
National Science and Technology Council. Smart Disclosure and Consumer Decision Making: Report of the Task Force on Smart Disclosure. Task Force on Smart Disclosure: Information and Efficiency in Consumer Markets. Washington, DC: United States Government: Executive Office of the President, May 30, 2013.
    • This inter-agency report is a comprehensive description of smart disclosure approaches being used across the Federal Government. The report not only highlights the importance of making data available to consumers but also to innovators to build better options for consumers.
  • In addition to providing context about government policies that guide smart disclosure initiatives, the report raises questions about what parties have influence in this space.

“Policies in Practice: The Download Capability.” Markle Connecting for Health Work Group on Consumer Engagement, August 2010.

  • This report from the Markle Connecting for Health Work Group on Consumer Engagement — the creator of the Blue Button system for downloading personal health records — features a “set of privacy and security practices to help people download their electronic health records.”
  • To help make health information easily accessible for all citizens, the report lists a number of important steps:
    • Make the download capability a common practice
    • Implement sound policies and practices to protect individuals and their information
    • Collaborate on sample data sets
    • Support the download capability as part of Meaningful Use and qualified or certified health IT
    • Include the download capability in procurement requirements.
  • The report also describes the rationale for the development of the Blue Button — perhaps the best known example of Smart Disclosure currently in existence — and the targeted release of health information in general:
    • Individual access to information is rooted in fair information principles and law
    • Patients need and want the information
    • The download capability would encourage innovation
    • A download capability frees data sources from having to make many decisions about the user interface
    • A download capability would hasten the path to standards and interoperability.
Sayogo, Djoko Sigit, and Theresa A. Pardo. “Understanding Smart Data Disclosure Policy Success: The Case of Green Button.” In Proceedings of the 14th Annual International Conference on Digital Government Research, 72–81. New York: ACM New York, NY, USA, 2013.
  • This paper from the Proceedings of the 14th Annual International Conference on Digital Government Research explores the implementation of the Green Button Initiative, analyzing qualitative data from interviews with experts involved in Green Button development and implementation.
  • Moving beyond the specifics of the Green Button initiative, the authors raise questions on the motivations and success factors facilitating successful collaboration between public and private organizations to support smart disclosure policy.

Thaler, Richard H., and Will Tucker. “Smarter Information, Smarter Consumers.” Harvard Business Review January – February 2013. The Big Idea.

  • In this article, Thaler and Tucker make three key observations regarding the challenges related to smart disclosure:
    • “We are constantly confronted with information that is highly important but extremely hard to navigate or understand.”
    • “Repeated attempts to improve disclosure, including efforts to translate complex contracts into “plain English,” have met with only modest success.”
    • “There is a fundamental difficulty of explaining anything complex in simple terms. Most people find it difficult to write instructions explaining how to tie a pair of shoelaces.