House Bill Raises Questions about Crowdsourcing

Curated on Posted on by Stefaan Verhulst

Anne Bowser for Commons Lab (Wilson Center):”A new bill in the House is raising some key questions about how crowdsourcing is understood by scientists, government agencies, policymakers and the public at large.
Robin Bravender’s recent article in Environment & Energy Daily, “House Republicans Push Crowdsourcing on Agency Science,” (subscription required) neatly summarizes the debate around H.R. 4012, a bill introduced to the House of Representatives earlier this month. The House Science, Space and Technology Committe earlier this week held a hearing on the bill, which could see a committee vote as early as next month.
Dubbed the “Secret Science Reform Act of 2014,” the bill prohibits the Environmental Protection Agency (EPA) from “proposing, finalizing, or disseminating regulations or assessments based upon science that is not transparent or reproducible.” If the bill is passed, EPA would be unable to base assessments or regulations on any information not “publicly available in a manner that is sufficient for independent analysis.” This would include all information published in scholarly journals based on data that is not available as open source.
The bill is based on the premise that forcing EPA to use public data will inspire greater transparency by allowing “the crowd” to conduct independent analysis and interpretation. While the premise of involving the public in scientific research is sound, this characterization of crowdsourcing as a process separate from traditional scientific research is deeply problematic.
This division contrasts the current practices of many researchers, who use crowdsourcing to directly involve the public in scientific processes. Galaxy Zoo, for example, enlists digital volunteers (called “citizen scientists”) help classify more than 40 million photographs of galaxies taken by the Hubble Telescope. These crowdsourced morphological classifications are a powerful form of data analysis, a key aspect of the scientific process. Galaxy Zoo then publishes a catalogue of these classifications as an open-source data set. And the data reduction techniques and measures of confidence and bias for the data catalogue are documented in MNRAS, a peer-reviewed journal. A recent Google Scholar search shows that the data set published in MNRAS has been cited a remarkable 121 times.
As this example illustrates, crowdsourcing is often embedded in the process of formal scientific research. But prior to being published in a scientific journal, the crowdsourced contributions of non-professional volunteers are subject to the scrutiny of professional scientists through the rigorous process of peer review. Because peer review was designed as an institution to ensure objective and unbiased research, peer-reviewed scientific work is widely accepted as the best source of information for any science-based decision.
Separating crowdsourcing from the peer review process, as this legislation intends, means that there will be no formal filters in place to ensure that open data will not be abused by special interests. Ellen Silbergeld, a professor at John Hopkins University who testified at the hearing this week, made exactly this point when she pointed to data manipulation commonly practiced by tobacco lobbyists in the United States.
Contributing to scientific research is one goal of crowdsourcing for science. Involving the public in scientific research also increases volunteer understanding of research topics and the scientific process and inspires heightened community engagement. These goals are supported by President Obama’s Second Open Government National Action Plan, which calls for “increased crowdsourcing and citizen science programs” to support “an informed and active citizenry.” But H.R. 4012 does not support these goals. Rather, this legislation could further degrade the public’s understanding of science by encouraging the public to distrust professional scientists rather than collaborate with them.
Crowdsourcing benefits organizations by bringing in the unique expertise held by external volunteers, which can augment and enhance the traditional scientific process. In return, these volunteers benefit from exposure to new and exciting processes, such as scientific research. This mutually beneficial relationship depends on collaboration, not opposition. Supporting an antagonistic relationship between science-based organizations like the EPA and members of “the crowd” will benefit neither institutions, nor volunteers, nor the country as a whole.“
 

What makes a good API?

Curated on Posted on by Stefaan Verhulst

Joshua Tauberer’s Blog: “There comes a time in every dataset’s life when it wants to become an API. That might be because of consumer demand or an executive order. How are you going to make a good one?…
Let’s take the common case where you have a relatively static, large dataset that you want to provide read-only access to. Here are 19 common attributes of good APIs for this situation. …
Granular Access. If the user wanted the whole thing they’d download it in bulk, so an API must be good at providing access to the most granular level practical for data users (h/t Ben Balter for the wording on that). When the data comes from a table, this usually means the ability to read a small slice of it using filters, sorting, and paging (limit/offset), the ability to get a single row by identifying it with a persistent, unique identifier (usually a numeric ID), and the ability to select just which fields should be included in the result output (good for optimizing bandwidth in mobile apps, h/t Eric Mill). (But see “intents” below.)
Deep Filtering. An API should be good at needle-in-haystack problems. Full text search is hard to do, so an API that can do it relieves a big burden for developers — if your API has any big text fields. Filters that can span relations or cross tables (i.e. joins) can be very helpful as well. But don’t go overboard. (Again, see “intents” below.)
Typed Values. Response data should be typed. That means that whether a field’s value is an integer, text, list, floating-point number, dictionary, null, or date should be encoded as a part of the value itself. JSON and XML with XSD are good at this. CSV and plain XML, on the other hand, are totally untyped. Types must be strictly enforced. Columns must choose a data type and stick with it, no exceptions. When encoding other sorts of data as text, the values must all absolutely be valid according to the most narrow regular expression that you can make. Provide that regular expression to the API users in documentation.
Normalize Tables, Then Denormalize. Normalization is the process of removing redundancy from tables by making multiple tables. You should do that. Have lots of primary keys that link related tables together. But… then… denormalize. The bottleneck of most APIs isn’t disk space but speed. Queries over denormalized tables are much faster than writing queries with JOINs over multiple tables. It’s faster to get data if it’s all in one response than if the user has to issue multiple API calls (across multiple tables) to get it. You still have to normalize first, though. Denormalized data is hard to understand and hard to maintain.
Be RESTful, And More. ”REST” is a set of practices. There are whole books on this. Here it is in short. Every object named in the data (often that’s the rows of the table) gets its own URL. Hierarchical relationships in the data are turned into nice URL paths with slashes. Put the URLs of related resources in output too (HATEOAS, h/t Ed Summers). Use HTTP GET and normal query string processing (a=x&b=y) for filtering, sorting, and paging. The idea of REST is that these are patterns already familiar to developers, and reusing existing patterns — rather than making up entirely new ones — makes the API more understandable and reusable. Also, use HTTPS for everything (h/t Eric Mill), and provide the API’s status as an API itself possibly at the root URL of the API’s URL space (h/t Eric Mill again).
….
Never Require Registration. Don’t have authentication on your API to keep people out! In fact, having a requirement of registration may contradict other guidelines (such as the 8 Principles of Open Government Data). If you do use an API key, make it optional. A non-authenticated tier lets developers quickly test the waters, and that is really important for getting developers in the door, and, again, it may be important for policy reasons as well. You can have a carrot to incentivize voluntary authentication: raise the rate limit for authenticated queries, for instance. (h/t Ben Balter)
Interactive Documentation. An API explorer is a web page that users can visit to learn how to build API queries and see results for test queries in real time. It’s an interactive browser tool, like interactive documentation. Relatedly, an “explain mode” in queries, which instead of returning results says what the query was and how it would be processed, can help developers understand how to use the API (h/t Eric Mill).
Developer Community. Life is hard. Coding is hard. The subject matter your data is about is probably very complex. Don’t make your API users wade into your API alone. Bring the users together, bring them to you, and sometimes go to them. Let them ask questions and report issues in a public place (such as github). You may find that users will answer other users’ questions. Wouldn’t that be great? Have a mailing list for longer questions and discussion about the future of the API. Gather case studies of how people are using the API and show them off to the other users. It’s not a requirement that the API owner participates heavily in the developer community — just having a hub is very helpful — but of course the more participation the better.
Create Virtuous Cycles. Create an environment around the API that make the data and API stronger. For instance, other individuals within your organization who need the data should go through the public API to the greatest extent possible. Those users are experts and will help you make a better API, once they realize they benefit from it too. Create a feedback loop around the data, meaning find a way for API users to submit reports of data errors and have a process to carry out data updates, if applicable and possible. Do this in the public as much as possible so that others see they can also join the virtuous cycle.”

Selected Readings on Behavioral Economics: Nudges

Curated on Posted on by Andrew Young

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 Health – a 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 Change – an 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. http://bit.ly/LFmC5s.

  • 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. http://bit.ly/1eFP16J.

  • 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. https://bit.ly/2QytRmf.

  • 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. https://bit.ly/2UDC5YK.

  • 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. https://bit.ly/2kNXroe.

  • 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. http://bit.ly/1cbYv5j.

  • 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 Big Data

Curated on Posted on by Andrew Young

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. http://bit.ly/17hs2xY.

  • 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. http://bit.ly/1a3hBIA.

  • 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. http://bit.ly/1jJstmz.

  • 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. http://bit.ly/17MpH8L.

  • 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. http://bit.ly/18Q5CSl.

  • 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. https://bit.ly/2EbBTMg.

  • 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. http://bit.ly/1aalUrs.

  • 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. http://bit.ly/17hrTKW.

  • 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.”

Citizen roles in civic problem-solving and innovation

Curated on Posted on by Stefaan Verhulst

Satish Nambisan: “Can citizens be fruitfully engaged in solving civic problems? Recent initiatives in cities such as Boston (Citizens Connect), Chicago (Smart Chicago Collaborative), San Francisco (ImproveSF) and New York (NYC BigApps) indicate that citizens can be involved in not just identifying and reporting civic problems but in conceptualizing, designing and developing, and implementing solutions as well.
The availability of new technologies (e.g. social media) has radically lowered the cost of collaboration and the “distance” between government agencies and the citizens they serve. Further involving citizens — who are often closest to and possess unique knowledge about the problems they face — makes a lot of sense given the increasing complexity of the problems that need to be addressed.
A recent research report that I wrote highlights four distinct roles that citizens can play in civic innovation and problem-solving.
As explorer, citizens can identify and report emerging and existing civic problems. For example, Boston’s Citizen Connect initiative enables citizens to use specially built smartphone apps to report minor and major civic problems (from potholes and graffiti to water/air pollution). Closer to home, both Wisconsin and Minnesota have engaged thousands of citizen volunteers in collecting data on the quality of water in their neighborhood streams, lakes and rivers (the data thus gathered are analyzed by the state pollution control agency). Citizens also can be engaged in data analysis. The N.Y.-based Datakind initiative involves citizen volunteers using their data analysis skills to mine public data in health, education, environment, etc., to identify important civic issues and problems.
As “ideator,”citizens can conceptualize novel solutions to well-defined problems in public services. For example, the federal government’s Challenge.gov initiative employs online contests and competitions to solicit innovative ideas from citizens to solve important civic problems. Such “crowdsourcing” initiatives also have been launched at the county, city and state levels (e.g. Prize2theFuture competition in Birmingham, Ala.; ImproveSF in San Francisco).
As designer, citizens can design and/or develop implementable solutions to well-defined civic problems. For example, as part of initiatives such as NYC Big Apps and Apps for California, citizens have designed mobile apps to address specific issues such as public parking availability, public transport delays, etc. Similarly, the City Repair project in Portland, Ore., focuses on engaging citizens in co-designing and creatively transforming public places into sustainable community-oriented urban spaces.
As diffuser,citizens can play the role of a change agent and directly support the widespread adoption of civic innovations and solutions. For example, in recent years, physicians interacting with peer physicians in dedicated online communities have assisted federal and state government agencies in diffusing health technology innovations such as electronic medical record systems (EMRs).
In the private sector, companies across industries have benefited much from engaging with their customers in innovation. Evidence so far suggests that the benefits from citizen engagement in civic problem-solving are equally tangible, valuable and varied. However, the challenges associated with organizing such citizen co-creation initiatives are also many and imply the need for government agencies to adopt an intentional, well-thought-out approach….”

Enhancing Social Innovation by Rethinking Collaboration, Leadership and Public Governance

Curated on Posted on by Stefaan Verhulst

New paper by Professors Eva Sørensen & Jacob Torfing: “It is widely recognized that public innovation is the intelligent alternative to blind across-the-board-cuts in times of shrinking budgets, and that innovation may help to break policy deadlocks and adjust welfare services to new and changing demands. At the same time, there is growing evidence that multi-actor collaboration in networks, partnerships and interorganizational teams can spur public innovation (Sørensen and Torfing, 2011). The involvement of different public and private actors in public innovation processes improves the understanding of the problem or challenge at hand and brings forth new ideas and proposals. It also ensures that the needs of users, citizens and civil society organizations are taken into account when innovative solutions are selected, tested and implemented.
While a lot of public innovation continues to be driven by particular public employees and managers, there seems to be a significant surge in collaborative forms of innovation that cut across the institutional and organization boundaries within the public sector and involve a plethora of private actors with relevant innovation assets. Indeed, the enhancement of collaborative innovation has be come a key aspiration of many public organizations around the world. However, if we fail to develop a more precise and sophisticated understanding of the concepts of ‘innovation’ and ‘collaboration’, we risk that both terms are reduced to empty and tiresome buzzwords that will not last to the end of the season. Moreover, in reality, collaborative and innovative processes are difficult to trigger and sustain without proper innovation management and a supporting cultural and institutional environment. This insight calls for further reflections on the role of public leadership and management and for a transformation of the entire system of public governing.
Hence, in order to spur collaborative innovation in the public sector, we need to clarify the basic terms of the debate and explore how collaborative innovation can be enhanced by new forms of innovation management and new forms of public governing. To this end, we shall first define the notions of innovation and public innovation and discuss the relation between public innovation and social innovation in order to better understand the purposes of different forms of innovation.
We shall then seek to clarify the notion of collaboration and pinpoint why and how collaboration enhances public innovation. Next, we shall offer some theoretical and practical reflections about how public leaders and managers can advance collaborative innovation. Finally, we shall argue that the enhancement of collaborative forms of social innovation calls for a transformation of the system of public governing that shifts the balance from New Public Management towards New Public Governance.”

Safety Datapalooza Shows Power of Data.gov Communities

Curated on Posted on by Stefaan Verhulst

Lisa Nelson at DigitalGov: “The White House Office of Public Engagement held the first Safety Datapalooza illustrating the power of Data.gov communities. Federal Chief Technology Officer Todd Park and Deputy Secretary of Transportation John Porcari hosted the event, which touted the data available on Safety.Data.gov and the community of innovators using it to make effective tools for consumers.
The event showcased many of the  tools that have been produced as a result of  opening this safety data including:

  • PulsePoint, from the San Ramon Fire Protection District, a lifesaving mobile app that allows CPR-trained volunteers to be notified if someone nearby is in need of emergency assistance;
  • Commute and crime maps, from Trulia, allow home buyers to choose their new residence based on two important everyday factors; and
  • Hurricane App, from the American Red Cross, to monitor storm conditions, prepare your family and home, find help, and let others know you’re safe even if the power is out;

Safety data is far from alone in generating innovative ideas and gathering a community of developers and entrepreneurs, Data.gov currently has 16 different topically diverse communities on land and sea — the Cities and Oceans communities being two such examples. Data.gov’s communities are a virtual meeting spot for interested parties across government, academia and industry to come together and put the data to use. Data.gov enables a whole set of tools to make these communities come to life: apps, blogs, challenges, forums, ranking, rating and wikis.
For a summary of the Safety Datapalooza visit Transportation’s “Fast Lane” blog.”

EPA Launches New Citizen Science Website

Curated on Posted on by Stefaan Verhulst

Press Release: “The U.S. Environmental Protection Agency has revamped its Citizen Science website to provide new resources and success stories to assist the public in conducting scientific research and collecting data to better understand their local environment and address issues of concern. The website can be found at www.epa.gov/region2/citizenscience.
“Citizen Science is an increasingly important part of EPA’s commitment to using sound science and technology to protect people’s health and safeguard the environment,” said Judith A. Enck, EPA Regional Administrator. “The EPA encourages the public to use the new website as a tool in furthering their scientific investigations and developing solutions to pollution problems.”
The updated website now offers detailed information about air, water and soil monitoring, including recommended types of equipment and resources for conducting investigations. It also includes case studies and videotapes that showcase successful citizen science projects in New York and New Jersey, provides funding opportunities, quality assurance information and workshops and webinars.”

The Emergence Of The Connected City

Curated on Posted on by Stefaan Verhulst

Glen Martin at Forbes: “If the modern city is a symbol for randomness — even chaos — the city of the near future is shaping up along opposite metaphorical lines. The urban environment is evolving rapidly, and a model is emerging that is more efficient, more functional, more — connected, in a word.
This will affect how we work, commute, and spend our leisure time. It may well influence how we relate to one another, and how we think about the world. Certainly, our lives will be augmented: better public transportation systems, quicker responses from police and fire services, more efficient energy consumption. But there could also be dystopian impacts: dwindling privacy and imperiled personal data. We could even lose some of the ferment that makes large cities such compelling places to live; chaos is stressful, but it can also be stimulating.
It will come as no surprise that converging digital technologies are driving cities toward connectedness. When conjoined, ISM band transmitters, sensors, and smart phone apps form networks that can make cities pretty darn smart — and maybe more hygienic. This latter possibility, at least, is proposed by Samrat Saha of the DCI Marketing Group in Milwaukee. Saha suggests “crowdsourcing” municipal trash pick-up via BLE modules, proximity sensors and custom mobile device apps.
“My idea is a bit tongue in cheek, but I think it shows how we can gain real efficiencies in urban settings by gathering information and relaying it via the Cloud,” Saha says. “First, you deploy sensors in garbage cans. Each can provides a rough estimate of its fill level and communicates that to a BLE 112 Module.”
As pedestrians who have downloaded custom “garbage can” apps on their BLE-capable iPhone or Android devices pass by, continues Saha, the information is collected from the module and relayed to a Cloud-hosted service for action — garbage pick-up for brimming cans, in other words. The process will also allow planners to optimize trash can placement, redeploying receptacles from areas where need is minimal to more garbage-rich environs….
Garbage can connectivity has larger implications than just, well, garbage. Brett Goldstein, the former Chief Data and Information Officer for the City of Chicago and a current lecturer at the University of Chicago, says city officials found clear patterns between damaged or missing garbage cans and rat problems.
“We found areas that showed an abnormal increase in missing or broken receptacles started getting rat outbreaks around seven days later,” Goldstein said. “That’s very valuable information. If you have sensors on enough garbage cans, you could get a temporal leading edge, allowing a response before there’s a problem. In urban planning, you want to emphasize prevention, not reaction.”
Such Cloud-based app-centric systems aren’t suited only for trash receptacles, of course. Companies such as Johnson Controls are now marketing apps for smart buildings — the base component for smart cities. (Johnson’s Metasys management system, for example, feeds data to its app-based Paoptix Platform to maximize energy efficiency in buildings.) In short, instrumented cities already are emerging. Smart nodes — including augmented buildings, utilities and public service systems — are establishing connections with one another, like axon-linked neurons.
But Goldstein, who was best known in Chicago for putting tremendous quantities of the city’s data online for public access, emphasizes instrumented cities are still in their infancy, and that their successful development will depend on how well we “parent” them.
“I hesitate to refer to ‘Big Data,’ because I think it’s a terribly overused term,” Goldstein said. “But the fact remains that we can now capture huge amounts of urban data. So, to me, the biggest challenge is transitioning the fields — merging public policy with computer science into functional networks.”…”

E-government research in the United States

Curated on Posted on by Stefaan Verhulst

Paper by JT Snead, E Wright in Government Information Quarterly: “The purpose of this exploratory study is to review scholarly publications and assess egovernment research efforts as a field of study specific to the United States e-government environment. Study results reveal that researchers who focus on the U.S. e-government environment assess specific e-government topics at the federal, state, and local levels; however, there are gaps in the research efforts by topic areas and across different levels of government, which indicate opportunities for future areas of research. Results also find that a multitude of methodology approaches are used to assess e-government. Issues, however, exist that include lack of or weak presentations of methodologies in publications, few studies include multi-method evaluation approaches for data collection and analysis efforts, and few studies take a theory-based approach to understanding the U.S. e-government environment.”