Not just the government’s playbook


at Radar: “Whenever I hear someone say that “government should be run like a business,” my first reaction is “do you know how badly most businesses are run?” Seriously. I do not want my government to run like a business — whether it’s like the local restaurants that pop up and die like wildflowers, or megacorporations that sell broken products, whether financial, automotive, or otherwise.
If you read some elements of the press, it’s easy to think that healthcare.gov is the first time that a website failed. And it’s easy to forget that a large non-government website was failing, in surprisingly similar ways, at roughly the same time. I’m talking about the Common App site, the site high school seniors use to apply to most colleges in the US. There were problems with pasting in essays, problems with accepting payments, problems with the app mysteriously hanging for hours, and more.
 
I don’t mean to pick on Common App; you’ve no doubt had your own experience with woefully bad online services: insurance companies, Internet providers, even online shopping. I’ve seen my doctor swear at the Epic electronic medical records application when it crashed repeatedly during an appointment. So, yes, the government builds bad software. So does private enterprise. All the time. According to TechRepublic, 68% of all software projects fail. We can debate why, and we can even debate the numbers, but there’s clearly a lot of software #fail out there — in industry, in non-profits, and yes, in government.
With that in mind, it’s worth looking at the U.S. CIO’s Digital Services Playbook. It’s not ideal, and in many respects, its flaws reveal its origins. But it’s pretty good, and should certainly serve as a model, not just for the government, but for any organization, small or large, that is building an online presence.
The playbook consists of 13 principles (called “plays”) that drive modern software development:

  • Understand what people need
  • Address the whole experience, from start to finish
  • Make it simple and intuitive
  • Build the service using agile and iterative practices
  • Structure budgets and contracts to support delivery
  • Assign one leader and hold that person accountable
  • Bring in experienced teams
  • Choose a modern technology stack
  • Deploy in a flexible hosting environment
  • Automate testing and deployments
  • Manage security and privacy through reusable processes
  • Use data to drive decisions
  • Default to open

These aren’t abstract principles: most of them should be familiar to anyone who has read about agile software development, attended one of our Velocity conferences, one of the many DevOps Days, or a similar event. All of the principles are worth reading (it’s not a long document). I’m going to call out two for special attention….”

Better Governing Through Data


Editorial Board of the New York Times: “Government bureaucracies, as opposed to casual friendships, are seldom in danger from too much information. That is why a new initiative by the New York City comptroller, Scott Stringer, to use copious amounts of data to save money and solve problems, makes such intuitive sense.

Called ClaimStat, it seeks to collect and analyze information on the thousands of lawsuits and claims filed each year against the city. By identifying patterns in payouts and trouble-prone agencies and neighborhoods, the program is supposed to reduce the cost of claims the way CompStat, the fabled data-tracking program pioneered by the New York Police Department, reduces crime.

There is a great deal of money to be saved: In its 2015 budget, the city has set aside $674 million to cover settlements and judgments from lawsuits brought against it. That amount is projected to grow by the 2018 fiscal year to $782 million, which Mr. Stringer notes is more than the combined budgets of the Departments of Aging and Parks and Recreation and the Public Library.

The comptroller’s office issued a report last month that applied the ClaimStat approach to a handful of city agencies: the Police Department, Parks and Recreation, Health and Hospitals Corporation, Environmental Protection and Sanitation. It notes that the Police Department generates the most litigation of any city agency: 9,500 claims were filed against it in 2013, leading to settlements and judgments of $137.2 million.

After adjusting for the crime rate, the report found that several precincts in the South Bronx and Central Brooklyn had far more claims filed against their officers than other precincts in the city. What does that mean? It’s hard to know, but the implications for policy and police discipline would seem to be a challenge that the mayor, police commissioner and precinct commanders need to figure out. The data clearly point to a problem.

Far more obvious conclusions may be reached from ClaimStat data covering issues like park maintenance and sewer overflows. The city’s tree-pruning budget was cut sharply in 2010, and injury claims from fallen tree branches soared. Multimillion-dollar settlements ensued.

The great promise of ClaimStat is making such shortsightedness blindingly obvious. And in exposing problems like persistent flooding from sewer overflows, ClaimStat can pinpoint troubled areas down to the level of city blocks. (We’re looking at you, Canarsie, and Community District 2 on Staten Island.)

Mayor Bill de Blasio’s administration has offered only mild praise for the comptroller’s excellent idea (“the mayor welcomes all ideas to make the city more effective and better able to serve its citizens”) while noting, perhaps a little defensively, that it is already on top of this, at least where the police are concerned. It has created a “Risk Assessment and Compliance Unit” within the Police Department to examine claims and make recommendations. The mayor’s aides also point out that the city’s payouts have remained flat over the last 12 years, for which they credit a smart risk-assessment strategy that knows when to settle claims and when to fight back aggressively in court.

But the aspiration of a well-run city should not be to hold claims even but to shrink them. And, at a time when anecdotes and rampant theorizing are fueling furious debates over police crime-fighting strategies, it seems beyond arguing that the more actual information, independently examined and publicly available, the better.”

Can big data help build more wind and solar farms?


Rachael Post in The Guardian: “Convincing customers to switch to renewable energy is an uphill battle. But for a former political operative, finding business is as easy as mining a consumer behavior database…After his father died from cancer related to pollution from a coal-burning plant, Tom Matzzie, the former director of democratic activist group MoveOn.org, decided that he’d had enough with traditional dirty energy. But when he installed solar panels on his home, he discovered that the complicated permitting and construction process made switching to renewable energy difficult and unwieldy. The solution, he concluded, was to use his online campaigning and big data skills – honed from his years of working in politics – to find the most likely customers for renewables and convince them to switch. Ethical Electric was born.
Matzzie’s company isn’t the first to sell renewable energy, but it might be the smartest. For the most part, convincing people to switch away from dirty energy is an unprofitable and work-intensive process, requiring electrical company representatives to approach thousands of randomly chosen customers. Ethical Electric, on the other hand, uses a highly-targeted, strategic method to identify its potential customers.
From finding votes to finding customers
Matzzie, who is now CEO of Ethical Electric, explained that the secret lies in his company’s use of big data, a resource that he and his partners mastered on the political front lines. In the last few presidential elections, big data fundamentally changed the way candidates – and their teams – approached voters. “We couldn’t rely on voter registration lists to make assumptions about who would be willing to vote in the next election,” Matzzie said. “What happened in politics is a real revolution in data.”…”

The Data Act's unexpected benefit


Adam Mazmanian at FCW: “The Digital Accountability and Transparency Act sets an aggressive schedule for creating governmentwide financial standards. The first challenge belongs to the Treasury Department and the Office of Management and Budget. They must come up with a set of common data elements for financial information that will cover just about everything the government spends money on and every entity it pays in order to give oversight bodies and government watchdogs a top-down view of federal spending from appropriation to expenditure. Those data elements are scheduled for completion by May 2015, one year after the act’s passage.
Two years after those standards are in place, agencies will be required to report their financial information following Data Act guidelines. The government currently supports more than 150 financial management systems but lacks a common data dictionary, so there are not necessarily agreed-upon definitions of how to classify and track government programs and types of expenditures.
“As far as systems today and how we can get there, they don’t necessarily map in the way that the act described,” U.S. CIO Steven VanRoekel said in June. “It’s going to be a journey to get to where the act aspires for us to be.”
However, an Obama administration initiative to encourage agencies to share financial services could be part of the solution. In May, OMB and Treasury designated four financial shared-services providers for government agencies: the Agriculture Department’s National Finance Center, the Interior Department’s Interior Business Center, the Transportation Department’s Enterprise Services Center and Treasury’s Administrative Resource Center.
There are some synergies between shared services and data standardization, but shared financial services alone will not guarantee Data Act compliance, especially considering that the government expects the migration to take 10 to 15 years. Nevertheless, the discipline required under the Data Act could boost agency efforts to prepare financial data when it comes time to move to a shared service….”

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. http://bit.ly/1xGf9oe

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Powerful new patent service shows every US invention, and a new view of R&D relationships


at GigaOm: “The website for the U.S. Patent Office website is famously clunky: searching and sorting patents can feel like playing an old Atari game, rather than watching innovation at work. But now a young inventor has come along with a tool to build a better patent office.
The service is called Trea, and was launched by Max Yuan, an engineer who received a patent of his own for a bike motor in 2007. After writing a tool to download patents related to his own invention, he expanded the process to slurp every patent and image in the USPTO database, and compile the information in a user-friendly interface.
Trea has been in beta for a while, but will formally launch on Wednesday. The tool not only provides an easy way to see what inventions a company or inventor is patenting, but also shows the fields in which they are most active. Here is a screenshot from Trea that shows what Apple has been up to in the last 12 months:
Trea screenshot of Apple inventions
Such information could be valuable to investors or to companies that want to use the filings as a way to track what might be in their competitors’ product pipelines. The Trea database also probes the USPTO for new filings, and can send alerts to subscribers. Yuan has also created a Twitter account just for new Apple filings.
Trea also draws on the patent database to display what Yuan calls a “unified knowledge graph” of relationships between inventors. Pictures, like the one below for IBM, show clusters of inventors and, at a broader level, the viral transmission of human ideas within a company:
Trea IBM screenshot
 
This type of information, gleaned from patent filings, could be valuable to corporate strategists, or to journalists, scholars or business historians. And making government websites more user-friendly, as Rankandfiled.com is attempting to do with Securities and Exchange Commission filings, can certainly help people understand what their regulators are doing….”

Unleashing Climate Data to Empower America’s Agricultural Sector


Secretary Tom Vilsack and John P. Holdren at the White House Blog: “Today, in a major step to advance the President’s Climate Data Initiative, the Obama administration is inviting leaders of the technology and agricultural sectors to the White House to discuss new collaborative steps to unleash data that will help ensure our food system is resilient to the effects of climate change.

More intense heat waves, heavier downpours, and severe droughts and wildfires out west are already affecting the nation’s ability to produce and transport safe food. The recently released National Climate Assessment makes clear that these kinds of impacts are projected to become more severe over this century.

Food distributors, agricultural businesses, farmers, and retailers need accessible, useable data, tools, and information to ensure the effectiveness and sustainability of their operations – from water availability, to timing of planting and harvest, to storage practices, and more.

Today’s convening at the White House will include formal commitments by a host of private-sector companies and nongovernmental organizations to support the President’s Climate Data Initiative by harnessing climate data in ways that will increase the resilience of America’s food system and help reduce the contribution of the nation’s agricultural sector to climate change.

Microsoft Research, for instance, will grant 12 months of free cloud-computing resources to winners of a national challenge to create a smartphone app that helps farmers increase the resilience of their food production systems in the face of weather variability and climate change; the Michigan Agri-Business Association will soon launch a publicly available web-based mapping tool for use by the state’s agriculture sector; and the U.S. dairy industry will test and pilot four new modules – energy, feed, nutrient, and herd management – on the data-driven Farm Smart environmental-footprint calculation tool by the end of 2014. These are just a few among dozens of exciting commitments.

And the federal government is also stepping up. Today, anyone can log onto climate.data.gov and find new features that make data accessible and usable about the risks of climate change to food production, delivery, and nutrition – including current and historical data from the Census of Agriculture on production, supply, and distribution of agricultural products, and data on climate-change-related risks such as storms, heat waves, and drought.

These steps are a direct response to the President’s call for all hands on deck to generate further innovation to help prepare America’s communities and business for the impacts of climate change.

We are delighted about the steps being announced by dozens of collaborators today, and we can’t wait to see what further tools, apps, and services are developed as the Administration and its partners continue to unleash data to make America’s agriculture enterprise stronger and more resilient than ever before.

Read a fact sheet about all of today’s Climate Data Initiative commitments here.

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


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

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

– BACKGROUND –

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

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

Sharing Data Is a Form of Corporate Philanthropy


Matt Stempeck in HBR Blog:  “Ever since the International Charter on Space and Major Disasters was signed in 1999, satellite companies like DMC International Imaging have had a clear protocol with which to provide valuable imagery to public actors in times of crisis. In a single week this February, DMCii tasked its fleet of satellites on flooding in the United Kingdom, fires in India, floods in Zimbabwe, and snow in South Korea. Official crisis response departments and relevant UN departments can request on-demand access to the visuals captured by these “eyes in the sky” to better assess damage and coordinate relief efforts.

DMCii is a private company, yet it provides enormous value to the public and social sectors simply by periodically sharing its data.
Back on Earth, companies create, collect, and mine data in their day-to-day business. This data has quickly emerged as one of this century’s most vital assets. Public sector and social good organizations may not have access to the same amount, quality, or frequency of data. This imbalance has inspired a new category of corporate giving foreshadowed by the 1999 Space Charter: data philanthropy.
The satellite imagery example is an area of obvious societal value, but data philanthropy holds even stronger potential closer to home, where a wide range of private companies could give back in meaningful ways by contributing data to public actors. Consider two promising contexts for data philanthropy: responsive cities and academic research.
The centralized institutions of the 20th century allowed for the most sophisticated economic and urban planning to date. But in recent decades, the information revolution has helped the private sector speed ahead in data aggregation, analysis, and applications. It’s well known that there’s enormous value in real-time usage of data in the private sector, but there are similarly huge gains to be won in the application of real-time data to mitigate common challenges.
What if sharing economy companies shared their real-time housing, transit, and economic data with city governments or public interest groups? For example, Uber maintains a “God’s Eye view” of every driver on the road in a city:
stempeck2
Imagine combining this single data feed with an entire portfolio of real-time information. An early leader in this space is the City of Chicago’s urban data dashboard, WindyGrid. The dashboard aggregates an ever-growing variety of public datasets to allow for more intelligent urban management.
stempeck3
Over time, we could design responsive cities that react to this data. A responsive city is one where services, infrastructure, and even policies can flexibly respond to the rhythms of its denizens in real-time. Private sector data contributions could greatly accelerate these nascent efforts.
Data philanthropy could similarly benefit academia. Access to data remains an unfortunate barrier to entry for many researchers. The result is that only researchers with access to certain data, such as full-volume social media streams, can analyze and produce knowledge from this compelling information. Twitter, for example, sells access to a range of real-time APIs to marketing platforms, but the price point often exceeds researchers’ budgets. To accelerate the pursuit of knowledge, Twitter has piloted a program called Data Grants offering access to segments of their real-time global trove to select groups of researchers. With this program, academics and other researchers can apply to receive access to relevant bulk data downloads, such as an period of time before and after an election, or a certain geographic area.
Humanitarian response, urban planning, and academia are just three sectors within which private data can be donated to improve the public condition. There are many more possible applications possible, but few examples to date. For companies looking to expand their corporate social responsibility initiatives, sharing data should be part of the conversation…
Companies considering data philanthropy can take the following steps:

  • Inventory the information your company produces, collects, and analyzes. Consider which data would be easy to share and which data will require long-term effort.
  • Think who could benefit from this information. Who in your community doesn’t have access to this information?
  • Who could be harmed by the release of this data? If the datasets are about people, have they consented to its release? (i.e. don’t pull a Facebook emotional manipulation experiment).
  • Begin conversations with relevant public agencies and nonprofit partners to get a sense of the sort of information they might find valuable and their capacity to work with the formats you might eventually make available.
  • If you expect an onslaught of interest, an application process can help qualify partnership opportunities to maximize positive impact relative to time invested in the program.
  • Consider how you’ll handle distribution of the data to partners. Even if you don’t have the resources to set up an API, regular releases of bulk data could still provide enormous value to organizations used to relying on less-frequently updated government indices.
  • Consider your needs regarding privacy and anonymization. Strip the data of anything remotely resembling personally identifiable information (here are some guidelines).
  • If you’re making data available to researchers, plan to allow researchers to publish their results without obstruction. You might also require them to share the findings with the world under Open Access terms….”

How Three Startups Are Using Data to Renew Public Trust In Government


Mark Hall: “Chances are that when you think about the word government, it is with a negative connotation.Your less-than-stellar opinion of government may be caused by everything from Washington’s dirty politics to the long lines at your local DMV.Regardless of the reason, local, state and national politics have frequently garnered a bad reputation. People feel like governments aren’t working for them.We have limited information, visibility and insight into what’s going on and why. Yes, the data is public information but it’s difficult to access and sift through.
Good news. Things are changing fast.
Innovative startups are emerging and they are changing the way we access government information at all levels.
Here are three tech startups that are taking a unique approach to opening up government data:
1. OpenGov is a Mountain View-based software company that enables government officials and local residents to easily parse through the city’s financial data.
Founded by a team with extensive technology and finance experience, this startup has already racked up some of the largest cities to join the movement, including the City of Los Angeles.OpenGov’s approach pairs data with good design in a manner that makes it easy to use.Historically, information like expenditures of public funds existed in a silo within the mayor’s office or city manager, diminishing  the accountability of public employees.Imagine you are a citizen who is interested in seeing how much your city spent on a particular matter?
Now you can find out within just a few clicks.
This data is always of great importance but could also become increasingly critical during events like local elections.This level of openness and accessibility to data will be game-changing.
2. FiscalNote is a one-year old startup that uses analytical signals and intelligent government data to map legislation and predict an outcome.
Headquartered in Washington D.C., the company has developed a search layer and unique algorithm that makes tracking legislative data extremely easy. If you are an organization that has vested interests in specific legislative bills, tools by FiscalNote can give you insights into its progress and likelihood of being passed or held up. Want to know if your local representative favors a bill that could hurt your industry? Find out early and take the steps necessary to minimize the impact. Large corporations and special interest groups have traditionally held lobbying power with elected officials. This technology is important because small businesses, nonprofits and organizations now have an additional tool to see a changing legislative landscape in ways that were previously unimaginable.
3. Civic Industries is a San Francisco startup that allows citizens and local government officials to easily access data that previously required you to drive down to city hall. Building permits, code enforcements, upcoming government projects and construction data is now openly available within a few clicks.
Civic Insight maps various projects in your community and enables you to see all the projects with the corresponding start and completion dates, along with department contacts.
Accountability of public planning is no longer concealed to the city workers in the back-office. Responsibility is made clear. The startup also pushes underutilized city resources like empty storefronts and abandoned buildings to the forefront in an effort to drive action, either by residents or government officials.
So What’s Next?
While these three startups using data to push government transparency in the right direction, more work is needed…”