Jeremy Goldberg: “Leaders in our social systems and institutions are faced with many of the same challenges of the past century, but they are tasked to solve them within new fiscal realities. In the United States these fiscal realities are tied to the impact of the most recent economic recession coupled with declining property and tax revenues. While these issues seem largely to be “problems” that many perceive to belong to our government, leadership across sectors has had to respond and adapt in numerous ways, some of which unfortunately include pay and hiring-freezes, lay-offs and cuts to important public services and programs related to education, parks and safety.
Fortunately, within this “new normal” there are examples of leadership within the public and private sector confronting these challenges head-on through innovative public-private partnerships (p3s). For example, municipal governments are turning to opportunities like IBM’s Smarter Cities Challenge, which provides funding and a team of IBM employees to assist the city in solving specific public problems. Other cities such as Boston, Louisville and San Francisco have established initiatives, projects and Offices of Civic Innovation where government, technologists, communities and residents are collaborating to solve problems through open-data initiatives and platforms.
This new generation of innovative P3s demonstrates the inherent power of what Joseph Nye coined a tri-sector athlete — someone who is able and experienced in business, government and the social sector. Today, unlike any other time before, tri-sector athletes are demonstrating that business as usual just won’t cut it. These athletes, myself included, believe it’s the perfect moment for civic innovation, the perfect time civic collaboration, and the perfect moment for an organization like Fuse Corps to lead the national civic entrepreneurship movement… and I’m proud to be a part of it.”
Bringing the deep, dark world of public data to light
Venturebeat: “The realm of public data is like a vast cave. It is technically open to all, but it contains many secrets and obstacles within its walls.
Enigma launched out of beta today to shed light on this hidden world. This “big data” startup focuses on data in the public domain, such as those published by governments, NGOs, and the media….
The company describes itself as “Google for public data.” Using a combination of automated web crawlers and directly reaching out to government agencies, Engima’s database contains billions of public records across more than 100,000 datasets. Pulling them all together breaks down the barriers that exist between various local, state, federal, and institutional search portals. On top of this information is an “entity graph” which searches through the data to discover relevant results. Furthermore, once the information is broken out of the silos, users can filter, reshape, and connect various datasets to find correlations….
The technology has a wide range of applications, including professional services, finance, news media, big data, and academia. Engima has formed strategic partnerships in each of these verticals with Deloitte, Gerson Lehrman Group, The New York Times, S&P Capital IQ, and Harvard Business School, respectively.”
D4D Challenge Winners announced
Global Pulse Blog: “The winners of the Data for Development challenge – an international research challenge using a massive anonymized dataset provided by telecommunications company Orange – were announced at the NetMob 2013 Conference in Boston last week….
In this post we’ll look at the winners and how their research could be put to use.
Best Visualization prize winner: “Exploration and Analysis of Massive Mobile Phone Data: A Layered Visual Analytics Approach” –
Best Development prize winner: “AllAboard: a System for Exploring Urban Mobility and Optimizing Public Transport Using Cellphone Data”
Best Scientific prize winner: “Analyzing Social Divisions Using Cell Phone Data”
First prize winner: “Exploiting Cellular Data for Disease Containment and Information Campaigns Strategies in Country-Wide Epidemics””
Innovation in Gov Service Delivery
DeveloperForce: “Can Government embody innovation and deliver ongoing increased levels of service? Salesforce.com’s Vivek Kundra and companies like BasicGov, Cloud Safety Net & LaunchPad believe so.
Entrepreneurs work tirelessly to help private sector companies streamline all aspects of their business from operations to customer engagement. Their goal and motto is to challenge the status quo and maximize customer satisfaction. Until recently, that mantra wasn’t exactly echoing through the hallways of most government agencies….
Public Sector transformation is being driven by increased data transparency and the formation of government-segmented ecosystems. In a January WSJ, CIO Journal article titled Vivek Kundra: Release Data, Even If It’s Imperfect, Vivek explains this concept and its role in creating efficiencies within government. Vivek says, “the release of government data is helping the private sector create a new wave of innovative apps, like applications that will help patients choose better hospitals. Those apps are built atop anonymized Medicare information.”
Some areas of government are even going so far as to create shared services. When you look at how governments are structured many processes are repeated, and in the past solutions were created or purchased for each unique instance. Various agencies have even gone so far as to create apps themselves and share these solutions without the benefit of leveraging best practices or creating scalable frameworks. Without subject-matter expertise government is falling behind in the business of building and maintaining world class applications….
ISV’s can leverage their private sector expertise and apply that to any number of functions and achieve dramatic results. Many of those partners are focused specifically on leveraging the Salesforce.com Platform.
One great example of an ISV leading that charge is BasicGov. BasicGov’s mission is to help state and local governments provide better services to its citizens. They accomplish this by offering a suite of modules that streamlines and automates processes in community development to achieve smart growth and sustainability goals. My personal favorite is the Citizen Portal where one can “view status of applications, complaints, communications online”….
AppExchange for Government is an online storefront offering apps specifically geared for federal, state & local governments.”
Is Privacy Algorithmically Impossible?
MIT Technology Review
: “In 1995, the European Union introduced privacy legislation that defined “personal data” as any information that could identify a person, directly or indirectly. The legislators were apparently thinking of things like documents with an identification number, and they wanted them protected just as if they carried your name.
Today, that definition encompasses far more information than those European legislators could ever have imagined—easily more than all the bits and bytes in the entire world when they wrote their law 18 years ago.
Here’s what happened. First, the amount of data created each year has grown exponentially (see figure)…
Much of this data is invisible to people and seems impersonal. But it’s not. What modern data science is finding is that nearly any type of data can be used, much like a fingerprint, to identify the person who created it: your choice of movies on Netflix, the location signals emitted by your cell phone, even your pattern of walking as recorded by a surveillance camera. In effect, the more data there is, the less any of it can be said to be private. We are coming to the point that if the commercial incentives to mine the data are in place, anonymity of any kind may be “algorithmically impossible,” says Princeton University computer scientist Arvind Narayanan.”
6 Things You May Not Know About Open Data
GovTech: “On Friday, May 3, Palo Alto, Calif., CIO Jonathan Reichental …said that when it comes to making data more open, “The invisible becomes visible,” and he outlined six major points that identify and define what open data really is:
1. It’s the liberation of peoples’ data
The public sector collects data that pertains to government, such as employee salaries, trees or street information, and government entities are therefore responsible for liberating that data so the constituent can view it in an accessible format. Though this practice has become more commonplace in recent years, Reichental said government should have been doing this all along.
2. Data has to be consumable by a machine
Piecing data together from a spreadsheet to a website or containing it in a PDF isn’t the easiest way to retrieve data. To make data more open, in needs to be in a readable format so users don’t have to go through additional trouble of finding or reading it.
3. Data has a derivative value
When data is made available to the public, people like app developers, arichitects or others are able to analyze the data. In some cases, data can be used in city planning to understand what’s happening at the city scale.
4. It eliminates the middleman
For many states, public records laws require them to provide data when a public records request is made. But oftentimes, complying with such request regulations involves long and cumbersome processes. Lawyers and other government officials must process paperwork, and it can take weeks to complete a request. By having data readily available, these processes can be eliminated, thus also eliminating the middleman responsible for processing the requests. Direct access to the data saves time and resources.
5. Data creates deeper accountability
Since government is expected to provide accessible data, it is therefore being watched, making it more accountable for its actions — everything from emails, salaries and city council minutes can be viewed by the public.
6. Open Data builds trust
When the community can see what’s going on in its government through the access of data, Reichtental said individuals begin to build more trust in their government and feel less like the government is hiding information.”
Linking open data to augmented intelligence and the economy
Open Data Institute and Professor Nigel Shadbolt (@Nigel_Shadbolt) interviewed by by Alex Howard (@digiphile): “…there are some clear learnings. One that I’ve been banging on about recently has been that yes, it really does matter to turn the dial so that governments have a presumption to publish non-personal public data. If you would publish it anyway, under a Freedom of Information request or whatever your local legislative equivalent is, why aren’t you publishing it anyway as open data? That, as a behavioral change. is a big one for many administrations where either the existing workflow or culture is, “Okay, we collect it. We sit on it. We do some analysis on it, and we might give it away piecemeal if people ask for it.” We should construct publication process from the outset to presume to publish openly. That’s still something that we are two or three years away from, working hard with the public sector to work out how to do and how to do properly.
We’ve also learned that in many jurisdictions, the amount of [open data] expertise within administrations and within departments is slight. There just isn’t really the skillset, in many cases. for people to know what it is to publish using technology platforms. So there’s a capability-building piece, too.
One of the most important things is it’s not enough to just put lots and lots of datasets out there. It would be great if the “presumption to publish” meant they were all out there anyway — but when you haven’t got any datasets out there and you’re thinking about where to start, the tough question is to say, “How can I publish data that matters to people?”
The data that matters is revealed in the fact that if we look at the download stats on these various UK, US and other [open data] sites. There’s a very, very distinctive parallel curve. Some datasets are very, very heavily utilized. You suspect they have high utility to many, many people. Many of the others, if they can be found at all, aren’t being used particularly much. That’s not to say that, under that long tail, there isn’t large amounts of use. A particularly arcane open dataset may have exquisite use to a small number of people.
The real truth is that it’s easy to republish your national statistics. It’s much harder to do a serious job on publishing your spending data in detail, publishing police and crime data, publishing educational data, publishing actual overall health performance indicators. These are tough datasets to release. As people are fond of saying, it holds politicians’ feet to the fire. It’s easy to build a site that’s full of stuff — but does the stuff actually matter? And does it have any economic utility?”
there are some clear learnings. One that I’ve been banging on about recently has been that yes, it really does matter to turn the dial so that governments have a presumption to publish non-personal public data. If you would publish it anyway, under a Freedom of Information request or whatever your local legislative equivalent is, why aren’t you publishing it anyway as open data? That, as a behavioral change. is a big one for many administrations where either the existing workflow or culture is, “Okay, we collect it. We sit on it. We do some analysis on it, and we might give it away piecemeal if people ask for it.” We should construct publication process from the outset to presume to publish openly. That’s still something that we are two or three years away from, working hard with the public sector to work out how to do and how to do properly.
We’ve also learned that in many jurisdictions, the amount of [open data] expertise within administrations and within departments is slight. There just isn’t really the skillset, in many cases. for people to know what it is to publish using technology platforms. So there’s a capability-building piece, too.
One of the most important things is it’s not enough to just put lots and lots of datasets out there. It would be great if the “presumption to publish” meant they were all out there anyway — but when you haven’t got any datasets out there and you’re thinking about where to start, the tough question is to say, “How can I publish data that matters to people?”
The data that matters is revealed in the fact that if we look at the download stats on these various UK, US and other [open data] sites. There’s a very, very distinctive parallel curve. Some datasets are very, very heavily utilized. You suspect they have high utility to many, many people. Many of the others, if they can be found at all, aren’t being used particularly much. That’s not to say that, under that long tail, there isn’t large amounts of use. A particularly arcane open dataset may have exquisite use to a small number of people.
The real truth is that it’s easy to republish your national statistics. It’s much harder to do a serious job on publishing your spending data in detail, publishing police and crime data, publishing educational data, publishing actual overall health performance indicators. These are tough datasets to release. As people are fond of saying, it holds politicians’ feet to the fire. It’s easy to build a site that’s full of stuff — but does the stuff actually matter? And does it have any economic utility?
The Big Data Debate: Correlation vs. Causation
Gil Press: “In the first quarter of 2013, the stock of big data has experienced sudden declines followed by sporadic bouts of enthusiasm. The volatility—a new big data “V”—continues and Ted Cuzzillo summed up the recent negative sentiment in “Big data, big hype, big danger” on SmartDataCollective:
“A remarkable thing happened in Big Data last week. One of Big Data’s best friends poked fun at one of its cornerstones: the Three V’s. The well-networked and alert observer Shawn Rogers, vice president of research at Enterprise Management Associates, tweeted his eight V’s: ‘…Vast, Volumes of Vigorously, Verified, Vexingly Variable Verbose yet Valuable Visualized high Velocity Data.’ He was quick to explain to me that this is no comment on Gartner analyst Doug Laney’s three-V definition. Shawn’s just tired of people getting stuck on V’s.”…
Cuzzillo is joined by a growing chorus of critics that challenge some of the breathless pronouncements of big data enthusiasts. Specifically, it looks like the backlash theme-of-the-month is correlation vs. causation, possibly in reaction to the success of Viktor Mayer-Schönberger and Kenneth Cukier’s recent big data book in which they argued for dispensing “with a reliance on causation in favor of correlation”…
In “Steamrolled by Big Data,” The New Yorker’s Gary Marcus declares that “Big Data isn’t nearly the boundless miracle that many people seem to think it is.”…
Matti Keltanen at The Guardian agrees, explaining “Why ‘lean data’ beats big data.” Writes Keltanen: “…the lightest, simplest way to achieve your data analysis goals is the best one…The dirty secret of big data is that no algorithm can tell you what’s significant, or what it means. Data then becomes another problem for you to solve. A lean data approach suggests starting with questions relevant to your business and finding ways to answer them through data, rather than sifting through countless data sets. Furthermore, purely algorithmic extraction of rules from data is prone to creating spurious connections, such as false correlations… today’s big data hype seems more concerned with indiscriminate hoarding than helping businesses make the right decisions.”
In “Data Skepticism,” O’Reilly Radar’s Mike Loukides adds this gem to the discussion: “The idea that there are limitations to data, even very big data, doesn’t contradict Google’s mantra that more data is better than smarter algorithms; it does mean that even when you have unlimited data, you have to be very careful about the conclusions you draw from that data. It is in conflict with the all-too-common idea that, if you have lots and lots of data, correlation is as good as causation.”
Isn’t more-data-is-better the same as correlation-is-as-good-as-causation? Or, in the words of Chris Andersen, “with enough data, the numbers speak for themselves.”
“Can numbers actually speak for themselves?” non-believer Kate Crawford asks in “The Hidden Biases in Big Data” on the Harvard Business Review blog and answers: “Sadly, they can’t. Data and data sets are not objective; they are creations of human design…
And David Brooks in The New York Times, while probing the limits of “the big data revolution,” takes the discussion to yet another level: “One limit is that correlations are actually not all that clear. A zillion things can correlate with each other, depending on how you structure the data and what you compare. To discern meaningful correlations from meaningless ones, you often have to rely on some causal hypothesis about what is leading to what. You wind up back in the land of human theorizing…”
The Next Great Internet Disruption: Authority and Governance
An essay by David Bollier and John Clippinger as part of their ongoing work of ID3, the Institute for Data-Driven Design : “As the Internet and digital technologies have proliferated over the past twenty years, incumbent enterprises nearly always resist open network dynamics with fierce determination, a narrow ingenuity and resistance….But the inevitable rearguard actions to defend old forms are invariably overwhelmed by the new, network-based ones. The old business models, organizational structures, professional sinecures, cultural norms, etc., ultimately yield to open platforms.
When we look back on the past twenty years of Internet history, we can more fully appreciate the prescience of David P. Reed’s seminal 1999 paper on “Group Forming Networks” (GFNs). “Reed’s Law” posits that value in networks increases exponentially as interactions move from a broadcasting model that offers “best content” (in which value is described by n, the number of consumers) to a network of peer-to-peer transactions (where the network’s value is based on “most members” and mathematically described by n2). But by far the most valuable networks are based on those that facilitate group affiliations, Reed concluded. When users have tools for “free and responsible association for common purposes,” he found, the value of the network soars exponentially to 2n – a fantastically large number. This is the Group Forming Network. Reed predicted that “the dominant value in a typical network tends to shift from one category to another as the scale of the network increases.…”
What is really interesting about Reed’s analysis is that today’s world of GFNs, as embodied by Facebook, Twitter, Wikipedia and other Web 2.0 technologies, remains highly rudimentary. It is based on proprietary platforms (as opposed to open source, user-controlled platforms), and therefore provides only limited tools for members of groups to develop trust and confidence in each other. This suggests a huge, unmet opportunity to actualize greater value from open networks. Citing Francis Fukuyama’ book Trust, Reed points out that “there is a strong correlation between the prosperity of national economies and social capital, which [Fukuyama] defines culturally as the ease with which people in a particular culture can form new associations.”
Measuring Impact of Open and Transparent Governance
Mark Robinson @ OGP blog: “Eighteen months on from the launch of the Open Government Partnership in New York in September 2011, there is growing attention to what has been achieved to date. In the recent OGP Steering Committee meeting in London, government and civil society members were unanimous in the view that the OGP must demonstrate results and impact to retain its momentum and wider credibility. This will be a major focus of the annual OGP conference in London on 31 October and 1 November, with an emphasis on showcasing innovations, highlighting results and sharing lessons.
Much has been achieved in eighteen months. Membership has grown from 8 founding governments to 58. Many action plan commitments have been realised for the majority of OGP member countries. The Independent Reporting Mechanism has been approved and launched. Lesson learning and sharing experience is moving ahead….
The third type of results are the trickiest to measure: What has been the impact of openness and transparency on the lives of ordinary citizens? In the two years since the OGP was launched it may be difficult to find many convincing examples of such impact, but it is important to make a start in collecting such evidence.
Impact on the lives of citizens would be evident in improvements in the quality of service delivery, by making information on quality, access and complaint redressal public. A related example would be efficiency savings realised from publishing government contracts. Misallocation of public funds exposed through enhanced budget transparency is another. Action on corruption arising from bribes for services, misuse of public funds, or illegal procurement practices would all be significant results from these transparency reforms. A final example relates to jobs and prosperity, where the utilisation of government data in the public domain by the private sector to inform business investment decisions and create employment.
Generating convincing evidence on the impact of transparency reforms is critical to the longer-term success of the OGP. It is the ultimate test of whether lofty public ambitions announced in country action plans achieve real impacts to the benefit of citizens.”