“An effective preparedness platform customizable to your city. City72 is an open-source emergency preparedness platform that promotes community resilience and connection. This Toolkit is designed specifically for emergency preparedness organizations and provides the information and resources to create a customized City72 site for any city or region. It includes: how to create localized content, access to the code to build and install your City72 website, and tips for how to manage and promote your site.”
In democracy and disaster, emerging world embraces 'open data'
Jeremy Wagstaff’ at Reuters: “Open data’ – the trove of data-sets made publicly available by governments, organizations and businesses – isn’t normally linked to high-wire politics, but just may have saved last month’s Indonesian presidential elections from chaos.
Data is considered open when it’s released for anyone to use and in a format that’s easy for computers to read. The uses are largely commercial, such as the GPS data from U.S.-owned satellites, but data can range from budget numbers and climate and health statistics to bus and rail timetables.
It’s a revolution that’s swept the developed world in recent years as governments and agencies like the World Bank have freed up hundreds of thousands of data-sets for use by anyone who sees a use for them. Data.gov, a U.S. site, lists more than 100,000 data-sets, from food calories to magnetic fields in space.
Consultants McKinsey reckon open data could add up to $3 trillion worth of economic activity a year – from performance ratings that help parents find the best schools to governments saving money by releasing budget data and asking citizens to come up with cost-cutting ideas. All the apps, services and equipment that tap the GPS satellites, for example, generate $96 billion of economic activity each year in the United States alone, according to a 2011 study.
But so far open data has had a limited impact in the developing world, where officials are wary of giving away too much information, and where there’s the issue of just how useful it might be: for most people in emerging countries, property prices and bus schedules aren’t top priorities.
But last month’s election in Indonesia – a contentious face-off between a disgraced general and a furniture-exporter turned reformist – highlighted how powerful open data can be in tandem with a handful of tech-smart programmers, social media savvy and crowdsourcing.
“Open data may well have saved this election,” said Paul Rowland, a Jakarta-based consultant on democracy and governance…”
Google's fact-checking bots build vast knowledge bank
Hal Hodson in the New Scientist: “The search giant is automatically building Knowledge Vault, a massive database that could give us unprecedented access to the world’s facts
GOOGLE is building the largest store of knowledge in human history – and it’s doing so without any human help. Instead, Knowledge Vault autonomously gathers and merges information from across the web into a single base of facts about the world, and the people and objects in it.
The breadth and accuracy of this gathered knowledge is already becoming the foundation of systems that allow robots and smartphones to understand what people ask them. It promises to let Google answer questions like an oracle rather than a search engine, and even to turn a new lens on human history.
Knowledge Vault is a type of “knowledge base” – a system that stores information so that machines as well as people can read it. Where a database deals with numbers, a knowledge base deals with facts. When you type “Where was Madonna born” into Google, for example, the place given is pulled from Google’s existing knowledge base.
This existing base, called Knowledge Graph, relies on crowdsourcing to expand its information. But the firm noticed that growth was stalling; humans could only take it so far. So Google decided it needed to automate the process. It started building the Vault by using an algorithm to automatically pull in information from all over the web, using machine learning to turn the raw data into usable pieces of knowledge.
Knowledge Vault has pulled in 1.6 billion facts to date. Of these, 271 million are rated as “confident facts”, to which Google’s model ascribes a more than 90 per cent chance of being true. It does this by cross-referencing new facts with what it already knows.
“It’s a hugely impressive thing that they are pulling off,” says Fabian Suchanek, a data scientist at Télécom ParisTech in France.
Google’s Knowledge Graph is currently bigger than the Knowledge Vault, but it only includes manually integrated sources such as the CIA Factbook.
Knowledge Vault offers Google fast, automatic expansion of its knowledge – and it’s only going to get bigger. As well as the ability to analyse text on a webpage for facts to feed its knowledge base, Google can also peer under the surface of the web, hunting for hidden sources of data such as the figures that feed Amazon product pages, for example.
Tom Austin, a technology analyst at Gartner in Boston, says that the world’s biggest technology companies are racing to build similar vaults. “Google, Microsoft, Facebook, Amazon and IBM are all building them, and they’re tackling these enormous problems that we would never even have thought of trying 10 years ago,” he says.
The potential of a machine system that has the whole of human knowledge at its fingertips is huge. One of the first applications will be virtual personal assistants that go way beyond what Siri and Google Now are capable of, says Austin…”
Technology’s Crucial Role in the Fight Against Hunger
Crowdsourcing, predictive analytics and other new tools could go far toward finding innovative solutions for America’s food insecurity.
National Geographic recently sent three photographers to explore hunger in the United States. It was an effort to give a face to a very troubling statistic: Even today, one-sixth of Americans do not have enough food to eat. Fifty million people in this country are “food insecure” — having to make daily trade-offs among paying for food, housing or medical care — and 17 million of them skip at least one meal a day to get by. When choosing what to eat, many of these individuals must make choices between lesser quantities of higher-quality food and larger quantities of less-nutritious processed foods, the consumption of which often leads to expensive health problems down the road.
This is an extremely serious, but not easily visible, social problem. Nor does the challenge it poses become any easier when poorly designed public-assistance programs continue to count the sauce on a pizza as a vegetable. The deficiencies caused by hunger increase the likelihood that a child will drop out of school, lowering her lifetime earning potential. In 2010 alone, food insecurity cost America $167.5 billion, a figure that includes lost economic productivity, avoidable health-care expenses and social-services programs.
As much as we need specific policy innovations, if we are to eliminate hunger in America food insecurity is just one of many extraordinarily complex and interdependent “systemic” problems facing us that would benefit from the application of technology, not just to identify innovative solutions but to implement them as well. In addition to laudable policy initiatives by such states as Illinois and Nevada, which have made hunger a priority, or Arkansas, which suffers the greatest level of food insecurity but which is making great strides at providing breakfast to schoolchildren, we can — we must — bring technology to bear to create a sustained conversation between government and citizens to engage more Americans in the fight against hunger.
Identifying who is genuinely in need cannot be done as well by a centralized government bureaucracy — even one with regional offices — as it can through a distributed network of individuals and organizations able to pinpoint with on-the-ground accuracy where the demand is greatest. Just as Ushahidi uses crowdsourcing to help locate and identify disaster victims, it should be possible to leverage the crowd to spot victims of hunger. As it stands, attempts to eradicate so-called food deserts are often built around developing solutions for residents rather than with residents. Strategies to date tend to focus on the introduction of new grocery stores or farmers’ markets but with little input from or involvement of the citizens actually affected.
Applying predictive analytics to newly available sources of public as well as private data, such as that regularly gathered by supermarkets and other vendors, could also make it easier to offer coupons and discounts to those most in need. In addition, analyzing nonprofits’ tax returns, which are legally open and available to all, could help map where the organizations serving those in need leave gaps that need to be closed by other efforts. The Governance Lab recently brought together U.S. Department of Agriculture officials with companies that use USDA data in an effort to focus on strategies supporting a White House initiative to use climate-change and other open data to improve food production.
Such innovative uses of technology, which put citizens at the center of the service-delivery process and streamline the delivery of government support, could also speed the delivery of benefits, thus reducing both costs and, every bit as important, the indignity of applying for assistance.
Being open to new and creative ideas from outside government through brainstorming and crowdsourcing exercises using social media can go beyond simply improving the quality of the services delivered. Some of these ideas, such as those arising from exciting new social-science experiments involving the use of incentives for “nudging” people to change their behaviors, might even lead them to purchase more healthful food.
Further, new kinds of public-private collaborative partnerships could create the means for people to produce their own food. Both new kinds of financing arrangements and new apps for managing the shared use of common real estate could make more community gardens possible. Similarly, with the kind of attention, convening and funding that government can bring to an issue, new neighbor-helping-neighbor programs — where, for example, people take turns shopping and cooking for one another to alleviate time away from work — could be scaled up.
Then, too, advances in citizen engagement and oversight could make it more difficult for lawmakers to cave to the pressures of lobbying groups that push for subsidies for those crops, such as white potatoes and corn, that result in our current large-scale reliance on less-nutritious foods. At the same time, citizen scientists reporting data through an app would be able do a much better job than government inspectors in reporting what is and is not working in local communities.
As a society, we may not yet be able to banish hunger entirely. But if we commit to using new technologies and mechanisms of citizen engagement widely and wisely, we could vastly reduce its power to do harm.
An Air-Quality Monitor You Take with You
MIT Technology Review: “A startup is building a wearable air-quality monitor using a sensing technology that can cheaply detect the presence of chemicals around you in real time. By reporting the information its sensors gather to an app on your smartphone, the technology could help people with respiratory conditions and those who live in highly polluted areas keep tabs on exposure.
Berkeley, California-based Chemisense also plans to crowdsource data from users to show places around town where certain compounds are identified.
Initially, the company plans to sell a $150 wristband geared toward kids with asthma—of which there are nearly 7 million in the U.S., according to data from the Centers for Disease Control and Prevention— to help them identify places and pollutants that tend to provoke attacks, and track their exposure to air pollution over time. The company hopes people with other respiratory conditions, and those who are just concerned about air pollution, will be interested, too.
In the U.S., air quality is monitored at thousands of stations across the country; maps and forecasts can be viewed online. But these monitors offer accurate readings only in their location.
Chemisense has not yet made its initial product, but it expects it will be a wristband using polymers treated with charged nanoparticles of carbon such that the polymers swell in the presence of certain chemical vapors, changing the resistance of a circuit.”
Using technology, data and crowdsourcing to hack infrastructure problems
Courtney M. Fowler at CAFWD.ORG: “Technology has become a way of life for most Americans, not just for communication but also for many daily activities. However, there’s more that can be done than just booking a trip or crushing candy. With a majority of Americans now owning smartphones, it’s only becoming more obvious that there’s room for governments to engage the public and provide more bang for their buck via technology.
CA Fwd has been putting on an “Open Data roadshow” around the state to highlight ways the marriage of tech and info can make government more efficient and transparent.
Jurisdictions have also been discovering that using technology and smartphone apps can be beneficial in the pursuit of improving infrastructure. Saving any amount of money on such projects is especially important for California, where it’s been estimated the state will only have half of the $765 billion needed for infrastructure investments over the next decade.
One of the best examples of applying technology to infrastructure problems comes from South Carolina, where an innovative bridge-monitoring system is producing real savings, despite being in use on only eight bridges.
Girder sensors are placed on each bridge so that they can measure its carrying capacity and can be monitored 24/7. Although, the monitors don’t eliminate the need for inspections, the technology does make the need for them significantly less frequent. Data from the monitors also led the South Carolina Department of Transportation to correct one bridge’s problems with a $100,000 retrofit, rather than spending $800,000 to replace it…”
In total, having the monitors on just eight bridges, at a cost of about $50,000 per bridge, saved taxpayers $5 million.
That kind of innovation and savings is exactly what California needs to ensure that infrastructure projects happen in a more timely and efficient fashion in the future. It’s also what is driving civic innovators to bring together technology and crowdsourcing and make sure infrastructure projects also are results oriented.
App enables citizens to report water waste in drought regions
Springwise: “Rallying citizens to take a part in looking after the community they live in has become easier thanks to smartphones. In the past, the Creek Watch app has enabled anyone to help monitor their local water quality by sending data back to the state water board. Now Everydrop LA wants to use similar techniques to avoid drought in California, encouraging residents to report incidents of water wastage.
According to the team behind the app — which also created the CitySourced platform for engaging users in civic issues — even the smallest amount of water wastage can lead to meaningful losses over time. A faucet that drips just once a minute will lose over 2000 gallons of drinkable water each year. Using the Everydrop LA, citizens can report the location of leaking faucets and fire hydrants as well as occurrences of blatant water wastage. They can also see how much water is being wasted in their local area and learn about what they can do to cut their own water usage. In times when drought is a risk, the app notifies users to conserve. Cities and counties can use the data in their reports and learn more about how water wastage is affecting their jurisdiction.”
Using the Wisdom of the Crowd to Democratize Markets
David Weidner at the Wall Street Journal: “For years investors have largely depended on three sources to distill the relentless onslaught of information about public companies: the companies themselves, Wall Street analysts and the media.
Each of these has their strengths, but they may have even bigger weaknesses. Companies spin. Analysts have conflicts of interest. The financial media is under deadline pressure and ill-equipped to act as a catch-all watchdog.
But in recent years, the tech whizzes out of Silicon Valley have been trying to democratize the markets. In 2010 I wrote about an effort called Moxy Vote, an online system for shareholders to cast ballots in proxy contests. Moxy Vote had some initial success but ran into regulatory trouble and failed to gain traction.
Some newer efforts are more promising, mostly because they depend on users, or some form of crowdsourcing, for their content. Crowdsourcing is when a need is turned over to a large group, usually an online community, rather than traditional paid employees or outside providers….
Estimize.com is one. It was founded in 2011 by former trader Leigh Drogan, but recently has undergone some significant expansion, adding a crowd-sourced prediction for mergers and acquisitions. Estimize also boasts a track record. It claims it beats Wall Street analysts 65.9% of the time during earnings season. Like SeekingAlpha, Estimize does, however, lean heavily on pros or semi-pros. Nearly 5,000 of its contributors are analysts.
Closer to the social networking world there’s scutify.com, a website and mobile app that aggregates what’s being said about individual stocks on social networks, blogs and other sources. It highlights trending stocks and links to chatter on social networks. (The site is owned by Cody Willard, a contributor to MarketWatch, which is owned by Dow Jones, the publisher of The Wall Street Journal.)
Perhaps the most intriguing startup is TwoMargins.com. The site allows investors, analysts, average Joes — anyone, really — to annotate company releases. In that way, Two Margins potentially can tap the power of the crowd to provide a fourth source for the marketplace.
Two Margins, a startup funded by Bloomberg L.P.’s venture capital fund, borrows annotation technology that’s already in use on other sites such as genius.com and scrible.com. Participants can sign in with their Twitter or Facebook accounts and post to those networks from the site. (Dow Jones competes with Bloomberg in the provision of news and financial data.)
At this moment, Two Margins isn’t a game changer. Founders Gniewko Lubecki and Akash Kapur said the site is in a pre-beta phase, which is to say it’s sort of up and running and being constantly tweaked.
Right now there’s nothing close to the critical mass needed for an exhaustive look at company filings. There’s just a handful of users and less than a dozen company releases and filings available.
Still, in the first moments after Twitter Inc.’s earnings were released Tuesday, Two Margins’ most loyal users began to scour the release. “Looks like Twitter is getting significantly better at monetizing users,” wrote a user named “George” who had annotated the revenue line from the company’s financial statement. Another user, “Scott Paster,” noted Twitter’s stock option grants to executives were nearly as high as its reported loss.
“The sum is greater than it’s parts when you pull together a community of users,” Mr. Kapur said. “Widening access to these documents is one goal. The other goal is broadening the pool of knowledge that’s brought to bear on these documents.”
In the end, this new wave of tech-driven services may never capture enough users to make it into the investing mainstream. They all struggle with uninformed and inaccurate content especially if they gain critical mass. Vetting is a problem.
For that reasons, it’s hard to predict whether these new entries will flourish or even survive. That’s not a bad thing. The march of technology will either improve on the idea or come up with a new one.
Ultimately, technology is making possible what hasn’t been. That is, free discussion, access and analysis of information. Some may see it as a threat to Wall Street, which has always charged for expert analysis. Really, though, these efforts are good for markets, which pride themselves on being fair and transparent.
It’s not just companies that should compete, but ideas too.”
This Exercise App Tracks Trends on How We Move In Different Cities
Mark Byrnes at CityLab: “An app designed to encourage exercise can also tell us a lot about the way different cities get from point A to B.
The app, called Human, runs in the background of your iPhone, automatically detecting activities like walking, cycling, running, and motorized transport. The point is to encourage you to exercise for at least 30 minutes a day.
Almost a year since Human launched (last August), its developers have released stunning visualization of all that movement: 7.5 million miles traveled by their app users so far.
On their site, you can look into the mobility data inside 30 different cities. Once you click on one, you’ll be greeted with a pie chart that shows the distribution of activity within that city lined up against a pie chart that shows the international average.
In the case of Amsterdam, its transportation clichés are verified. App users in the bike-loving city use two wheels way more than they use four. And they walk about as much as anywhere else:
Human then shows the paths traveled by their users. When it comes to Amsterdam, the results look almost exactly like the city’s entire street grid, no matter what physical activity is being shown:
How to harness the wisdom of crowds to improve public service delivery and policymaking
Eddie Copeland in PolicyBytes: “…In summary, government has used technology to streamline transactions and better understand the public’s opinions. Yet it has failed to use it to radically change the way it works. Have public services been reinvented? Is government smaller and leaner? Have citizens, businesses and civic groups been offered the chance to take part in the work of government and improve their own communities? On all counts the answer is unequivocally, no. What is needed, therefore, is a means to enable citizens to provide data to government to inform policymaking and to improve – or even help deliver – public services. What is needed is a Government Data Marketplace.
Government Data Marketplace
A Government Data Marketplace (GDM) would be a website that brought together public sector bodies that needed data, with individuals, businesses and other organisations that could provide it. Imagine an open data portal in reverse: instead of government publishing its own datasets to be used by citizens and businesses, it would instead publish its data needs and invite citizens, businesses or community groups to provide that data (for free or in return for payment). Just as open data portals aim to provide datasets in standard, machine-readable formats, GDM would operate according to strict open standards, and provide a consistent and automated way to deliver data to government through APIs.
How would it work? Imagine a local council that wished to know where instances of graffiti occurred within its borough. The council would create an account on GDM and publish a new request, outlining the data it required (not dissimilar to someone posting a job on a site like Freelancer). Citizens, businesses and other organisations would be able to view that request on GDM and bid to offer the service. For example, an app-development company could offer to build an app that would enable citizens to photograph and locate instances of graffiti in the borough. The app would be able to upload the data to GDM. The council could connect its own IT system to GDM to pass the data to their own database.
Importantly, the app-development company would specify via GDM how much it would charge to provide the data. Other companies and organisations could offer competing bids for delivering the same – or an even better service – at different prices. Supportive local civic hacker groups could even offer to provide the data for free. Either way, the council would get the data it needed without having to collect it for itself, whilst also ensuring it paid the best price from a number of competing providers.
Since GDM would be a public marketplace, other local authorities would be able to see that a particular company had designed a graffiti-reporting solution for one council, and could ask for the same data to be collected in their own boroughs. This would be quick and easy for the developer, as instead of having to create a bespoke solution to work with each council’s IT system, they could connect to all of them using one common interface via GDM. That would good for the company, as they could sell to a much larger market (the same solution would work for one council or all), and good for the councils, as they would benefit from cheaper prices generated from economies of scale. And since GDM would use open standards, if a council was unhappy with the data provided by one supplier, it could simply look to another company to provide the same information.
What would be the advantages of such a system? Firstly, innovation. GDM would free government from having to worry about what software it needed, and instead allow it to focus on the data it required to provide a service. To be clear: councils themselves do not need a graffiti app – they need data on where graffiti is. By focusing attention on its data needs, the public sector could let the market innovate to find the best solutions for providing it. That might be via an app, perhaps via a website, social media, or Internet of Things sensors, or maybe even using a completely new service that collected information in a radically different way. It will not matter – the right information would be provided in a common format via GDM.
Secondly, the potential cost savings of this approach would be many and considerable. At the very least, by creating a marketplace, the public sector would be able to source data at a competitive price. If several public sector bodies needed the same service via GDM, companies providing that data would be able to offer much cheaper prices for all, as instead of having to deal with hundreds of different organisations (and different interfaces) they could create one solution that worked for all of them. As prices became cheaper for standard solutions, this would in turn encourage more public sector bodies to converge on common ways of working, driving down costs still further. Yet these savings would be dwarfed by those possible if GDM could be used to source data that public sectors bodies currently have to manually collect themselves. Imagine if instead of having teams of inspectors to locate instances X, Y or Z, it could instead source the same data from citizens via GDM?
There would no limit to the potential applications to which GDM could be put by central and local government and other public sector bodies: for graffiti, traffic levels, environmental issues, education or welfare. It could be used to crowdsource facts, figures, images, map coordinates, text – anything that can be collected as data. Government could request information on areas on which it previously had none, helping them to assign their finite resources and money in a much more targeted way. New York City’s Mayor’s Office of Data Analytics has demonstrated that up to 500% increases in the efficiency of providing some public services can be achieved, if only the right data is available.
For the private sector, GDM would stimulate the growth of innovative new companies offering community data, and make it easier for them to sell data solutions across the whole of the public sector. They could pioneer in new data methods, and potentially even take over the provision of entire services which the public sector currently has to provide itself. For citizens, it would offer a means to genuinely get involved in solving issues that matter to their local communities, either by using apps made by businesses, or working to provide the data themselves.
And what about the benefits for policymaking? It is important to acknowledge that the idea of harnessing the wisdom of crowds for policymaking is currently experimental. In the case of Policy Futures Markets, some applications have also been considered to be highly controversial. So which methods would be most effective? What would they look like? In what policy domains would they provide most value? The simple fact is that we do not know. What is certain, however, is that innovation in open policymaking and crowdsourcing ideas will never be achieved until a platform is available that allows such ideas to be tried and tested. GDM could be that platform.
Public sector bodies could experiment with asking citizens for information or answers to particular, fact-based questions, or even for predictions on future outcomes, to help inform their policymaking activities. The market could then innovate to develop solutions to source that data from citizens, using the many different models for harnessing the wisdom of crowds. The effectiveness of those initiatives could then be judged, and the techniques honed. In the worst case scenario that it did not work, money would not have been wasted on building the wrong platform – GDM would continue to have value in providing data for public service needs as described above….”