Springwise: “Congestion at peak hours is a major problem in the world’s busiest city centres. We’ve recently seen Gothenburg in Sweden offering free bicycles to ease the burden on public transport services, but now a new app is looking to take a different approach to the same problem. Urban Engines uses algorithms to help cities determine key congestion choke points and times, and can then reward commuters for avoiding them.
The Urban Engines system is based on commuters using the smart commuter cards already found in many major cities. The company tracks journeys made with those commuter cards, and uses that data to identify main areas of congestion, and at what times the congestion occurs. The system has already been employed in Washington, D.C, and Sao Paulo, Brazil, helping provide valuable data for work with city planners.
It’s in Singapore, however, where the most interesting work has been achieved so far. There, commuters who have signed up and registered their commuter cards can earn rewards when they travel. They will earn one point for every kilometre travelled during peak hours, or triple that when travelling off-peak. The points earned can then be converted into discounts on future journeys, or put towards an in-app raffle game, where they have the opportunity to win sums of money. Urban Engines claim there’s been a 7 to 13 percent reduction in journeys made during peak hours, with 200,000 commuters taking part.
The company is based on an original experiment carried out in Bangalore. The rewards program there, carried out among 20,000 employees of the Indian company Infosys, lead to 17 percent of traffic shifting to off-peak travel times in six months. A similarly successful experiment has also been carried out on the Stanford University campus, and the plan is to now expand to other major cities…”
Lawsuit Would Force IRS to Release Nonprofit Tax Forms Digitally
Suzanne Perry at the Chronicle of Philanthropy on how “Open Data Could Shine a Light on Pay and Lobbying”: “Nonprofits that want to find out what their peers are doing can find a wealth of information in the forms the groups must file each year with the Internal Revenue Service—how much they pay their chief executives, how much they spend on fundraising, who is on their boards, where they offer services.
But the way the IRS makes those data available harkens to the digital dark ages, and critics who want to overhaul the system have been shaking up the generally polite nonprofit world with legal challenges, charges of monopoly, and talk of “disrupting” the status quo.
The issue will take center stage in a courtroom this week when a federal district judge in San Francisco is scheduled to consider arguments about whether to approve the IRS’s move to dismiss a lawsuit filed by an open-records group.
The group wants to obtain some specific Forms 990s, the informational tax documents filed by nonprofits, in a format that can be read by computers.
In theory, that shouldn’t be difficult since the nine nonprofits involved— including the American National Standards Institute, the New Horizons Foundation, and the International Code Council—submitted the forms electronically. But the IRS converts all 990s, no matter how they were filed, into images, rendering them useless for digital operations like searching multiple forms for information.
That means watchdog groups and those that provide information on charities, like Charity Navigator, GuideStar, and the Urban Institute, have to spend money to manually enter the data they get from the IRS before making it available to the public, even if it has previously been digitized.
The lawsuit against the IRS, filed by Public.Resource.Org, aims to end that practice.
Carl Malamud, who heads the group, is a longtime activist who successfully pushed the Securities and Exchange Commission to post corporate filings free online in the 1990s, among other projects.
He wants to do the same with the IRS, arguing that data should be readily available at no cost about a sector that represents more than 1.5 million tax-exempt organizations and more than $1.5-trillion in revenue.
Putting Open Data to Work for Communities
In Defense of Transit Apps
Mark Headd at Civic Innovations: “The civic technology community has a love-hate relationship with transit apps.
We love to, and often do, use the example of open transit data and the cottage industry of civic app development it has helped spawn as justification for governments releasing open data. Some of the earliest, most enduring and most successful civic applications have been built on transit data and there literally hundreds of different apps available.
The General Transit Feed Specification (GTFS), which has helped to encourage the release of transit data from dozens and dozens of transportation authorities across the country, is used as the model for the development of other open data standards. I once described work being done to develop a data standard for locations dispensing vaccinations as “GTFS for flu shots.”
But some in the civic technology community chafe at the overuse of transit apps as the example cited for the release of open data and engagement with outside civic hackers. Surely there are other examples we can point to that get at deeper, more fundamental problems with civic engagement and the operation of government. Is the best articulation of the benefits of open data and civic hacking a simple bus stop application?
Last week at Transparency Camp in DC, during a session I ran on open data, I was asked what data governments should focus on releasing as open data. I stated my belief that – at a minimum – governments should concentrate on The 3 B’s: Buses (transit data), Bullets (crime data) and Bucks (budget & expenditure data).
To be clear – transit data and the apps it helps generate are critical to the open data and civic technology movements. I think it is vital to exploring the role that transit apps have played in the development of the civic technology ecosystem and their impact on open data.
Story telling with transit data
Transit data supports more than just “next bus” apps. In fact, characterizing all transit apps this way does a disservice to the talented and creative people working to build things with transit data. Transit data supports a wide range of different visualizations that can tell an intimate, granular story about how a transit system works and how it’s operation impacts a city.
One inspiring example of this kind of app was developed recently by Mike Barry and Brian Card, and looked at the operation of MBTA in Boston. Their motive was simple:
We attempt to present this information to help people in Boston better understand the trains, how people use the trains, and how the people and trains interact with each other.
We’re able to tell nuanced stories about transit systems because the quality of data being released continues to expand and improve in quality. This happens because developers building apps in cities across the country have provided feedback to transit officials on what they want to see and the quality of what is provided.
Developers building the powerful visualizations we see today are standing on the shoulders of the people that built the “next bus” apps a few years ago. Without these humble apps, we don’t get to tell these powerful stories today.
Holding government accountable
Transit apps are about more than just getting to the train on time.
Support for transit system operations can run into the billions of dollars and affect the lives of millions of people in an urban area. With this much investment, it’s important that transit riders and taxpayers are able to hold officials accountable for the efficient operation of transit systems. To help us do this, we now have a new generation of transit apps that can examine things like the scheduled arrival and departure times of trains with their actual arrival and departure time.
Not only does this give citizens transparency into how well their transit system is being run, it offers a pathway for engagement – by knowing which routes are not performing close to scheduled times, transit riders and others can offer suggestions for changes and improvements.
A gateway to more open data
One of the most important things that transit apps can do is provide a pathway for more open data.
In Philadelphia, the city’s formal open data policy and the creation of an open data portal all followed after the efforts of a small group of developers working to obtain transit schedule data from the Southeastern Pennsylvania Transportation Authority (SEPTA). This group eventually built the region’s first transit app.
This small group pushed SEPTA to make their data open, and the Authority eventually embraced open data. This, in turn, raised the profile of open data with other city leaders and directly contributed to the adoption of an open data policy by the City of Philadelphia several years later. Without this simple transit app and the push for more open transit data, I don’t think this would have happened. Certainly not as soon as it did.
And it isn’t just big cities like Philadelphia. In Syracuse, NY – a small city with no tradition of civic hacking and no formal open data program – a group at a local hackathon decided that they wanted to build a platform for government open data.
The first data source they selected to focus on? Transit data. The first app they built? A transit app…”
The Emerging Science of Computational Anthropology
Emerging Technology From the arXiv: The increasing availability of big data from mobile phones and location-based apps has triggered a revolution in the understanding of human mobility patterns. This data shows the ebb and flow of the daily commute in and out of cities, the pattern of travel around the world and even how disease can spread through cities via their transport systems.
So there is considerable interest in looking more closely at human mobility patterns to see just how well it can be predicted and how these predictions might be used in everything from disease control and city planning to traffic forecasting and location-based advertising.
Today we get an insight into the kind of detailed that is possible thanks to the work of Zimo Yang at Microsoft research in Beijing and a few pals. These guys start with the hypothesis that people who live in a city have a pattern of mobility that is significantly different from those who are merely visiting. By dividing travelers into locals and non-locals, their ability to predict where people are likely to visit dramatically improves.
Zimo and co begin with data from a Chinese location-based social network called Jiepang.com. This is similar to Foursquare in the US. It allows users to record the places they visit and to connect with friends at these locations and to find others with similar interests.
The data points are known as check-ins and the team downloaded more than 1.3 million of them from five big cities in China: Beijing, Shanghai, Nanjing, Chengdu and Hong Kong. They then used 90 per cent of the data to train their algorithms and the remaining 10 per cent to test it. The Jiapang data includes the users’ hometowns so it’s easy to see whether an individual is checking in in their own city or somewhere else.
The question that Zimo and co want to answer is the following: given a particular user and their current location, where are they most likely to visit in the near future? In practice, that means analysing the user’s data, such as their hometown and the locations recently visited, and coming up with a list of other locations that they are likely to visit based on the type of people who visited these locations in the past.
Zimo and co used their training dataset to learn the mobility pattern of locals and non-locals and the popularity of the locations they visited. The team then applied this to the test dataset to see whether their algorithm was able to predict where locals and non-locals were likely to visit.
They found that their best results came from analysing the pattern of behaviour of a particular individual and estimating the extent to which this person behaves like a local. That produced a weighting called the indigenization coefficient that the researchers could then use to determine the mobility patterns this person was likely to follow in future.
In fact, Zimo and co say they can spot non-locals in this way without even knowing their home location. “Because non-natives tend to visit popular locations, like the Imperial Palace in Beijing and the Bund in Shanghai, while natives usually check in around their homes and workplaces,” they add.
The team say this approach considerably outperforms the mixed algorithms that use only individual visiting history and location popularity. “To our surprise, a hybrid algorithm weighted by the indigenization coefficients outperforms the mixed algorithm accounting for additional demographical information.”
It’s easy to imagine how such an algorithm might be useful for businesses who want to target certain types of travelers or local people. But there is a more interesting application too.
Zimo and co say that it is possible to monitor the way an individual’s mobility patterns change over time. So if a person moves to a new city, it should be possible to see how long it takes them to settle in.
One way of measuring this is in their mobility patterns: whether they are more like those of a local or a non-local. “We may be able to estimate whether a non-native person will behave like a native person after a time period and if so, how long in average a person takes to become a native-like one,” say Zimo and co.
That could have a fascinating impact on the way anthropologists study migration and the way immigrants become part of a local community. This is computational anthropology a science that is clearly in its early stages but one that has huge potential for the future.”
Ref: arxiv.org/abs/1405.7769 : Indigenization of Urban Mobility
Making cities smarter through citizen engagement
Vaidehi Shah at Eco-Business: “Rapidly progressing information communications technology (ICT) is giving rise to an almost infinite range of innovations that can be implemented in cities to make them more efficient and better connected. However, in order for technology to yield sustainable solutions, planners must prioritise citizen engagement and strong leadership.
This was the consensus on Tuesday at the World Cities Summit 2014, where representatives from city and national governments, technology firms and private sector organisations gathered in Singapore to discuss strategies and challenges to achieving sustainable cities in the future.
Laura Ipsen, Microsoft corporate vice president for worldwide public sector, identified globalisation, social media, big data, and mobility as the four major technological trends prevailing in cities today, as she spoke at the plenary session with a theme on “The next urban decade: critical challenges and opportunities”.
Despite these increasing trends, she cautioned, “technology does not build infrastructure, but it does help better engage citizens and businesses through public-private partnerships”.
For example, “LoveCleanStreets”, an online tool developed by Microsoft and partners, enables London residents to report infrastructure problems such as damaged roads or signs, shared Ipsen.
“By engaging citizens through this application, cities can fix problems early, before they get worse,” she said.
In Singapore, the ‘MyWaters’ app of PUB, Singapore’s national water agency, is also a key tool for the government to keep citizens up-to-date of water quality and safety issues in the country, she added.
Even if governments did not actively develop solutions themselves, simply making the immense amounts of data collected by the city open to businesses and citizens could make a big difference to urban liveability, Mark Chandler, director of the San Francisco Mayor’s Office of International Trade and Commerce, pointed out.
Opening up all of the data collected by San Francisco, for instance, yielded 60 free mobile applications that allow residents to access urban solutions related to public transport, parking, and electricity, among others, he explained. This easy and convenient access to infrastructure and amenities, which are a daily necessity, is integral to “a quality of life that keeps the talented workforce in the city,” Chandler said….”
Twitter releasing trove of user data to scientists for research
Joe Silver at ArsTechnica: “Twitter has a 200-million-strong and ever-growing user base that broadcasts 500 million updates daily. It has been lauded for its ability to unsettle repressive political regimes, bring much-needed accountability to corporations that mistreat their customers, and combat other societal ills (whether such characterizations are, in fact, accurate). Now, the company has taken aim at disrupting another important sphere of human society: the scientific research community.
Back in February, the site announced its plan—in collaboration with Gnip—to provide a handful of research institutions with free access to its data sets from 2006 to the present. It’s a pilot program called “Twitter Data Grants,” with the hashtag #DataGrants. At the time, Twitter’s engineering blog explained the plan to enlist grant applications to access its treasure trove of user data:
Twitter has an expansive set of data from which we can glean insights and learn about a variety of topics, from health-related information such as when and where the flu may hit to global events like ringing in the new year. To date, it has been challenging for researchers outside the company who are tackling big questions to collaborate with us to access our public, historical data. Our Data Grants program aims to change that by connecting research institutions and academics with the data they need.
In April, Twitter announced that, after reviewing the more than 1,300 proposals submitted from more than 60 different countries, it had selected six institutions to provide with data access. Projects approved included a study of foodborne gastrointestinal illnesses, a study measuring happiness levels in cities based on images shared on Twitter, and a study using geosocial intelligence to model urban flooding in Jakarta, Indonesia. There’s even a project exploring the relationship between tweets and sports team performance.
Twitter did not directly respond to our questions on Tuesday afternoon regarding the specific amount and types of data the company is providing to the six institutions. But in its privacy policy, Twitter explains that most user information is intended to be broadcast widely. As a result, the company likely believes that sharing such information with scientific researchers is well within its rights, as its services “are primarily designed to help you share information with the world,” Twitter says. “Most of the information you provide us is information you are asking us to make public.”
While mining such data sets will undoubtedly aid scientists in conducting experiments for which similar data was previously either unavailable or quite limited, these applications raise some legal and ethical questions. For example, Scientific American has asked whether Twitter will be able to retain any legal rights to scientific findings and whether mining tweets (many of which are not publicly accessible) for scientific research when Twitter users have not agreed to such uses is ethically sound.
In response, computational epidemiologists Caitlin Rivers and Bryan Lewis have proposed guidelines for ethical research practices when using social media data, such as avoiding personally identifiable information and making all the results publicly available….”
The Trend towards “Smart Cities”
Chien-Chu Chen in the International Journal of Automation and Smart Technology (AUSMT): “Looking back over the past century, the steady pace of development in many of the world’s cities has resulted in a situation where a high percentage of these cities are now faced with the problem of aging, decrepit urban infrastructure; a considerable number of cities are having to undertake large-scale infrastructure renewal projects. While creating new opportunities in the area of infrastructure, ongoing urbanization is also creating problems, such as excessive consumption of water, electric power and heat energy, environmental pollution, increased greenhouse gas emissions, traffic jams, and the aging of the existing residential housing stock, etc. All of these problems present a challenge to cities’ ability to achieve sustainable development. In response to these issues, the concept of the “smart city” has grown in popularity throughout the world. The aim of smart city initiatives is to make the city a vehicle for “smartification” through the integration of different industries and sectors. As initiatives of this kind move beyond basic automation into the realm of real “smartification,” the smart city concept is beginning to take concrete form….”
Free Online Lawmaking Platform for Washington, D.C.
OpenGov Foundation: “At-Large Councilmember David Grosso and The OpenGov Foundation today launched the beta version of MadisonDC, a free online lawmaking tool that empowers citizens to engage directly with their elected officials – and the policymaking process itself – by commenting on, proposing changes to, and debating real D.C. Council legislation. Grosso is the first-ever District elected official to give citizens the opportunity to log on and legislate, putting him at the forefront of a nation-wide movement reinventing local legislatures with technology. Three bills are now open for crowdsourcing on MadisonDC: a plan to fully legalize marijuana, a proposal to make zoning laws more friendly to urban farmers, and legislation to create open primary elections….
MadisonDC is the District of Columbia’s version of the freeMadison software that reinvents government for the Internet Age. Madison 1.0 powered the American people’s successful defense of Internet freedom from Congressional threats. It delivered the first crowdsourced bill in the history of the U.S. Congress. And now, the non-partisan, non-profit OpenGov Foundation has released Madison 2.0, empowering you to participate in your government, efficiently access your elected officials, and hold them accountable.”
Three projects meet the European Job Challenge and receive the Social Innovation Prize
EU Press Release: “Social innovation can be a tool to create new or better jobs, while giving an answer to pressing challenges faced by Europe. Today, Michel Barnier, European Commissioner, has awarded three European Social Innovation prizes to ground-breaking ideas to create new types of work and address social needs. The winning projects aim to help disadvantaged women by employing them to create affordable and limited fashion collections, create jobs in the sector of urban farming, and convert abandoned social housing into learning spaces and entrepreneurship labs.
After the success of the first edition in 2013, the European Commission launched a second round of the Social Innovation Competition in memory of Diogo Vasconcelos1. Its main goal was to invite Europeans to propose new solutions to answer The Job Challenge. The Commission received 1,254 ideas out of which three were awarded with a prize of €30,000 each.
Commissioner Michel Barnier said: “We believe that the winning projects can take advantage of unmet social needs and create sustainable jobs. I want these projects to be scaled up and replicated and inspire more social innovations in Europe. We need to tap into this potential to bring innovative solutions to the needs of our citizens and create new types of work.”
More informationon the Competition page
More jobs for Europe – three outstanding ideas
The following new and exceptional ideas are the winners of the second edition of the European Social Innovation Competition:
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‘From waste to wow! QUID project’ (Italy): fashion business demands perfection, and slightly damaged textile cannot be used for top brands. The project intends to recycle this first quality waste into limited collections and thereby provide jobs to disadvantaged women. This is about creating highly marketable products and social value through recycling.
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‘Urban Farm Lease’ (Belgium): urban agriculture could provide 6,000 direct jobs in Brussels, and an additional 1,500 jobs considering indirect employment (distribution, waste management, training or events). The project aims at providing training, connection and consultancy so that unemployed people take advantage of the large surfaces available for agriculture in the city (e.g. 908 hectares of land or 394 hectares of suitable flat roofs).
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‘Voidstarter’ (Ireland): all major cities in Europe have “voids”, units of social housing which are empty because city councils have insufficient budgets to make them into viable homes. At the same time these cities also experience pressure with social housing provision and homelessness. Voidstarter will provide unemployed people with learning opportunities alongside skilled tradespersons in the refurbishing of the voids.”