AI And Open Data Show Just How Often Cars Block Bus And Bike Lanes

Curated on Posted on by Stefaan Verhulst

Eillie Anzilotti in Fast Company: “…While anyone who bikes or rides a bus in New York City knows intuitively that the lanes are often blocked, there’s been little data to back up that feeling apart from the fact that last year, the NYPD issues 24,000 tickets for vehicles blocking bus lanes, and around 79,000 to cars in the bike lane. By building the algorithm, Bell essentializes what engaged citizenship and productive use of open data looks like. The New York City Department of Transportation maintains several hundred video cameras throughout the city; those cameras feed images in real time to the DOT’s open-data portal. Bell downloaded a week’s worth of footage from that portal to analyze.

To build his computer algorithm to do the analysis, he fed around 2,000 images of buses, cars, pedestrians, and vehicles like UPS trucks into TensorFlow, Google’s open-source framework that the tech giant is using to train autonomous vehicles to recognize other road users. “Because of the push into AVs, machine learning in general and neural networks have made lots of progress, because they have to answer the same questions of: What is this vehicle, and what is it going to do?” Bell says. After several rounds of processing, Bell was able to come up with an algorithm that fairly faultlessly could determine if a vehicle at the bus stop was, in fact, a bus, or if it was something else that wasn’t supposed to be there.

As cities and governments, spurred by organizations like OpenGov, have moved to embrace transparency and open data, the question remains: So, what do you do with it?

For Bell, the answer is that citizens can use it to empower themselves. “I’m a little uncomfortable with cameras and surveillance in cities,” Bell says. “But agencies like the NYPD and DOT have already made the decision to put the cameras up. We don’t know the positive and negative outcomes if more and more data from cameras is opened to the public, but if the cameras are going in, we should know what data they’re collecting and be able to access it,” he says. He’s made his algorithm publicly available in the hopes that more people will use data to investigate the issue on their own streets, and perhaps in other cities….Bell is optimistic that open data can empower more citizens to identify issues in their own cities and bring a case for why they need to be addressed….(More)”.

Data for Development: What’s next? Concepts, trends and recommendations

Curated on Posted on by Stefaan Verhulst

Report by the WebFoundation: “The exponential growth of data provides powerful new ways for governments and companies to understand and respond to challenges and opportunities. This report, Data for Development: What’s next, investigates how organisations working in international development can leverage the growing quantity and variety of data to improve their investments and projects so that they better meet people’s needs.

Investigating the state of data for development and identifying emerging data trends, the study provides recommendations to support German development cooperation actors seeking to integrate data strategies and investments in their work. These insights can guide any organisation seeking to use data to enhance their development work.

The research considers four types of data: (1) big data, (2) open data, (3) citizen-generated data and (4) real-time data, and examines how they are currently being used in development-related policy-making and how they might lead to better development outcomes….(More)”.

Could the open government movement shut the door on Freedom of Information

Curated on Posted on by Stefaan Verhulst

,  and  in The Conversation: “For democracy to work, citizens need to know what their government is doing. Then they can hold government officials and institutions accountable.

Over the last 50 years, Freedom of Information – or FOI – laws have been one of the most useful methods for citizens to learn what government is doing. These state and federal laws give people the power to request, and get, government documents. From everyday citizens to journalists, FOI laws have proven a powerful way to uncover the often-secret workings of government.

But a potential threat is emerging – from an unexpected place – to FOI laws.

We are scholars of government administration, ethics and transparency. And our research leads us to believe that while FOI laws have always faced many challenges, including resistance, evasion,  and poor implementation and enforcement, the last decade has brought a different kind of challenge in the form of a new approach to transparency….

The open government movement could help FOI implementation. Government information posted online, which is a core goal of open government advocates, can reduce the number of FOI requests. Open government initiatives can explicitly promote FOI by encouraging the passage of FOI laws, offering more training for officials who fill FOI requests, and developing technologies to make it easier to process and track FOI requests.

On the other hand, the relationship between open government and FOI may not always be positive in practice.

First, as with all kinds of public policy issues, resources – both money and political attention – are inherently scarce. Government officials now have to divide their attention between FOI and other open government initiatives. And funders now have to divide their financial resources between FOI and other open government initiatives.

Second, the open government reform movement as well as the FOI movement have long depended on nonprofit advocacy groups – from the National Freedom of Information Coalition and its state affiliates to the Sunlight Foundation – to obtain and disseminate government information. This means that the financial stability of those nonprofit groups is crucial. But their efforts, as they grow, may each only get a shrinking portion of the total amount of grant money available. Freedominfo.org, a website for gathering and comparing information on FOI laws around the world, had to suspend its operations in 2017 due to resources drying up.

We believe that priorities among government officials and good government advocates may also shift away from FOI. At a time when open data is “hot,” FOI programs could get squeezed as a result of this competition. Further, by allowing governments to claim credit for more politically convenient reforms such as online data portals, the open government agenda may create a false sense of transparency – there’s a lot more government information that isn’t available in those portals.

This criticism was leveled recently against Kenya, whose government launched a high-profile open data portal for publishing data on government performance and activities in 2011, yet delayed passage of an FOI law until 2016.

Similarly, in the United Kingdom, one government minister said in 2012,“I’d like to make Freedom of Information redundant, by pushing out so much data that people won’t have to ask for it.”…(More)”

Trustworthy data will transform the world

Curated on Posted on by Stefaan Verhulst

John Thornhill at the Financial Times: “The internet’s original sin was identified as early as 1993 in a New Yorker cartoon. “On the internet, nobody knows you’re a dog,” the caption ran beneath an illustration of a pooch at a keyboard. That anonymity has brought some benefits. But it has also created myriad problems, injecting distrust into the digital world. If you do not know the provenance and integrity of information and data, how can you trust their veracity?

That has led to many of the scourges of our times, such as cyber crime, identity theft and fake news. In his Alan Turing Institute lecture in London last week, the American computer scientist Sandy Pentland outlined the massive gains that could result from trusted data.

The MIT professor argued that the explosion of such information would give us the capability to understand our world in far more detail than ever before. Most of what we know in the fields of sociology, psychology, political science and medicine is derived from tiny experiments in controlled environments. But the data revolution enables us to observe behaviour as it happens at mass scale in the real world. That feedback could provide invaluable evidence about which theories are most valid and which policies and products work best.

The promise is that we make soft social science harder and more predictive. That, in turn, could lead to better organisations, fairer government, and more effective monitoring of our progress towards achieving collective ambitions, such as the UN’s sustainable development goals. To take one small example, Mr Pentland illustrated the strong correlation between connectivity and wealth. By studying the telephone records of 100,000 users in south-east Asia, researchers have plotted social connectivity against income. The conclusion: “The more diverse your connections, the more money you have.” This is not necessarily a causal relationship but it does have a strong causal element, he suggested.

Similar studies of European cities have shown an almost total segregation between groups of different socio-economic status. That lack of connectivity has to be addressed if our politics is not to descend further into a meaningless dialogue.

Data give us a new way to measure progress.

For years, the Open Data movement has been working to create public data sets that can better inform decision making. This worldwide movement is prising open anonymised public data sets, such as transport records, so that they can be used by academics, entrepreneurs and civil society groups. However, much of the most valuable data is held by private entities, notably the consumer tech companies, telecoms operators, retailers and banks. “The big win would be to include private data as a public good,” Mr Pentland said….(More)”.

Using Open Data for Public Services

Curated on Posted on by Stefaan Verhulst

New report by the Open Data Institute:  “…Today we’re publishing our initial findings based on examining 8 examples where open data supports the delivery of a public service. We have defined 3 high-level ‘patterns’ for how open data is used in public services. We think these could be helpful for others looking to redesign and deliver better services.

The patterns are summarised in the table below:

The first pattern is perhaps the model which everyone is most familiar with as it’s used by the likes of Citymapper, who use open transport data from Transport for London to inform passengers about routes and timings, and other citizen-focused apps. Data is released by a public sector organisation about a public service and a third organisation uses this data to provide a complementary service, online or face-face, to help citizens use the public service.

The second pattern involves the release of open data in the service delivery chain. Open data is used to plan public service delivery and make service delivery chains more efficient. Examples provided in the report include local authorities’ release of open spending, contract and tender data, which is used by Spend Network to support better value for money in public expenditure.

In the third pattern, public sector organisations commissioning services and external organisations involved in service delivery make strategic decisions based on insights and patterns revealed by open data. Visualisations of open data can inform policies on job seeker allowance, as shown in the example from the Department for Work and Pensions in the report.

As well as identifying these patterns, we have created ecosystem maps of the public services we have examined to help understand the relationships and the mechanisms by which open data supports each of them….

Having compared the ecosystems of the examples we have considered so far, the report sets out practical recommendations for those involved in the delivery of public services and for Central Government for the better use of open data in the delivery of public services.

The recommendations are focused on organisational collaboration; technology infrastructure, digital skills and literacy; open standards for data; senior level championing; peer networks; intermediaries; and problem focus….(More)”.

Global Fishing Watch And The Power Of Data To Understand Our Natural World

Curated on Posted on by Stefaan Verhulst

Kalev Leetaru at Forbes: “A year and a half ago I wrote about the public debut of the Global Fishing Watch project as a showcase of what becomes possible when massive datasets are made accessible to the general public through easy-to-use interfaces that allow them to explore the planet they inhabit. At the time I noted how the project drove home the divide between the “glittering technological innovation of Silicon Valley and the technological dark ages of the development community” and what becomes possible when technologists and development organizations come together to apply incredible technology not for commercial gain, but rather to save the world itself. Continuing those efforts, last week Global Fishing Watch launched what it describes as the “the first ever dataset of global industrial fishing activities (all countries, all gears),” making the entire dataset freely accessible to seed new scientific, activist, governmental, journalistic and citizen understanding of the state of global fishing.

The Global Fishing Watch project stands as a powerful model for data-driven development work done right and hopefully, the rise of notable efforts like it will eventually catalyze the broader development community to emerge from the stone age of technology and more openly embrace the technological revolution. While it has a very long way to go, there are signs of hope for the development community as pockets of innovation begin to infuse the power of data-driven decision making and situational awareness into everything from disaster response to proactive planning to shaping legislative action.

Bringing technologists and development organizations together is not always that easy and the most creative solutions aren’t always to be found among the “usual suspects.” Open data and open challenges built upon them offer the potential for organizations to reach beyond the usual communities they interact with and identify innovative new approaches to the grand challenges of their fields. Just last month a collaboration of the World Bank, WeRobotics and OpenAerialMap launched a data challenge to apply deep learning to assess aerial imagery in the immediate aftermath of disasters to determine the impact to food producing trees and to road networks. By launching the effort as an open AI challenge, the goal is to reach the broader AI and open development communities at the forefront of creative and novel algorithmic approaches….(More)”.

Open data sharing and the Global South—Who benefits?

Curated on Posted on by Stefaan Verhulst

David Serwadda et al in Science: “A growing number of government agencies, funding organizations, and publishers are endorsing the call for increased data sharing, especially in biomedical research, many with an ultimate goal of open data. Open data is among the least restrictive forms of data sharing, in contrast to managed access mechanisms, which typically have terms of use and in some cases oversight by the data generators themselves. But despite an ethically sound rationale and growing support for open data sharing in many parts of the world, concerns remain, particularly among researchers in low- and middle-income countries (LMICs) in Africa, Latin America, and parts of Asia and the Middle East that comprise the Global South. Drawing on our perspective as researchers and ethicists working in the Global South, we see opportunities to improve community engagement, raise awareness, and build capacity, all toward improving research and data sharing involving researchers in LMICs…African scientists have expressed concern that open data compromises national ownership and reopens the gates for “parachute-research” (i.e., Northern researchers absconding with data to their home countries). Other LMIC researchers have articulated fears over free-riding scientists using the data collected by others for their own career advancement …(More)”

Who Killed Albert Einstein? From Open Data to Murder Mystery Games

Curated on Posted on by Stefaan Verhulst

Gabriella A. B. Barros et al at arXiv: “This paper presents a framework for generating adventure games from open data. Focusing on the murder mystery type of adventure games, the generator is able to transform open data from Wikipedia articles, OpenStreetMap and images from Wikimedia Commons into WikiMysteries. Every WikiMystery game revolves around the murder of a person with a Wikipedia article, and populates the game with suspects who must be arrested by the player if guilty of the murder or absolved if innocent. Starting from only one person as the victim, an extensive generative pipeline finds suspects, their alibis, and paths connecting them from open data, transforms open data into cities, buildings, non-player characters, locks and keys and dialog options. The paper describes in detail each generative step, provides a specific playthrough of one WikiMystery where Albert Einstein is murdered, and evaluates the outcomes of games generated for the 100 most influential people of the 20th century….(More)”.

Building Trust in Data and Statistics

Curated on Posted on by Stefaan Verhulst

Shaida Badiee at UN World Data Forum: …What do we want for a 2030 data ecosystem?

Hope to achieve: A world where data are part of the DNA and culture of decision-making, used by all and valued as an important public good. A world where citizens trust the systems that produce data and have the skills and means to use and verify their quality and accuracy. A world where there are safeguards in place to protect privacy, while bringing the benefits of open data to all. In this world, countries value their national statistical systems, which are working independently with trusted partners in the public and private sectors and citizens to continuously meet the changing and expanding demands from data users and policy makers. Private sector data generators are generously sharing their data with public sector. And gaps in data are closing, making the dream of “leaving no one behind” come true, with SDG goals on the path to being met by 2030.

Hope to avoid: A world where large corporations control the bulk of national and international data and statistics with only limited sharing with the public sector, academics, and citizens. The culture of every man for himself and who pays, wins, dominates data sharing practices. National statistical systems are under-resourced and under-valued, with low trust from users, further weakening them and undermining their independence from political interference and their ability to control quality. The divide between those who have and those who do not have access, skills, and the ability to use data for decision-making and policy has widened. Data systems and their promise to count the uncounted and “leave no one behind” are falling behind due to low capacity and poor standards and institutions, and the hope of the 2030 agenda is fading.

With this vision in mind, are we on the right path? An optimist would say we are closer to the data ecosystem that we want to achieve. However, there are also some examples of movement in the wrong direction. There is no magic wand to make our wish come true, but a powerful enabler would be building trust in data and statistics. Therefore, this should be included as a goal in all our data strategies and action plans.

Here are some important building blocks underlying trust in data and statistics:

  1. Building strong organizational infrastructure, governance, and partnerships;
  2. Following sound data standards and principles for production, sharing, interoperability, and dissemination; and
  3. Addressing the last mile in the data value chain to meet users’ needs, create value with data, and ensure meaningful impacts…(More)”.

The Entrepreneurial Impact of Open Data

Curated on Posted on by Stefaan Verhulst

Sheena Iyengar and  Patrick Bergemann at Opening Governance Research Network: “…To understand how open data is being used to spur innovation and create value, the Governance Lab (GovLab) at NYU Tandon School of Engineering conducted the first ever census of companies that use open data. Using outreach campaigns, expert advice and other sources, they created a database of more than 500 companies founded in the United States called the Open Data 500 (OD500). Among the small and medium enterprises identified that use government data, the most common industries they found are data and technology, followed by finance and investment, business and legal services, and healthcare.

In the context of our collaboration with the GovLab-chaired MacArthur Foundation Research Network on Opening Governance, we sought to dig deeper into the broader impact of open data on entrepreneurship. To do so we combined the OD500 with databases on startup activity from Crunchbase and AngelList. This allowed us to look at the trajectories of open data companies from their founding to the present day. In particular, we compared companies that use open data to similar companies with the same founding year, location and industry to see how well open data companies fare at securing funding along with other indicators of success.

We first looked at the extent to which open data companies have access to investor capital, wondering if open data companies have difficulty gaining funding because their use of public data may be perceived as insufficiently innovative or proprietary. If this is the case, the economic impact of open data may be limited. Instead, we found that open data companies obtain more investors than similar companies that do not use open data. Open data companies have, on average, 1.74 more investors than similar companies founded at the same time. Interestingly, investors in open data companies are not a specific group who specialize in open data startups. Instead, a wide variety of investors put money into these companies. Of the investors who funded open data companies, 59 percent had only invested in one open data company, while 81 percent had invested in one or two. Open data companies appear to be appealing to a wide range of investors….(More)”.