The Participatory Approach to Open Data

Curated on Posted on by Stefaan Verhulst

Christopher Whitaker at the SmartChicagoCollaborative: “…Having vast stores of government data is great, but to make this data useful – powerful – takes a different type of approach. The next step in the open data movement will be about participatory data.

Systems that talk back

One of the great advantages behind Chicago’s 311 ServiceTracker is that when you submit something to the system, the system has the capacity to talk back giving you a tracking number and an option to get email updates about your request. What also happens is that as soon as you enter your request, the data get automatically uploaded into the city’s data portal giving other 311 apps like SeeClickFix and access to the information as well…

Participatory Legislative Apps

We already see a number of apps that allow user to actively participate using legislative data.
At the Federal level, apps like PopVox allow users to find and track legislation that’s making it’s way through Congress. The app then allows users to vote if they approve or disapprove of a particular bill. You can then send explain your reasoning in a message that will be sent to all of your elected officials. The app makes it easier for residents to send feedback on legislation by creating a user interface that cuts through the somewhat difficult process of keeping tabs on legislation.
At the state level, New York’s OpenLegislation site allows users to search for state legislation and provide commentary on each resolution.
At the local level, apps like Councilmatic allows users to post comments on city legislation – but these comments aren’t mailed or sent to alderman the same way PopVox does. The interaction only works if the alderman are also using Councilmatic to receive feedback…

Crowdsourced Data

Chicago has hardwired several datasets into their computer systems, meaning that this data is automatically updated as the city does the people’s business.
But city governments can’t be everywhere at once. There are a number of apps that are designed to gather information from residents to better understand what’s going on their cities.
In Gary, the city partnered with the University of Chicago and LocalData to collect information on the state of buildings in Gary, IN. LocalData is also being used in Chicago, Houston, and Detroit by both city governments and non-profit organizations.
Another method the City of Chicago has been using to crowdsource data has been to put several of their datasets on GitHub and accept pull requests on that data. (A pull request is when one developer makes a change to a code repository and asks the original owner to merge the new changes into the original repository.) An example of this is bikers adding private bike rack locations to the city’s own bike rack dataset.

Going from crowdsourced to participatory

Shareabouts is a mapping platform by OpenPlans that gives city the ability to collect resident input on city infrastructure. Chicago’s Divvy Bikeshare program is using the tool to collect resident feedback on where the new Divvy stations should go. The app allows users to comment on suggested locations and share the discussion on social media.
But perhaps the most unique participatory app has been piloted by the City of South Bend, Indiana. CityVoice is a Code for America fellowship project designed to get resident feedback on abandoned buildings in South Bend…. (More)”

Three Things that a Good Infographic Needs

Curated on Posted on by Stefaan Verhulst

Antonio Salazar at BBVA Open Mind: “…A good infographic can save lives. Or almost, like the map drawn by Dr. Snow, who in 1854 tried to prove —with not much success, it’s true— that cholera spread by water. Not all graphics can be so ambitious, but when they hope to become a very powerful vehicle for knowledge, these are three elements that an excellent infographic should have. In order:

1. Rigor

This is taken for granted. Or not. This chart from Pravda (not Miuccia, the Soviet daily) is manipulated graphically to give the impression of growth:
OpenMind-antonio-salazar-infografia-tips-2
But rigor does not only mean accuracy, it means respect for the data in a broader sense. Letting them speak beyond the ornamentation, avoiding the “ducks” referred to by Edward R. Tufte.  Guiding our eye so the reader can discover them one step at a time. This brings us to the second quality:

2. Depth

The beauty of the data sometimes lies in their implications and their connections. This is why a good  infographic should be understandable at first sight, but also, when viewed for a second time, enable the reader to take pleasure in the data. Perhaps in the process of reasoning, both analytical and visual, that a graphic requires, we may come to a conclusion we hadn’t imagined. This is why a good infographic should have layers of information. Any infographic by Francesco Franchi is a wonder of visual richness and provides hours of entertainment and learning.

OpenMind-antonio-salazar-infografia-tips-3

Infographic by Francesco Franchi and Alessandro Giberti on Chinese imports published in IL

3. Narration

Storytelling in today’s parlance. When time, space and even meteorology are combined skillfully to tell a story through the data….”

Big Data in Action for Development

Curated on Posted on by Stefaan Verhulst

New report by the Worldbank: “Data provide critical inputs in designing effective development policy recommendations, supporting their implementation, and evaluating results. In this new report “Big Data in Action for Development,” the World Bank Group collaborated with Second Muse, a global innovation agency, to explore big data’s transformative potential for socioeconomic development.  The report develops a conceptual framework to work with big data in the development sector and presents a variety of case studies that lay out big data’s innovations, challenges, and opportunities.”

Turns Out the Internet Is Bad at Guessing How Many Coins Are in a Jar

Curated on Posted on by Stefaan Verhulst

Eric B. Steiner at Wired: “A few weeks ago, I asked the internet to guess how many coins were in a huge jar…The mathematical theory behind this kind of estimation game is apparently sound. That is, the mean of all the estimates will be uncannily close to the actual value, every time. James Surowiecki’s best-selling book, Wisdom of the Crowd, banks on this principle, and details several striking anecdotes of crowd accuracy. The most famous is a 1906 competition in Plymouth, England to guess the weight of an ox. As reported by Sir Francis Galton in a letter to Nature, no one guessed the actual weight of the ox, but the average of all 787 submitted guesses was exactly the beast’s actual weight….
So what happened to the collective intelligence supposedly buried in our disparate ignorance?
Most successful crowdsourcing projects are essentially the sum of many small parts: efficiently harvested resources (information, effort, money) courtesy of a large group of contributors. Think Wikipedia, Google search results, Amazon’s Mechanical Turk, and KickStarter.
But a sum of parts does not wisdom make. When we try to produce collective intelligence, things get messy. Whether we are predicting the outcome of an election, betting on sporting contests, or estimating the value of coins in a jar, the crowd’s take is vulnerable to at least three major factors: skill, diversity, and independence.
A certain amount of skill or knowledge in the crowd is obviously required, while crowd diversity expands the number of possible solutions or strategies. Participant independence is important because it preserves the value of individual contributors, which is another way of saying that if everyone copies their neighbor’s guess, the data are doomed.
Failure to meet any one of these conditions can lead to wildly inaccurate answers, information echo, or herd-like behavior. (There is more than a little irony with the herding hazard: The internet makes it possible to measure crowd wisdom and maybe put it to use. Yet because people tend to base their opinions on the opinions of others, the internet ends up amplifying the social conformity effect, thereby preventing an accurate picture of what the crowd actually thinks.)
What’s more, even when these conditions—skill, diversity, independence—are reasonably satisfied, as they were in the coin jar experiment, humans exhibit a whole host of other cognitive biases and irrational thinking that can impede crowd wisdom. True, some bias can be positive; all that Gladwellian snap-judgment stuff. But most biases aren’t so helpful, and can too easily lead us to ignore evidence, overestimate probabilities, and see patterns where there are none. These biases are not vanquished simply by expanding sample size. On the contrary, they get magnified.
Given the last 60 years of research in cognitive psychology, I submit that Galton’s results with the ox weight data were outrageously lucky, and that the same is true of other instances of seemingly perfect “bean jar”-styled experiments….”

Democratizing Inequalities: Dilemmas of the New Public Participation

Curated on Posted on by Stefaan Verhulst
New book edited by Caroline W. Lee, Michael McQuarrie and Edward T. Walker: “Opportunities to “have your say,” “get involved,” and “join the conversation” are everywhere in public life. From crowdsourcing and town hall meetings to government experiments with social media, participatory politics increasingly seem like a revolutionary antidote to the decline of civic engagement and the thinning of the contemporary public sphere. Many argue that, with new technologies, flexible organizational cultures, and a supportive policymaking context, we now hold the keys to large-scale democratic revitalization.
Democratizing Inequalities shows that the equation may not be so simple. Modern societies face a variety of structural problems that limit potentials for true democratization, as well as vast inequalities in political action and voice that are not easily resolved by participatory solutions. Popular participation may even reinforce elite power in unexpected ways. Resisting an oversimplified account of participation as empowerment, this collection of essays brings together a diverse range of leading scholars to reveal surprising insights into how dilemmas of the new public participation play out in politics and organizations. Through investigations including fights over the authenticity of business-sponsored public participation, the surge of the Tea Party, the role of corporations in electoral campaigns, and participatory budgeting practices in Brazil, Democratizing Inequalities seeks to refresh our understanding of public participation and trace the reshaping of authority in today’s political environment.”

Businesses dig for treasure in open data

Curated on Posted on by Stefaan Verhulst

Lindsay Clark in ComputerWeekly: “Open data, a movement which promises access to vast swaths of information held by public bodies, has started getting its hands dirty, or rather its feet.
Before a spade goes in the ground, construction and civil engineering projects face a great unknown: what is down there? In the UK, should someone discover anything of archaeological importance, a project can be halted – sometimes for months – while researchers study the site and remove artefacts….
During an open innovation day hosted by the Science and Technologies Facilities Council (STFC), open data services and technology firm Democrata proposed analytics could predict the likelihood of unearthing an archaeological find in any given location. This would help developers understand the likely risks to construction and would assist archaeologists in targeting digs more accurately. The idea was inspired by a presentation from the Archaeological Data Service in the UK at the event in June 2014.
The proposal won support from the STFC which, together with IBM, provided a nine-strong development team and access to the Hartree Centre’s supercomputer – a 131,000 core high-performance facility. For natural language processing of historic documents, the system uses two components of IBM’s Watson – the AI service which famously won the US TV quiz show Jeopardy. The system uses SPSS modelling software, the language R for algorithm development and Hadoop data repositories….
The proof of concept draws together data from the University of York’s archaeological data, the Department of the Environment, English Heritage, Scottish Natural Heritage, Ordnance Survey, Forestry Commission, Office for National Statistics, the Land Registry and others….The system analyses sets of indicators of archaeology, including historic population dispersal trends, specific geology, flora and fauna considerations, as well as proximity to a water source, a trail or road, standing stones and other archaeological sites. Earlier studies created a list of 45 indicators which was whittled down to seven for the proof of concept. The team used logistic regression to assess the relationship between input variables and come up with its prediction….”

The Emerging Science of Human-Data Interaction

Curated on Posted on by Stefaan Verhulst

Emerging Technology From the arXiv: “The rapidly evolving ecosystems associated with personal data is creating an entirely new field of scientific study, say computer scientists. And this requires a much more powerful ethics-based infrastructure….
Now Richard Mortier at the University of Nottingham in the UK and a few pals say the increasingly complex, invasive and opaque use of data should be a call to arms to change the way we study data, interact with it and control its use. Today, they publish a manifesto describing how a new science of human-data interaction is emerging from this “data ecosystem” and say that it combines disciplines such as computer science, statistics, sociology, psychology and behavioural economics.
They start by pointing out that the long-standing discipline of human-computer interaction research has always focused on computers as devices to be interacted with. But our interaction with the cyber world has become more sophisticated as computing power has become ubiquitous, a phenomenon driven by the Internet but also through mobile devices such as smartphones. Consequently, humans are constantly producing and revealing data in all kinds of different ways.
Mortier and co say there is an important distinction between data that is consciously created and released such as a Facebook profile; observed data such as online shopping behaviour; and inferred data that is created by other organisations about us, such as preferences based on friends’ preferences.
This leads the team to identify three key themes associated with human-data interaction that they believe the communities involved with data should focus on.
The first of these is concerned with making data, and the analytics associated with it, both transparent and comprehensible to ordinary people. Mortier and co describe this as the legibility of data and say that the goal is to ensure that people are clearly aware of the data they are providing, the methods used to draw inferences about it and the implications of this.
Making people aware of the data being collected is straightforward but understanding the implications of this data collection process and the processing that follows is much harder. In particular, this could be in conflict with the intellectual property rights of the companies that do the analytics.
An even more significant factor is that the implications of this processing are not always clear at the time the data is collected. A good example is the way the New York Times tracked down an individual after her seemingly anonymized searches were published by AOL. It is hard to imagine that this individual had any idea that the searches she was making would later allow her identification.
The second theme is concerned with giving people the ability to control and interact with the data relating to them. Mortier and co describe this as “agency”. People must be allowed to opt in or opt out of data collection programs and to correct data if it turns out to be wrong or outdated and so on. That will require simple-to-use data access mechanisms that have yet to be developed
The final theme builds on this to allow people to change their data preferences in future, an idea the team call “negotiability”. Something like this is already coming into force in the European Union where the Court of Justice has recently begun to enforce the “right to be forgotten”, which allows people to remove information from search results under certain circumstances….”
Ref: http://arxiv.org/abs/1412.6159  Human-Data Interaction: The Human Face of the Data-Driven Society

“Smart” Cities and the Urban Digital Revolution

Curated on Posted on by Stefaan Verhulst

Shawn DuBravac at Re/Code: “Smog, sewage and congestion are three of the hallmarks of contemporary urban living. But these downsides to city living are gradually becoming things of the past. City planners are finding new ways to address these inefficiencies, leveraging connected technology to create smarter hubs that work for city dwellers.
Welcome to the era of “smart” cities. Advances in wireless sensor systems, information and communication technology (ICT), and infrastructure allow cities to collect and curate huge amounts of data capable of sustaining and improving urban life thanks to the new and ever-growing web of connected technology: The Internet of Things (IoT).
Last year, Los Angeles became the first city in the world to synchronize its traffic lights — all 4,500 of them — reducing traffic time on major LA corridors by about 12 percent, according to the city’s Department of Transportation. In Singapore, city authorities are testing smart systems for managing parking and waste disposal to adjust to daily and weekly patterns. In New York City, mobile air pollution monitors help city leaders pinpoint those neighborhoods most affected by smog and pollutants, so residents can modify their commuting paths and preferred modes of transportation to avoid exposure to higher levels of pollution.
And cities across the U.S. — including Chicago, Seattle and Washington, D.C. — are hiring chief technology officers to oversee broad implementation of digital systems and technologies. As more and more city functions evolve from analog to digital, it makes sense for municipalities to put the improvement, functionality and security of those systems into one department. These city CTOs will quickly become indispensable cabinet positions….”

Can Business And Tech Transform The Way Our Government Works By 2020?

Curated on Posted on by Stefaan Verhulst

Ben Schiller at Co.Exist: “The rise of open data, crowd-sourcing, predictive analytics, and other big tech trends, aren’t just for companies to contend with. They’re also a challenge for government. New technology gives public agencies the opportunity to develop and deliver services in new ways, track results more accurately, and open up decision-making.
Deloitte’s big new Government 2020 report looks at the trends impacting government and lays out a bunch of ideas for how they can innovate. We picked out a few below. There are more infographics in the slide show.

Consumerization of public services

Deloitte expects entrepreneurs to “develop innovative and radically user-friendly approaches to satisfy unmet consumer demand for better public services.” Startups like Uber or Lyft “reinvigorated transportation.” Now it expects a similar “focus on seamless customer experiences” in education and health care.

Open workforce

Deloitte expects governments to become looser: collections of people doing a job, rather than large hierarchical structures. “Governments [will] expand their talent networks to include ‘partnership talent’ (employees who are parts of joint ventures), ‘borrowed talent’ (employees of contractors), ‘freelance talent’ (independent, individual contractors) and ‘open-source talent,'” the report says.

Outcome based legislation

Just as big data analytics allows companies to measure the effectiveness of marketing campaigns, so it allows governments to measure how well legislation and regulation is working. They can “shift from a concentration on processes to the achievement of specific targets.” And, if the law isn’t working, someone has the data to throw it out….”

Data is Law

Curated on Posted on by Stefaan Verhulst

Mark Headd at Civic Innovations: The Future is Open: “In his famous essay on the importance of the technological underpinnings of the Internet, Lawrence Lessig described the potential threat if the architecture of cyberspace was built on values that diverged from those we believe are important to the proper functioning of our democracy. The central point of this seminal work seems to grow in importance each day as technology and the Internet become more deeply embedded into our daily lives.
But increasingly, another kind of architecture is becoming central to the way we live and interact with each other – and to the way in which we are governed and how we interact with those that govern us. This architecture is used by governments at the federal, state and local level to share data with the public.
This data – everything from weather data, economic data, education data, crime data, environmental data – is becoming increasingly important for how we view the world around us and our perception of how we are governed. It is quite easy for us to catalog the wide range of personal decisions – some rote, everyday decisions like what to wear based on the weather forecast, and some much more substantial like where to live or where to send our children to school – that are influenced by data collected, maintained or curated by government.
It seems to me that Lessig’s observations from a decade and a half ago about the way in which the underlying architecture of the Internet may affect our democracy can now be applied to data. Ours is the age of data – it pervades every aspect of our lives and influences how we raise our children, how we spend our time and money and who we elect to public office.
But even more fundamental to our democracy, how well our government leaders are performing the job we empower them to do depends on data. How effective is policing in reducing the number of violent crimes? How effective are environmental regulations in reducing dangerous emissions? How well are programs performing to lift people out of poverty and place them in gainful employment? How well are schools educating our children?
These are all questions that we answer – in whole or in part – by looking at data. Data that governments themselves are largely responsible for compiling and publishing….
Having access to open data is no longer an option for participating effectively in our modern democracy, it’s a requirement. Data – to borrow Lessig’s argument – has become law.”