Victoria Lemieux at the WEF Blog: “An unprecedented number of individuals and organizations are finding ways to explore, interpret and use Open Data. Public agencies are hosting Open Data events such as meetups, hackathons and data dives. The potential of these initiatives is great, including support for economic development (McKinsey, 2013), anti-corruption (European Public Sector Information Platform, 2014) and accountability (Open Government Partnership, 2012). But is Open Data’s full potential being realized?
A news item from Computer Weekly casts doubt. A recent report notes that, in the United Kingdom, poor data quality is hindering the government’s Open Data program. The report goes on to explain that – in an effort to make the public sector more transparent and accountable – UK public bodies have been publishing spending records every month since November 2010. The authors of the report, who conducted an analysis of 50 spending-related data releases by the Cabinet Office since May 2010, found that that the data was of such poor quality that using it would require advanced computer skills.
Far from being a one-off problem, research suggests that this issue is ubiquitous and endemic. Some estimates indicate that as much as 80 percent of the time and cost of an analytics project is attributable to the need to clean up “dirty data” (Dasu and Johnson, 2003).
In addition to data quality issues, data provenance can be difficult to determine. Knowing where data originates and by what means it has been disclosed is key to being able to trust data. If end users do not trust data, they are unlikely to believe they can rely upon the information for accountability purposes. Establishing data provenance does not “spring full blown from the head of Zeus.” It entails a good deal of effort undertaking such activities as enriching data with metadata – data about data – such as the date of creation, the creator of the data, who has had access to the data over time and ensuring that both data and metadata remain unalterable.
Similarly, if people think that data could be tampered with, they are unlikely to place trust in it; full comprehension of data relies on the ability to trace its origins….”
Open Source Governance—A More Ambitious Cousin of Collaborative Governance
New paper by Ani Matei & Sergiu Ioan Irimia in the International Journal of Public Administration: “Open source represents a model generally known for its success in software production. The objective of this article is to establish a new strategic approach of using open source development principles for managing collaborative arrangements between citizens and public administration. The identity of open source governance is developed by highlighting how it is different from its main “competitor”—collaborative governance, and from other two popular concepts—open government and e-democracy. The other sections are designed to answer to public managers regarding why and what to adopt from this governance model for public sector services.”
Francis Fukuyama’s ‘Political Order and Political Decay’
Book Review by David Runciman of “Political Order and Political Decay: From the Industrial Revolution to the Globalisation of Democracy”, by Francis Fukuyama in the Financial TImes: “It is not often that a 600-page work of political science ends with a cliffhanger. But the first volume of Francis Fukuyama’s epic two-part account of what makes political societies work, published three years ago, left the big question unanswered. That book took the story of political order from prehistoric times to the dawn of modern democracy in the aftermath of the French Revolution. Fukuyama is still best known as the man who announced in 1989 that the birth of liberal democracy represented the end of history: there were simply no better ideas available. But here he hinted that liberal democracies were not immune to the pattern of stagnation and decay that afflicted all other political societies. They too might need to be replaced by something better. So which was it: are our current political arrangements part of the solution, or part of the problem?
Political Order and Political Decay is his answer. He squares the circle by insisting that democratic institutions are only ever one component of political stability. In the wrong circumstances they can be a destabilising force as well. His core argument is that three building blocks are required for a well-ordered society: you need a strong state, the rule of law and democratic accountability. And you need them all together. The arrival of democracy at the end of the 18th century opened up that possibility but by no means guaranteed it. The mere fact of modernity does not solve anything in the domain of politics (which is why Fukuyama is disdainful of the easy mantra that failing states just need to “modernise”).
The explosive growth in industrial capacity and wealth that the world has experienced in the past 200 years has vastly expanded the range of political possibilities available, for better and for worse (just look at the terrifying gap between the world’s best functioning societies – such as Denmark – and the worst – such as the Democratic Republic of Congo). There are now multiple different ways state capacity, legal systems and forms of government can interact with each other, and in an age of globalisation multiple different ways states can interact with each other as well. Modernity has speeded up the process of political development and it has complicated it. It has just not made it any easier. What matters most of all is getting the sequence right. Democracy doesn’t come first. A strong state does. …”
Forget GMOs. The Future of Food Is Data—Mountains of It
Cade Metz at Wired: “… Led by Dan Zigmond—who previously served as chief data scientist for YouTube, then Google Maps—this ambitious project aims to accelerate the work of all the biochemists, food scientists, and chefs on the first floor, providing a computer-generated shortcut to what Hampton Creek sees as the future of food. “We’re looking at the whole process,” Zigmond says of his data team, “trying to figure out what it all means and make better predictions about what is going to happen next.”
The project highlights a movement, spreading through many industries, that seeks to supercharge research and development using the kind of data analysis and manipulation pioneered in the world of computer science, particularly at places like Google and Facebook. Several projects already are using such techniques to feed the development of new industrial materials and medicines. Others hope the latest data analytics and machine learning techniques can help diagnosis disease. “This kind of approach is going to allow a whole new type of scientific experimentation,” says Jeremy Howard, who as the president of Kaggle once oversaw the leading online community of data scientists and is now applying tricks of the data trade to healthcare as the founder of Enlitic.
Zigmond’s project is the first major effort to apply “big data” to the development of food, and though it’s only just getting started—with some experts questioning how effective it will be—it could spur additional research in the field. The company may license its database to others, and Hampton Creek founder and CEO Josh Tetrick says it may even open source the data, so to speak, freely sharing it with everyone. “We’ll see,” says Tetrick, a former college football linebacker who founded Hampton Creek after working on economic and social campaigns in Liberia and Kenya. “That would be in line with who we are as a company.”…
Initially, Zigmond and his team will model protein interactions on individual machines, using tools like the R programming language (a common means of crunching data) and machine learning algorithms much like those that recommend products on Amazon.com. As the database expands, they plan to arrange for much larger and more complex models that run across enormous clusters of computer servers, using the sort of sweeping data-analysis software systems employed by the likes of Google. “Even as we start to get into the tens and hundreds of thousands and millions of proteins,” Zigmond says, “it starts to be more than you can handle with traditional database techniques.”
In particular, Zigmond is exploring the use of deep learning, a form of artificial intelligence that goes beyond ordinary machine learning. Google is using deep learning to drive the speech recognition system in Android phones. Microsoft is using it to translate Skype calls from one language to another. Zigmond believes it can help model the creation of new foods….”
Zigmond’s project is the first major effort to apply “big data” to the development of food, and though it’s only just getting started—with some experts questioning how effective it will be—it could spur additional research in the field. The company may license its database to others, and Hampton Creek founder and CEO Josh Tetrick says it may even open source the data, so to speak, freely sharing it with everyone. “We’ll see,” says Tetrick, a former college football linebacker who founded Hampton Creek after working on economic and social campaigns in Liberia and Kenya. “That would be in line with who we are as a company.”…
Initially, Zigmond and his team will model protein interactions on individual machines, using tools like the R programming language (a common means of crunching data) and machine learning algorithms much like those that recommend products on Amazon.com. As the database expands, they plan to arrange for much larger and more complex models that run across enormous clusters of computer servers, using the sort of sweeping data-analysis software systems employed by the likes of Google. “Even as we start to get into the tens and hundreds of thousands and millions of proteins,” Zigmond says, “it starts to be more than you can handle with traditional database techniques.”
In particular, Zigmond is exploring the use of deep learning, a form of artificial intelligence that goes beyond ordinary machine learning. Google is using deep learning to drive the speech recognition system in Android phones. Microsoft is using it to translate Skype calls from one language to another. Zigmond believes it can help model the creation of new foods….”
Citizen Science: The Law and Ethics of Public Access to Medical Big Data
New Paper by Sharona Hoffman: “Patient-related medical information is becoming increasingly available on the Internet, spurred by government open data policies and private sector data sharing initiatives. Websites such as HealthData.gov, GenBank, and PatientsLikeMe allow members of the public to access a wealth of health information. As the medical information terrain quickly changes, the legal system must not lag behind. This Article provides a base on which to build a coherent data policy. It canvasses emergent data troves and wrestles with their legal and ethical ramifications.
Publicly accessible medical data have the potential to yield numerous benefits, including scientific discoveries, cost savings, the development of patient support tools, healthcare quality improvement, greater government transparency, public education, and positive changes in healthcare policy. At the same time, the availability of electronic personal health information that can be mined by any Internet user raises concerns related to privacy, discrimination, erroneous research findings, and litigation. This Article analyzes the benefits and risks of health data sharing and proposes balanced legislative, regulatory, and policy modifications to guide data disclosure and use.”
5 great apps backed with open data
Jeanne Holm at OpenSource.com: “Data.gov has taken open source to heart. Beyond just providing open data and open source code, the entire process involves open civic engagement. All team ideas, public interactions, and new ideas (from any interaction) are cross-posted and entered in Github. These are tracked openly and completed to milestones for full transparency. We also recently redesigned the website at Data.gov through usability testing and open engagement on Github.
Today, I want to share with you just five of the hundreds of applications that have been developed by the public using open government data. These are examples of the kind of apps, visualizations, and analyses that are created from working with developers, educators, and businesses on a specific challenge at events that pull the community together, like data jams, meetups, and conferences.
Archimedes
Archimedes makes tools that give quantitative models to doctors and patients so that they can find effective interventions, predict how interventions will affect an individual’s health risk, and help decision-makers analyze health outcomes….
Trulia
Trulia provides insights into neighborhoods where you might be interested in moving. Looking at the homes and apartments for sale and rent, trends and prices in real estate, and neighborhood characteristics, Trulia gives you the data to make decisions about buying, selling, renting, and moving….
HelloWallet
HelloWallet helps people to manage their money, and to learn about and start making investments. Some of the subjects for individuals include retirement readiness, debt levels, emergency savings, and health savings….
SaferCar
Consumers looking for a new car, can find a safer car by using the SaferCar app from the Department of Transportation. Powered by data on five-star safety ratings from the National Highway Traffic Safety Administration, consumers can look at new and used car ratings, recalls and complaints, and information about installing child seats….
Red Cross Hurricane
The Safety.Data.gov community of Data.gov held a Safety Datapalooza and brought together developers, businesses, NGOs, and government participants to brainstorm ways to put government data to use to improve the lives of citizens in America. A 90-day challenge was issued to create some of these apps and concepts, and one was with the Red Cross to create an app that would help people find safe ways to move around during a natural disaster. This included rail, roads, buses, and airports–which were open and what schedules they were running on. These data were provided by the Department of Transportation. As Hurricane Sandy descended on the east coast, we accelerated the development of the Red Cross Hurricane app and launched the app as the Hurricane touched ground…”
How Open Data Is Transforming City Life
Joel Gurin, The GovLab, at Techonomy: “Start a business. Manage your power use. Find cheap rents, or avoid crime-ridden neighborhoods. Cities and their citizens worldwide are discovering the power of “open data”—public data and information available from government and other sources that can help solve civic problems and create new business opportunities. By opening up data about transportation, education, health care, and more, municipal governments are helping app developers, civil society organizations, and others to find innovative ways to tackle urban problems. For any city that wants to promote entrepreneurship and economic development, open data can be a valuable new resource.
The urban open data movement has been growing for several years, with American cities including New York, San Francisco, Chicago, and Washington in the forefront. Now an increasing number of government officials, entrepreneurs, and civic hackers are recognizing the potential of open data. The results have included applications that can be used across many cities as well as those tailored to an individual city’s needs.
At first, the open data movement was driven by a commitment to transparency and accountability. City, state, and local governments have all released data about their finances and operations in the interest of good government and citizen participation. Now some tech companies are providing platforms to make this kind of city data more accessible, useful, and comparable. Companies like OpenGov and Govini make it possible for city managers and residents to examine finances, assess police department overtime, and monitor other factors that let them compare their city’s performance to neighboring municipalities.
Other new businesses are tapping city data to provide residents with useful, practical information. One of the best examples is NextBus, which uses metropolitan transportation data to tell commuters when to expect a bus along their route. Commuter apps like this have become common in cities in the U.S. and around the world. Another website, SpotCrime, collects, analyzes, and maps crime statistics to tell city dwellers which areas are safest or most dangerous and to offer crime alerts. And the Chicago-based Purple Binder helps people in need find city healthcare services. Many companies in the Open Data 500, the study of open data companies that I direct at the GovLab at NYU, use data from cities as well as other sources….
Some of the most ambitious uses of city data—with some of the greatest potential—focus on improving education. In Washington, the nonprofit Learn DC has made data about public schools available through a portal that state agencies, community organizations, and civic hackers can all use. They’re using it for collaborative research and action that, they say, has “empowered every DC parent to participate in shaping the future of the public education system.”…”
Data Mining Reveals How Social Coding Succeeds (And Fails)
Emerging Technology From the arXiv : “Collaborative software development can be hugely successful or fail spectacularly. An analysis of the metadata associated with these projects is teasing apart the difference….
The process of developing software has undergone huge transformation in the last decade or so. One of the key changes has been the evolution of social coding websites, such as GitHub and BitBucket.
These allow anyone to start a collaborative software project that other developers can contribute to on a voluntary basis. Millions of people have used these sites to build software, sometimes with extraordinary success.
Of course, some projects are more successful than others. And that raises an interesting question: what are the differences between successful and unsuccessful projects on these sites?
Today, we get an answer from Yuya Yoshikawa at the Nara Institute of Science and Technology in Japan and a couple of pals at the NTT Laboratories, also in Japan. These guys have analysed the characteristics of over 300,000 collaborative software projects on GitHub to tease apart the factors that contribute to success. Their results provide the first insights into social coding success from this kind of data mining.
A social coding project begins when a group of developers outline a project and begin work on it. These are the “internal developers” and have the power to update the software in a process known as a “commit”. The number of commits is a measure of the activity on the project.
External developers can follow the progress of the project by “starring” it, a form of bookmarking on GitHub. The number of stars is a measure of the project’s popularity. These external developers can also request changes, such as additional features and so on, in a process known as a pull request.
Yoshikawa and co begin by downloading the data associated with over 300,000 projects from the GitHub website. This includes the number of internal developers, the number of stars a project receives over time and the number of pull requests it gets.
The team then analyse the effectiveness of the project by calculating factors such as the number of commits per internal team member, the popularity of the project over time, the number of pull requests that are fulfilled and so on.
The results provide a fascinating insight into the nature of social coding. Yoshikawa and co say the number of internal developers on a project plays a significant role in its success. “Projects with larger numbers of internal members have higher activity, popularity and sociality,” they say….
Ref: arxiv.org/abs/1408.6012 : Collaboration on Social Media: Analyzing Successful Projects on Social Coding”
Beta Release of the Open Contracting Data Standard
Open Contracting: “Each year, governments around the world spend over $9 trillion dollars of citizens’ money through public contracts. All too often, however, little to no data is made available to the public about these contracts. If data is available, it is often supplied in ways which make analysis very challenging or downright impossible.
Yet, if data relating to public contracts is released in a clear, reusable and timely way, the rewards will be great. Governments will have data to make better decisions and enhance their effectiveness, private companies will be better able to compete in the market and citizens will be able to hold their governments accountable for how they spend public resources.
To help unlock these benefits, the Open Contracting Partnership (OCP) is pleased to share for broad consultation the Beta Release of the Open Contracting Data Standard (OCDS).This Standard is currently being developed for the OCP by the World Wide Web Foundation through the support of Omidyar Network and the World Bank.
The objective of the Data Standard is to support governments to publish contracting data in a more accessible, interoperable and useful manner and to enable the widest possible range of stakeholders to use contracting data effectively.
Some of the features provided by this Beta Release include a description of the overall Open Contracting Data Standard Model and a JSON Schema for open contracting releases and records that includes a set of recommended fields.
The development of the Open Contracting Data Standard is an open process and inputs and feedback are encouraged. Although this will be an ongoing process, those comments provided before September 30, 2014 will be more likely to fully inform version 1.0 of the Standard. These comments will help refine the standard, both the structure and fields, in preparation for the initial release version.
Those interested in providing comments can do so in two different ways:
- Inline comments on the document – Log in to the Open Contracting Data Standard Github site and then highlight portions of text to add comment. To “reply” to an existing comment, highlight the same portion of text, and then add your comment. See instructions at the top of the Github login page for more help on commenting.
- Mailing list – If you have more general comments that don’t fit well as inline comments, please join the OCDS mailing list and start a discussion with your thoughts….”
When Citizens Bypass Government
in Governing: “Local governments are facing new realities. Citizens’ trust in government has declined, and financial constraints do not allow local governments to deliver all of the services their communities would like. In response, citizens are changing as well. Increasingly, local residents and organizations are seizing opportunities to engage with their communities in their own ways by creating platforms that bypass government.
These platforms are powered by inexpensive technology and driven by a desire for community improvement that is bottom-up. While some local governments are embracing this development, others are reacting defensively, at least initially. As this phenomenon grows, more and more local governments will be faced with the challenge of deciding what their stances should be toward these citizen-engagement platforms.
In Alexandria, Va., a citizens’ group launched ACTion Alexandria, an online platform for residents to engage in challenges, debate solutions, share stories and develop relationships, all on their own and without the help or permission of the city government. Even though ACTion Alexandria is a platform created and owned by citizens, the city government supports it and even partners with it.
Oakland, Calif., initially took a less supportive stance to the citizen-developed Oakland Crimespotting website. Using open city law-enforcement data, Oakland Crimespotting provides residents with the most up-to-date information on crime in the city on an interactive map. A week after the site was launched, however, the city government cut off its data stream, saying Oakland Crimespotting’s frequent data demands were disrupting the city’s own crime-tracking website. Eventually, the city changed its mind and restored the data flow.
Citizen platforms are also have much to offer in times of crisis. In Allentown, Pa., in 2011, a devastating natural-gas explosion occurred in the downtown area. Five people died. During and following the disaster, Allentown residents used social-media platforms to provide updates about rescue and recovery, disseminate information about ways to help the affected families, and volunteer….”