The Economist: “PredPol is one of a range of tools using better data, more finely crunched, to predict crime. They seem to promise better law-enforcement. But they also bring worries about privacy, and of justice systems run by machines not people.
Criminal offences, like infectious disease, form patterns in time and space. A burglary in a placid neighbourhood represents a heightened risk to surrounding properties; the threat shrinks swiftly if no further offences take place. These patterns have spawned a handful of predictive products which seem to offer real insight. During a four-month trial in Kent, 8.5% of all street crime occurred within PredPol’s pink boxes, with plenty more next door to them; predictions from police analysts scored only 5%. An earlier trial in Los Angeles saw the machine score 6% compared with human analysts’ 3%.
Intelligent policing can convert these modest gains into significant reductions in crime…
Predicting and forestalling crime does not solve its root causes. Positioning police in hotspots discourages opportunistic wrongdoing, but may encourage other criminals to move to less likely areas. And while data-crunching may make it easier to identify high-risk offenders—about half of American states use some form of statistical analysis to decide when to parole prisoners—there is little that it can do to change their motivation.
Misuse and overuse of data can amplify biases…But mathematical models might make policing more equitable by curbing prejudice.”
9 models to scale open data – past, present and future
Open Knowledge Foundation Blog: “The possibilities of open data have been enthralling us for 10 years…But that excitement isn’t what matters in the end. What matters is scale – which organisational structures will make this movement explode? This post quickly and provocatively goes through some that haven’t worked (yet!) and some that have.
Ones that are working now
1) Form a community to enter in new data. Open Street Map and MusicBrainz are two big examples. It works as the community is the originator of the data. That said, neither has dominated its industry as much as I thought they would have by now.
2) Sell tools to an upstream generator of open data. This is what CKAN does for central Governments (and the new ScraperWiki CKAN tool helps with). It’s what mySociety does, when selling FixMyStreet installs to local councils, thereby publishing their potholes as RSS feeds.
3) Use open data (quietly). Every organisation does this and never talks about it. It’s key to quite old data resellers like Bloomberg. It is what most of ScraperWiki’s professional services customers ask us to do. The value to society is enormous and invisible. The big flaw is that it doesn’t help scale supply of open data.
4) Sell tools to downstream users. This isn’t necessarily open data specific – existing software like spreadsheets and Business Intelligence can be used with open or closed data. Lots of open data is on the web, so tools like the new ScraperWiki which work well with web data are particularly suited to it.
Ones that haven’t worked
5) Collaborative curation ScraperWiki started as an audacious attempt to create an open data curation community, based on editing scraping code in a wiki. In its original form (now called ScraperWiki Classic) this didn’t scale. …With a few exceptions, notably OpenCorporates, there aren’t yet open data curation projects.
6) General purpose data marketplaces, particularly ones that are mainly reusing open data, haven’t taken off. They might do one day, however I think they need well-adopted higher level standards for data formatting and syncing first (perhaps something like dat, perhaps something based on CSV files).
Ones I expect more of in the future
These are quite exciting models which I expect to see a lot more of.
7) Give labour/money to upstream to help them create better data. This is quite new. The only, and most excellent, example of it is the UK’s National Archive curating the Statute Law Database. They do the work with the help of staff seconded from commercial legal publishers and other parts of Government.
It’s clever because it generates money for upstream, which people trust the most, and which has the most ability to improve data quality.
8) Viral open data licensing. MySQL made lots of money this way, offering proprietary dual licenses of GPLd software to embedded systems makers. In data this could use OKFN’s Open Database License, and organisations would pay when they wanted to mix the open data with their own closed data. I don’t know anyone actively using it, although Chris Taggart from OpenCorporates mentioned this model to me years ago.
9) Corporations release data for strategic advantage. Companies are starting to release their own data for strategic gain. This is very new. Expect more of it.”
Ones that are working now
1) Form a community to enter in new data. Open Street Map and MusicBrainz are two big examples. It works as the community is the originator of the data. That said, neither has dominated its industry as much as I thought they would have by now.
2) Sell tools to an upstream generator of open data. This is what CKAN does for central Governments (and the new ScraperWiki CKAN tool helps with). It’s what mySociety does, when selling FixMyStreet installs to local councils, thereby publishing their potholes as RSS feeds.
3) Use open data (quietly). Every organisation does this and never talks about it. It’s key to quite old data resellers like Bloomberg. It is what most of ScraperWiki’s professional services customers ask us to do. The value to society is enormous and invisible. The big flaw is that it doesn’t help scale supply of open data.
4) Sell tools to downstream users. This isn’t necessarily open data specific – existing software like spreadsheets and Business Intelligence can be used with open or closed data. Lots of open data is on the web, so tools like the new ScraperWiki which work well with web data are particularly suited to it.
Ones that haven’t worked
5) Collaborative curation ScraperWiki started as an audacious attempt to create an open data curation community, based on editing scraping code in a wiki. In its original form (now called ScraperWiki Classic) this didn’t scale. …With a few exceptions, notably OpenCorporates, there aren’t yet open data curation projects.
6) General purpose data marketplaces, particularly ones that are mainly reusing open data, haven’t taken off. They might do one day, however I think they need well-adopted higher level standards for data formatting and syncing first (perhaps something like dat, perhaps something based on CSV files).
Ones I expect more of in the future
These are quite exciting models which I expect to see a lot more of.
7) Give labour/money to upstream to help them create better data. This is quite new. The only, and most excellent, example of it is the UK’s National Archive curating the Statute Law Database. They do the work with the help of staff seconded from commercial legal publishers and other parts of Government.
It’s clever because it generates money for upstream, which people trust the most, and which has the most ability to improve data quality.
8) Viral open data licensing. MySQL made lots of money this way, offering proprietary dual licenses of GPLd software to embedded systems makers. In data this could use OKFN’s Open Database License, and organisations would pay when they wanted to mix the open data with their own closed data. I don’t know anyone actively using it, although Chris Taggart from OpenCorporates mentioned this model to me years ago.
9) Corporations release data for strategic advantage. Companies are starting to release their own data for strategic gain. This is very new. Expect more of it.”
Let’s Shake Up the Social Sciences
Nicholas Christakis in The New York Times:”TWENTY-FIVE years ago, when I was a graduate student, there were departments of natural science that no longer exist today. Departments of anatomy, histology, biochemistry and physiology have disappeared, replaced by innovative departments of stem-cell biology, systems biology, neurobiology and molecular biophysics. Taking a page from Darwin, the natural sciences are evolving with the times. The perfection of cloning techniques gave rise to stem-cell biology; advances in computer science contributed to systems biology. Whole new fields of inquiry, as well as university departments and majors, owe their existence to fresh discoveries and novel tools.
In contrast, the social sciences have stagnated. They offer essentially the same set of academic departments and disciplines that they have for nearly 100 years: sociology, economics, anthropology, psychology and political science. This is not only boring but also counterproductive, constraining engagement with the scientific cutting edge and stifling the creation of new and useful knowledge. Such inertia reflects an unnecessary insecurity and conservatism, and helps explain why the social sciences don’t enjoy the same prestige as the natural sciences.
One reason citizens, politicians and university donors sometimes lack confidence in the social sciences is that social scientists too often miss the chance to declare victory and move on to new frontiers. Like natural scientists, they should be able to say, “We have figured this topic out to a reasonable degree of certainty, and we are now moving our attention to more exciting areas.” But they do not.”
Digital Public Spaces
FutureEverything Publications: “This publication gathers a range of short explorations of the idea of the Digital Public Space. The central vision of the Digital Public Space is to give everyone everywhere unrestricted access to an open resource of culture and knowledge. This vision has emerged from ideas around building platforms for engagement around cultural archives to become something wider, which this publication is seeking to hone and explore.
This is the first publication to look at the emergence of the Digital Public Space. Contributors include some of the people who are working to make the Digital Public Space happen.
The Digital Public Spaces publication has been developed by FutureEverything working with Bill Thompson of the BBC and in association with The Creative Exchange.”
The Little Data Book on Information and Communication Technology 2013
The World Bank: “This new addition to the Little Data Book series presents at-a-glance tables for more than 200 economies showing the most recent national data on key indicators of information and communications technology (ICT), including access, quality, affordability, efficiency, sustainability and applications.”
Open Government is About Raising People’s Opinions
Lucas Dailey, Chief Innovation Officer at political social network MyMaryland.net, in Sunlight Foundation’s OpenGov Voices: “The mechanism for citizen interaction with government doesn’t start and end at the ballot box. An essential goal of our fight for greater government openness and transparency is to give citizens’ opinions greater power. For government to be responsive it must have a fast, easy means to understand how constituents feel about any given issues. Ultimate
ly, government itself is a relationship between the institutions that constitute a polity and its citizens.
MyMaryland.net wants to bridge the gap between voters and their representatives because we believe people’s voices matter. MyMaryland.net connects verified Maryland voters with their elected officials in democracy’s first 24/7 online Town Hall.
Participation: a two-sided problem
One of the keys to a vibrant representative democracy is an informed and engaged citizenry. Yet only 10% of Americans contact their elected officials between elections. We can do better by lowering the hurdles to participate and raising the political value of opinions.
…Open Government isn’t just about transparency, it’s also about the ability to take action based on what that transparency allows us to learn. The Open Government movement has helped us learn what government does and how it does it. Now it’s your move.”
Transforming Our Conversation of Information Architecture with Structure
Nathaniel Davis: Information architecture has been characterized as both an art and a science. Because there’s more evidence of the former than the latter, the academic and research community is justified in hesitating to give the practice of information architecture more attention.
If you probe the history of information architecture for the web, its foundation appears to be rooted in library science. But you’ll also find a pattern of borrowing methods and models from many other disciplines like architecture and urban planning, linguistics and ethnography, cognition and psychology, to name a few. This history leads many to wonder if the practice of information architecture is anything other than an art of induction for solving problems of architecture and design for the web…
Certainly, there is one concept that has persisted under the radar for many years with limited exploration. It is littered throughout countless articles, books and papers and is present in the most cited IA practice definitions. It may be the single concept that truly bridges practitioner and academic interests around a central and worthwhile topic. That concept is structure.”
Accountability.Org: Online Disclosure by Nonprofits
Paper by Joannie Tremblay-Boire and Aseem Prakash: “Why do some nonprofits signal their accountability via unilateral website disclosures? We develop an Accountability Index to examine the websites of 200 U.S. nonprofits ranked by the Chronicle of Philanthropy. We expect nonprofits’ incentives for website disclosures will be shaped by their organizational and sectoral characteristics. Our analysis suggests that nonprofits appearing frequently in the media disclose more accountability information while nonprofits larger in size disclose less. Religion-related nonprofits tend to disclose less information, suggesting that religious bonding enhances trust and reduce incentives for self-disclosure. Health nonprofits disclose less information, arguably because government-mandated disclosures reduce marginal benefits from voluntary disclosures. Education nonprofits, on the other hand, tend to disclose more accountability information perhaps because they supply credence goods. This research contributes to the emerging literature on websites as accountability mechanisms by developing a new index for scholars to use and proposing new hypotheses based on the corporate social responsibility literature.”
Understanding Smart Data Disclosure Policy Success: The Case of Green Button
New Paper by Djoko Sigit Sayogo and Theresa Pardo: “Open data policies are expected to promote innovations that stimulate social, political and economic change. In pursuit of innovation potential, open datahas expanded to wider environment involving government, business and citizens. The US government recently launched such collaboration through a smart data policy supporting energy efficiency called Green Button. This paper explores the implementation of Green Button and identifies motivations and success factors facilitating successful collaboration between public and private organizations to support smart disclosure policy. Analyzing qualitative data from semi-structured interviews with experts involved in Green Button initiation and implementation, this paper presents some key findings. The success of Green Button can be attributed to the interaction between internal and external factors. The external factors consist of both market and non-market drivers: economic factors, technology related factors, regulatory contexts and policy incentives, and some factors that stimulate imitative behavior among the adopters. The external factors create the necessary institutional environment for the Green Button implementation. On the other hand, the acceptance and adoption of Green Button itself is influenced by the fit of Green Button capability to the strategic mission of energy and utility companies in providing energy efficiency programs. We also identify the different roles of government during the different stages of Green Button implementation.”
[Recipient of Best Management/Policy Paper Award, dgo2013]
What Happens When Everyone Makes Maps?
Laura Mallonee in the Atlantic: “On a spring Sunday in a Soho penthouse, ten people have gathered for a digital mapping “Edit-A-Thon.” Potted plants grow to the ceiling and soft cork carpets the floor. At a long wooden table, an energetic woman named Liz Barry is showing me how to map my neighborhood. “This is what you’ll see when you look at OpenStreetMap,” she says.
Though visually similar to Google’s, the map on the screen gives users unfettered access to its underlying data — anyone can edit it. Barry lives in Williamsburg, and she’s added many of the neighborhood’s boutiques and restaurants herself. “Sometimes when I’m tired at the end of the day and can’t work anymore, I just edit OpenStreetMap,” she says. “Kind of a weird habit.” Barry then shows me the map’s “guts.” I naively assume it will be something technical and daunting, but it’s just an editable version of the same map, with tools that let you draw roads, identify landmarks, and even label your own house.”