Springwise: “The power of the visual sharing that makes platforms such as Instagram so popular has been harnessed by retailers like Ask CT Food to share knowledge about cooking, but could the same be done for the medical world? Figure1 enables health professionals to upload and share photos of conditions, creating online discussion as well as crowdsourcing a database of reference images.
Developed by healthcare tech startup Movable Science, the platform is designed in a similar vein to Instagram and enables medical professionals to create their own feed of images from the cases they deal with. In order to protect patients’ identities, the app uses facial recognition to block out faces, while users can add their own marks to cover up other indentifiable marks. They can also add pointers and annotations, as well as choosing who sees it, before uploading the image. Photos can be tagged with relevant terms to allow the community to easily find them through search and others can comment on the images, fostering discussion among users. Images can also be starred, which acts simultaneously as an indication of quality as well as enabling users to save useful images for later reference. …
Although Instagram was developed with the broad purpose of entertainment and social sharing, Figure1 has tweaked the platform’s functions to provide a tool that could help doctors and students share their knowledge and learn from others in an engaging way…”
Metadata Liberation Movement
Holman Jenkins in the Wall Street Journal: “The biggest problem, then, with metadata surveillance may simply be that the wrong agencies are in charge of it. One particular reason why this matters is that the potential of metadata surveillance might actually be quite large but is being squandered by secret agencies whose narrow interest is only looking for terrorists….
“Big data” is only as good as the algorithms used to find out things worth finding out. The efficacy and refinement of big-data techniques are advanced by repetition, by giving more chances to find something worth knowing. Bringing metadata out of its black box wouldn’t only be a way to improve public trust in what government is doing. It would be a way to get more real value for society out of techniques that are being squandered on a fairly minor threat.
Bringing metadata out of the black box would open up new worlds of possibility—from anticipating traffic jams to locating missing persons after a disaster. It would also create an opportunity to make big data more consistent with the constitutional prohibition of unwarranted search and seizure. In the first instance, with the computer withholding identifying details of the individuals involved, any red flag could be examined by a law-enforcement officer to see, based on accumulated experience, whether the indication is of interest.
If so, a warrant could be obtained to expose the identities involved. If not, the record could immediately be expunged. All this could take place in a reasonably aboveboard, legal fashion, open to inspection in court when and if charges are brought or—this would be a good idea—a court is informed of investigations that led to no action.
Our guess is that big data techniques would pop up way too many false positives at first, and only considerable learning and practice would allow such techniques to become a useful tool. At the same time, bringing metadata surveillance out of the shadows would help the Googles, Verizons and Facebooks defend themselves from a wholly unwarranted suspicion that user privacy is somehow better protected by French or British or (heavens) Chinese companies from their own governments than U.S. data is from the U.S. government.
Most of all, it would allow these techniques to be put to work on solving problems that are actual problems for most Americans, which terrorism isn’t.”
Eduardo Paes on Open Government
Eduardo Paes, Mayor, Rio de Janeiro, Brazil in the Huffington Post: “The Internet revolution has transformed the way knowledge is disseminated and how people unite over causes. Social networks are playing a key role in this movement, just as books and the press have done over the last six centuries. During the recent demonstrations in Brazil, approximately 62 percent of the people were informed of the event via Facebook, a much higher rate than TV, which was first source of information to 14 percent of attendees, according to Ibope Institute. Three out of four agitators used social networks to round up support. As generations succeed and the digital gap narrows, these statistics could possibly rise.
This revolution is also accentuating the imperfections of the representative democracy, the only plausible alternative, as Churchill famously said. We live in an era of “Liquid Modernity” as defined by sociologist Zygmunt Bauman, which describes the ephemeral nature of contemporary social interactions. Bauman says that these days society, in a similar manner to liquid, adopts various unstable forms under small amounts of pressure. They are incapable of stabilizing in a consistent form, which results in consequences to social relationships and politics. Meanwhile, political parties, bureaucracy and institutions seem to remain firmly in the 17th Century.
Democracy has to reinvent itself in accordance with this new “liquid society” where collaboration happens between many millions of people directly. Leadership is not vertical, as in the past, but horizontal. Nowadays some say following is more important than leading. Cyber culture understands open code as a principle, something the music industry has reluctantly had to learn. There is no time and space limitation for public accountability on the Internet. Creative commonality is standard and does not resemble the authoritarian style of the dead communist experience. It seems that it is no longer society’s obligation to understand legislation, it is a duty for governments to be understood by their people.”
Facebook Is Being Redefined by Its Developing World Users
Tom Simonite in MIT Technology Review: “…as Facebook’s user base continues to expand, a growing proportion of its users think of it quite differently, as a luxury brand, badge of status, and or even a place to make a little extra money. That’s due to the rapid growth in the number of Facebook users signing on from developing countries, a trend underscored by news from the company today that more than 100 million people use a mobile app the company makes for feature phones…
Little research has been done on Facebook’s growth in developing countries (and a lot would be needed to capture even some of the diversity included under the blanket term “developing world”). Two small, recent studies of Kenyan Facebook users in poor areas by Susan Wyche of Michigan State University are among the first to be published, and they provide some interesting insights.
One of Wyche’s ethnographic studies took place in rural Internet cafes, where the researchers were told that “Facebook is a luxury,” only to be indulged if someone had money to spare (here’s a PDF of Wyche’s paper). When study participants thought about social networking, the challenges of low bandwidth and sometimes unreliable electricity supplies were foremost in their minds.
The barriers of cost and infrastructure associated with Facebook led people in another community Wyche and colleagues visited, a slum of Nairobi, to see the service as for more than just socializing. They used it—with mixed success—as a way to make a little money, look for jobs, market themselves, and seek remittances from friends and family overseas. (This reminded me of a recent report on people in Kuwait using Instagram to sell things and run retail businesses.)…
Should it want to, Facebook could even become a powerful tool for efforts to improve the lives of people in poor areas, where the site is gaining traction. The company has already dabbled with using social engineering to boost organ donations in the U.S. (see “Thank God for Facebook: When Platforms Proselytize”). There’s no shortage of similar experiments that could be run in places with more fundamental health problems, where Facebook’s status as a luxury could make it very influential.”
Predictive Policing: Don’t even think about it
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.”
Index: Participation and Civic Engagement
The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on participation and civic engagement and was originally published in 2013.
- Percent turnout of voting age population in 2012 U.S. Presidential election: 57.5
- Percent turnout in 2008, 2004, 2000 elections: 62.3, 60.4, 54.2
- Change in voting rate in U.S. from 1980 to most recent election: –29
- Change in voting rate in Slovak Republic from 1980 to most recent election: –42, the lowest rate among democratic countries surveyed
- Change in voting rate in Russian Federation from 1980 to most recent election: +14, the highest rate among democratic countries surveyed
- Percent turnout in Australia as of 2011: 95, the highest rate among democratic countries surveyed
- Percentage point difference in voting rates between high and low educated people in Australia as of 2011: 1
- Percentage point difference in voting rates between high and low educated people in the U.S. as of 2011: 33
- Number of Black and Hispanic U.S. voters in comparison to 2008 election: 1.7 million and 1.4 million increase
- Number of non-Hispanic White U.S. voters in comparison to 2008 election: 2 million decrease, the only example of a race group showing a decrease in net voting from one presidential election to the next
- Percent of Americans that contact their elected officials between elections: 10
- Margin of victory in May 2013 Los Angeles mayoral election: 54-46
- Percent turnout among Los Angeles citizens in May 2013 Los Angeles mayoral election: 19
- Percent of U.S. adults that used social networking sites in 2012: 60
- How many of which participated in a political or civic activity online: 2/3
- Percent of U.S. social media users in 2012 that used social tools to encourage other people to take action on an issue that is important to them: 31
- Percent of U.S. adults that belonged to a group on a social networking site involved in advancing a political or social issue in 2012: 12
- Increase in the number of adults who took part in these behaviors in 2008: four-fold
- Number of U.S. adults that signed up to receive alerts about local issues via email or text messaging in 2010: 1 in 5
- Percent of U.S. adults that used digital tools digital tools to talk to their neighbors and keep informed about community issues in 2010: 20
- Number of Americans that talked face-to-face with neighbors about community issues in 2010: almost half
- How many online adults that have used social tools as blogs, social networking sites, and online video as well as email and text alerts to keep informed about government activities: 1/3
- Percent of U.S. adult internet users that have gone online for raw data about government spending and activities in 2010: 40
- Of which how many look online to see how federal stimulus money is being spent: 1 in 5
- Read or download the text of legislation: 22%
- How many Americans volunteered through or for an organization at least once between September 2011 and September 2012: 64.5 million
- Median hours spent on volunteer activities during this time: 50
- Change in volunteer rate compared to the year before: 0.3 decline
Sources
- Dailey, Lucas, “OpenGov Voices: Open Government is About Raising People’s Opinions.” Sunlight Foundation. July 12, 2013.
- File, Thom, “The Diversifying Electorate—Voting Rates by Race and Hispanic Origin in 2012.” May 2013.
- Smith, Aaron, “Civic Engagement in the Digital Age.” Pew Internet & American Life Project. April 25, 2013.
- “Volunteering in the United States, 2012.” Bureau of Labor Statistics. February 22, 2013.
- Rainie, Lee, “Social Media and Voting.” Pew Internet & American Life Project. November 6, 2012.
- Rainie Lee, and Aaron Smith, Kay Lehman Schlozman, Henry Brady, Sidney Verba, “Social Media and Political Engaegment.” Pew Internet & American Life Project. October 19, 2012.
- “Society at a Glance 2011: OECD Social Indicators.” OECD iLibrary. Accessed on July 22, 2013.
- Smith, Aaron, “Neighbors Online.” Pew Internet & American Life Project. June 9, 2010.
- Smith, Aaron, “Government Online.” Pew Internet & American Life Project. April 27, 2010.
- “2012 Voter Turnout.” Bipartisan Policy Center. November 8, 2012.
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.”
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.”
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]