Feedback Labs


Feedback Labs: FeedBackLabs_circleLogo_HiRes100pxIf you find yourself asking the following three questions, then you have come to the right place:

  1. “What do citizens want?”
  2. “Are they getting it?”
  3. “If not, how will things change?”

Much excellent work has been done over recent years to answer the first and second questions. Our goal is to catalyze that work and make it matter by focusing on the third question – “How will things change?”
Aid, philanthropy, and government programs are often designed, implemented and evaluated by experts.  We think that citizens should increasingly be in the driver’s seat.  Experts are still important, but in many cases their role needs to shift from being a decision-maker to being people who enrich and inform conversations among citizens.

What will Feedback Labs do?

Based on what we have heard so far, we think we can add value in three ways:

  • Frame the issues – for example, what exactly do we mean by feedback loops? What works and what doesn’t? What is the evidence for impact?
  • Help close the feedback loop – uncover approaches that are succeeding at finding out what people want and whether they are getting it, and then helping to close the loop by understanding (and in some cases funding) what it takes to translate citizen voice into real changes in programs.
  • Facilitate mainstreaming ­– i.e., assist aid, philanthropy and government organizations adopt feedback loops in their normal course of operation. We want to make feedback loops the norm rather than the exception.

Historically we have often assumed that the flow of knowledge is from the richer countries to the poorer.  But learning goes both ways, and in the case of feedback loops, some of the most innovative approaches are being pioneered in developing countries.  So we plan to support work both internationally and domestically.”

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.”

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.
williamburg_570.jpg
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.”

Crowdsourcing—Harnessing the Masses to Advance Health and Medicine


A Systematic Review of the literature in the Journal of General Internal Medicine: “Crowdsourcing research allows investigators to engage thousands of people to provide either data or data analysis. However, prior work has not documented the use of crowdsourcing in health and medical research. We sought to systematically review the literature to describe the scope of crowdsourcing in health research and to create a taxonomy to characterize past uses of this methodology for health and medical research..
Twenty-one health-related studies utilizing crowdsourcing met eligibility criteria. Four distinct types of crowdsourcing tasks were identified: problem solving, data processing, surveillance/monitoring, and surveying. …
Utilizing crowdsourcing can improve the quality, cost, and speed of a research project while engaging large segments of the public and creating novel science. Standardized guidelines are needed on crowdsourcing metrics that should be collected and reported to provide clarity and comparability in methods.”

Why We Collaborate


NPR and TED Radio Hour:
 The Internet as a tool allows for really brilliant people to do things that they weren’t really able to do in the past. — Jimmy Wales
“The world has over a trillion hours a year of free time to commit to shared projects,” says professor Clay Shirky. But what motivates dozens, thousands, even millions of people to come together on the Internet and commit their time to a project for free? What is the key to making a successful collaboration work? In this hour, TED speakers unravel ideas behind the mystery of mass collaborations that build a better world.

The Science of Familiar Strangers: Society’s Hidden Social Network


The Physics arXiv Blog “We’ve all experienced the sense of being familiar with somebody without knowing their name or even having spoken to them. These so-called “familiar strangers” are the people we see every day on the bus on the way to work, in the sandwich shop at lunchtime, or in the local restaurant or supermarket in the evening.
These people are the bedrock of society and a rich source of social potential as neighbours, friends, or even lovers.
But while many researchers have studied the network of intentional links between individuals—using mobile-phone records, for example—little work has been on these unintentional links, which form a kind of hidden social network.
Today, that changes thanks to the work of Lijun Sun at the Future Cities Laboratory in Singapore and a few pals who have analysed the passive interactions between 3 million residents on Singapore’s bus network (about 55 per cent of the city’s population).  ”This is the first time that such a large network of encounters has been identied and analyzed,” they say.
The results are a fascinating insight into this hidden network of familiar strangers and the effects it has on people….
Perhaps the most interesting result involves the way this hidden network knits society together. Lijun and co say that the data hints that the connections between familiar strangers grows stronger over time. So seeing each other more often increases the chances that familiar strangers will become socially connected.
That’s a fascinating insight into the hidden social network in which we are all embedded. It’s important because it has implications for our understanding of the way things like epidemics can spread through cities.
Perhaps a more interesting is the insight it gives into how links form within communities and how these can strengthened. With the widespread adoption of smart cards on transport systems throughout the world, this kind of study can easily be repeated in many cities, which may help to tease apart some of the factors that make them so different.”
Ref: arxiv.org/abs/1301.5979: Understanding Metropolitan Patterns of Daily Encounters

Social: Why Our Brains are Wired to Connect


Book by Matthew D. Lieberman : “Why are we influenced by the behaviour of complete strangers? Why does the brain register similar pleasure when I perceive something as ‘fair’ or when I eat chocolate? Why can we be so profoundly hurt by bereavement? What are the evolutionary benefits of these traits? The young discipline of ‘social cognitive neuroscience’ has been exploring this fascinating interface between brain science and human behaviour since the late 1990s. Now one of its founding pioneers, Matthew D. Lieberman, presents the discoveries that he and fellow researchers have made. Using fMRI scanning and a range of other techniques, they have been able to see that the brain responds to social pain and pleasure the same way as physical pain and pleasure; and that unbeknown to ourselves, we are constantly ‘mindreading’ other people so that we can fit in with them. It is clear that our brains are designed to respond to and be influenced by others. For good evolutionary reasons, he argues, we are wired to be social. The implications are numerous and profound. Do we have to rethink what we understand by identity, and free will? How can managers improve the way their teams relate and perform? Could we organize large social institutions in ways that would work far better? And could there be whole new methods of education?”

A Smarter, More Innovative Government for the American People


Steve VanRoekel and Todd Park at the White House Blog: “This morning, the President held a meeting with his Cabinet and senior officials to lay out his vision for building a better, smarter, faster government over the course of his second term. During the meeting, the President directed Cabinet members and key officials in his Administration to build on the progress made over the first term, and he challenged us to improve government even further….
This morning, the President stated, “We need the brightest minds to help solve our biggest challenges. In this democracy, we, the people, realize this government is ours. It’s up to each and every one of us to make it work better. And we all have a stake in our success.” Read the President’s full remarks here, and see all the graphics from his speech below.”

The Management Agenda for Government Innovation

Open Government is an Open Conversation


Lisa Ellman and Hollie Russon Gilman at the White House Blog: “President Obama launched the first U.S. Open Government National Action Plan in September 2011, as part of the Nation’s commitment to the principles of the global Open Government Partnership. The Plan laid out twenty-six concrete steps the United States would take to promote public participation in government, increase transparency in government, and manage public resources more effectively.
A  year and a half later, we have fulfilled twenty-four of the Plan’s prescribed commitments—including launching the online We the People petition platform, which has been used by more than 9.6 million people, and unleashing thousands of government data resources as part of the Administration’s Open Data Initiatives.
We are proud of this progress, but recognize that there is always more work to be done to build a more efficient, effective, and transparent government. In that spirit, as part of our ongoing commitment to the international Open Government Partnership, the Obama Administration has committed to develop a second National Action Plan on Open Government.
To accomplish this task effectively, we’ll need all-hands-on-deck. That’s why we plan to solicit and incorporate your input as we develop the National Action Plan “2.0.”…
Over the next few months, we will continue to gather your thoughts. We will leverage online platforms such as Quora, Google+, and Twitter to communicate with the public and collect feedback.  We will meet with members of open government civil society organizations and other experts, to ensure all voices are brought to the table.  We will solicit input from Federal agencies on lessons learned from their unique experiences, and gather information about successful initiatives that could potentially be scaled across government.  And finally, we will canvass the international community for their diverse insights and innovative ideas.”

Frontiers in Massive Data Analysis


New Report from the National Research Council: “From Facebook to Google searches to bookmarking a webpage in our browsers, today’s society has become one with an enormous amount of data. Some internet-based companies such as Yahoo! are even storing exabytes (10 to the 18 bytes) of data. Like these companies and the rest of the world, scientific communities are also generating large amounts of data-—mostly terabytes and in some cases near petabytes—from experiments, observations, and numerical simulation. However, the scientific community, along with defense enterprise, has been a leader in generating and using large data sets for many years. The issue that arises with this new type of large data is how to handle it—this includes sharing the data, enabling data security, working with different data formats and structures, dealing with the highly distributed data sources, and more.
Frontiers in Massive Data Analysis presents the Committee on the Analysis of Massive Data’s work to make sense of the current state of data analysis for mining of massive sets of data, to identify gaps in the current practice and to develop methods to fill these gaps. The committee thus examines the frontiers of research that is enabling the analysis of massive data which includes data representation and methods for including humans in the data-analysis loop. The report includes the committee’s recommendations, details concerning types of data that build into massive data, and information on the seven computational giants of massive data analysis.”