Paper by Michael Curtotti, Wayne Weibel, Eric McCreath, Nicolas Ceynowa, Sara Frug, and Tom R Bruce: “This paper sits at the intersection of citizen access to law, legal informatics and plain language. The paper reports the results of a joint project of the Cornell University Legal Information Institute and the Australian National University which collected thousands of crowdsourced assessments of the readability of law through the Cornell LII site. The aim of the project is to enhance accuracy in the prediction of the readability of legal sentences. The study requested readers on legislative pages of the LII site to rate passages from the United States Code and the Code of Federal Regulations and other texts for readability and other characteristics. The research provides insight into who uses legal rules and how they do so. The study enables conclusions to be drawn as to the current readability of law and spread of readability among legal rules. The research is intended to enable the creation of a dataset of legal rules labelled by human judges as to readability. Such a dataset, in combination with machine learning, will assist in identifying factors in legal language which impede readability and access for citizens. As far as we are aware, this research is the largest ever study of readability and usability of legal language and the first research which has applied crowdsourcing to such an investigation. The research is an example of the possibilities open for enhancing access to law through engagement of end users in the online legal publishing environment for enhancement of legal accessibility and through collaboration between legal publishers and researchers….(More)”
White House Releases 150 Data Sets to Fight Climate Change
The undertakings were released at a White House climate and health conference where John Holdren, director of the White House Office of Science and Technology Policy, pressed the need for greater data to compel decreases to greenhouse emissions.
“This is a science-based administration, a fact-based administration, and our climate policies have to be based on fact, have to be based on data, and we want to make those data available to everybody,” Holdren said.
The data initiative touches multiple agencies — including NASA, the Centers for Disease Control and Prevention, the National Institutes of Health and the Environmental Protection Agency — and is part of the White House proclamation of a new National Public Health Week, from April 6 to April 12, to spur national health solutions and awareness.
The 150-plus data sets are all connected to health, and are among the 560 climate-related data sets available on Data.gov, the U.S. government’s open data portal. Accompanying the release, the Department of Health and Human Services added a Health Care Facilities Toolkit on Toolkit.climate.gov, a site that delivers climate resilience techniques, strategies, case studies and tools for organizations attempting climate change initiatives.
Holdren was followed by White House Chief Data Scientist D.J. Patil, who moderated a tech industry panel with representatives from Google, Microsoft and GIS mapping software company Esri.
Google Earth Outreach Program Manager Allison Lieber confirmed that Google will continue to provide assistance with 10 million hours for high-performance computing for climate data projects — down from 50 million in 2014 — and the company will likewise provide climate data hosting on Google Earth….(More)”
Big Data, Little Data, No Data
New book by Christine L. Borgman: “Big Data” is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data—because relevant data don’t exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines.
Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure—an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation—six “provocations” meant to inspire discussion about the uses of data in scholarship—Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship….(More)”
Discovering the Language of Data: Personal Pattern Languages and the Social Construction of Meaning from Big Data
Paper by Kim Erwin; Maggee Bond; Aashika Jain in Interdisciplinary Science Reviews: “This paper attempts to address two issues relevant to the sense-making of Big Data. First, it presents a case study for how a large dataset can be transformed into both a visual language and, in effect, a ‘text’ that can be read and interpreted by human beings. The case study comes from direct observation of graduate students at the IIT Institute of Design who investigated task-switching behaviours, as documented by productivity software on a single user’s laptop and a smart phone. Through a series of experiments with the resulting dataset, the team effects a transformation of that data into a catalogue of visual primitives — a kind of iconic alphabet — that allow others to ‘read’ the data as a corpus and, more provocatively, suggest the formation of a personal pattern language. Second, this paper offers a model for human-technical collaboration in the sense-making of data, as demonstrated by this and other teams in the class. Current sense-making models tend to be data- and technology-centric, and increasingly presume data visualization as a primary point of entry of humans into Big Data systems. This alternative model proposes that meaningful interpretation of data emerges from a more elaborate interplay between algorithms, data and human beings….(More)”
Eight ways to make government more experimental
Such an approach requires a degree of humility. Facing up to the fact that we don’t have all the answers for the next five years. We need to test things out, evaluate new ways of doing things with the best of social science, and grow what works. And drop policies that fail.
But how best to go about it? Here are our 8 ways to make it a reality:
- Make failure OK. A more benign attitude to risk is central to experimentation. As a 2003 Cabinet Office review entitled Trying it Out said, a pilot that reveals a policy to be flawed should be ‘viewed as a success rather than a failure, having potentially helped to avert a potentially larger political and/or financial embarrassment’. Pilots are particularly important in fast moving areas such as technology to try promising fresh ideas in real-time. Our ‘Visible Classroom’ pilot tried an innovative approach to teacher CPD developed from technology for television subtitling.
- Avoid making policies that are set in stone. Allowing policy to be more project–based, flexible and time-limited could encourage room for manoeuvre, according to a previous Nesta report State of Uncertainty; Innovation policy through experimentation. The Department for Work and Pensions’ Employment Retention and Advancement pilot scheme to help people back to work was designed to influence the shape of legislation. It allowed for amendments and learning as it was rolled out. We need more policy experiments like this.
- Work with the grain of current policy environment. Experimenters need to be opportunists. We need to be nimble and flexible. Ready to seize windows of opportunity to experiment. Some services have to be rolled out in stages due to budget constraints. This offers opportunities to try things out before going national. For instance, The Mexican Oportunidades anti-poverty experiments which eventually reached 5.8 million households in all Mexican states, had to be trialled first in a handful of areas. Greater devolution is creating a patchwork of different policy priorities, funding and delivery models – so-called ‘natural experiments’. Let’s seize the opportunity to deliberately test and compare across different jurisdictions. What about a trial of basic income in Northern Ireland, for example, along the lines of recent Finnish proposals, or universal free childcare in Scotland?
- Experiments need the most robust and appropriate evaluation methods such as, if appropriate, Randomised Controlled Trials. Other methods, such as qualitative research may be needed to pry open the ‘black box’ of policies – to learn about why and how things are working. Civil servants should use the government trial advice panel as a source of expertise when setting up experiments.
- Grow the public debate about the importance of experimentation. Facebook had to apologise after a global backlash to psychological experiments on their 689,000 users web-users. Approval by ethics committees – normal practice for trials in hospitals and universities – is essential, but we can’t just rely on experts. We need a dedicated public understanding of experimentation programmes, perhaps run by Evidence Matters or Ask for Evidence campaigns at Sense about Science. Taking part in an experiment in itself can be a learning opportunity creating an appetite amongt the public, something we have found from running an RCT with schools.
- Create ‘Skunkworks’ institutions. New or improved institutional structures within government can also help with experimentation. The Behavioural Insights Team, located in Nesta, operates a classic ‘skunkworks’ model, semi-detached from day-to-day bureaucracy. The nine UK What Works Centres help try things out semi-detached from central power, such as the The Education Endowment Foundation who source innovations widely from across the public and private sectors- including Nesta- rather than generating ideas exclusively in house or in government.
- Find low-cost ways to experiment. People sometimes worry that trials are expensive and complicated. This does not have to be the case. Experiments to encourage organ donation by the Government Digital Service and Behavioural Insights Team involved an estimated cost of £20,000. This was because the digital experiments didn’t involve setting up expensive new interventions – just changing messages on web pages for existing services. Some programmes do, however, need significant funding to evaluate and budgets need to be found for it. A memo from the White House Office for Management and Budget has asked for new Government schemes seeking funding to allocate a proportion of their budgets to ‘randomized controlled trials or carefully designed quasi-experimental techniques’.
- Be bold. A criticism of some experiments is that they only deal with the margins of policy and delivery. Government officials and researchers should set up more ambitious experiments on nationally important big-ticket issues, from counter-terrorism to innovation in jobs and housing….(More)
New Desktop Application Has Potential to Increase Asteroid Detection, Now Available to Public
NASA Press Release: “A software application based on an algorithm created by a NASA challenge has the potential to increase the number of new asteroid discoveries by amateur astronomers.
Analysis of images taken of our solar system’s main belt asteroids between Mars and Jupiter using the algorithm showed a 15 percent increase in positive identification of new asteroids.
During a panel Sunday at the South by Southwest Festival in Austin, Texas, NASA representatives discussed how citizen scientists have made a difference in asteroid hunting. They also announced the release of a desktop software application developed by NASA in partnership with Planetary Resources, Inc., of Redmond, Washington. The application is based on an Asteroid Data Hunter-derived algorithm that analyzes images for potential asteroids. It’s a tool that can be used by amateur astronomers and citizen scientists.
The Asteroid Data Hunter challenge was part of NASA’s Asteroid Grand Challenge. The data hunter contest series, which was conducted in partnership with Planetary Resources under a Space Act Agreement, was announced at the 2014 South by Southwest Festival and concluded in December. The series offered a total of $55,000 in awards for participants to develop significantly improved algorithms to identify asteroids in images captured by ground-based telescopes. The winning solutions of each piece of the contest combined to create an application using the best algorithm that increased the detection sensitivity, minimized the number of false positives, ignored imperfections in the data, and ran effectively on all computer systems.
“The Asteroid Grand Challenge is seeking non-traditional partnerships to bring the citizen science and space enthusiast community into NASA’s work,” said Jason Kessler, program executive for NASA’s Asteroid Grand Challenge. “The Asteroid Data Hunter challenge has been successful beyond our hopes, creating something that makes a tangible difference to asteroid hunting astronomers and highlights the possibility for more people to play a role in protecting our planet.”…
The new asteroid hunting application can be downloaded at:
For information about NASA’s Asteroid Grand Challenge, visit:
Mission Control: A History of the Urban Dashboard
Futuristic control rooms have proliferated in dozens of global cities. Baltimore has its CitiStat Room, where department heads stand at a podium before a wall of screens and account for their units’ performance. The Mayor’s office in London’s City Hall features a 4×3 array of iPads mounted in a wooden panel, which seems an almost parodic, Terry Gilliam-esque take on the Brazilian Ops Center. Meanwhile, British Prime Minister David Cameron commissioned an iPad app – the “No. 10 Dashboard” (a reference to his residence at 10 Downing Street) – which gives him access to financial, housing, employment, and public opinion data. As The Guardian reported, “the prime minister said that he could run government remotely from his smartphone.”
This is the age of Dashboard Governance, heralded by gurus like Stephen Few, founder of the “visual business intelligence” and “sensemaking” consultancy Perceptual Edge, who defines the dashboard as a “visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.” A well-designed dashboard, he says — one that makes proper use of bullet graphs, sparklines, and other visualization techniques informed by the “brain science” of aesthetics and cognition — can afford its users not only a perceptual edge, but a performance edge, too. The ideal display offers a big-picture view of what is happening in real time, along with information on historical trends, so that users can divine the how and why and redirect future action. As David Nettleton emphasizes, the dashboard’s utility extends beyond monitoring “the current situation”; it also “allows a manager to … make provisions, and take appropriate actions.”….
The dashboard market now extends far beyond the corporate world. In 1994, New York City police commissioner William Bratton adapted former officer Jack Maple’s analog crime maps to create the CompStat model of aggregating and mapping crime statistics. Around the same time, the administrators of Charlotte, North Carolina, borrowed a business idea — Robert Kaplan’s and David Norton’s “total quality management” strategy known as the “Balanced Scorecard” — and began tracking performance in five “focus areas” defined by the City Council: housing and neighborhood development, community safety, transportation, economic development, and the environment. Atlanta followed Charlotte’s example in creating its own city dashboard.
In 1999, Baltimore mayor Martin O’Malley, confronting a crippling crime rate and high taxes, designed CitiStat, “an internal process of using metrics to create accountability within his government.” (This rhetoric of data-tested internal “accountability” is prevalent in early dashboard development efforts.) The project turned to face the public in 2003, when Baltimore launched a website of city operational statistics, which inspired DCStat (2005), Maryland’s StateStat (2007), and NYCStat (2008). Since then, myriad other states and metro areas — driven by a “new managerialist” approach to urban governance, committed to “benchmarking” their performance against other regions, and obligated to demonstrate compliance with sustainability agendas — have developed their own dashboards.
The Open Michigan Mi Dashboard is typical of these efforts. The state website presents data on education, health and wellness, infrastructure, “talent” (employment, innovation), public safety, energy and environment, financial health, and seniors. You (or “Mi”) can monitor the state’s performance through a side-by-side comparison of “prior” and “current” data, punctuated with a thumbs-up or thumbs-down icon indicating the state’s “progress” on each metric. Another click reveals a graph of annual trends and a citation for the data source, but little detail about how the data are actually derived. How the public is supposed to use this information is an open question….(More)”
Why governments need guinea pigs for policies
Jonathan Breckon in the Guardian:”People are unlikely to react positively to the idea of using citizens as guinea pigs; many will be downright disgusted. But there are times when government must experiment on us in the search for knowledge and better policy….
Though history calls into question the ethics of experimentation, unless we try things out, we will never learn. The National Audit Office says that £66bn worth of government projects have no plans to evaluate their impact. It is unethical to roll out policies in this arbitrary way. We have to experiment on a small scale to have a better understanding of how things work before rolling out policies across the UK. This is just as relevant to social policy, as it is to science and medicine, as set out in a new report by the Alliance for Useful Evidence.
Whether it’s the best ways to teach our kids to read, designing programmes to get unemployed people back to work, or encouraging organ donation – if the old ways don’t work, we have to test new ones. And that testing can’t always be done by a committee in Whitehall or in a university lab.
Experimentation can’t happen in isolation. What works in Lewisham or Londonnery, might not work in Lincoln – or indeed across the UK. For instance, there is a huge amount debate around the current practice of teaching children to read and spell using phonics, which was based on a small-scale study in Clackmannanshire, as well as evidence from the US. A government-commissioned review on the evidence for phonics led professor Carole Torgerson, then at York University, to warn against making national policy off the back of just one small Scottish trial.
One way round this problem is to do larger experiments. The increasing use of the internet in public services allows for more and faster experimentation, on a larger scale for lower cost – the randomised controlled trial on voter mobilisation that went to 61 million users in the 2010 US midterm elections, for example. However, the use of the internet doesn’t get us off the ethical hook. Facebook had to apologise after a global backlash to secret psychological tests on their 689,000 users.
Contentious experiments should be approved by ethics committees – normal practice for trials in hospitals and universities.
We are also not interested in freewheeling trial-and-error; robust and appropriate research techniques to learn from experiments are vital. It’s best to see experimentation as a continuum, ranging from the messiness of attempts to try something new to experiments using the best available social science, such as randomised controlled trials.
Experimental government means avoiding an approach where everything is fixed from the outset. What we need is “a spirit of experimentation, unburdened by promises of success”, as recommended by the late professor Roger Jowell, author of the 2003 Cabinet Office report, Trying it out [pdf]….(More)”
Big Data for Social Good
Introduction to a Special Issue of the Journal “Big Data” by Catlett Charlie and Ghani Rayid: “…organizations focused on social good are realizing the potential as well but face several challenges as they seek to become more data-driven. The biggest challenge they face is a paucity of examples and case studies on how data can be used for social good. This special issue of Big Data is targeted at tackling that challenge and focuses on highlighting some exciting and impactful examples of work that uses data for social good. The special issue is just one example of the recent surge in such efforts by the data science community. …
This special issue solicited case studies and problem statements that would either highlight (1) the use of data to solve a social problem or (2) social challenges that need data-driven solutions. From roughly 20 submissions, we selected 5 articles that exemplify this type of work. These cover five broad application areas: international development, healthcare, democracy and government, human rights, and crime prevention.
“Understanding Democracy and Development Traps Using a Data-Driven Approach” (Ranganathan et al.) details a data-driven model between democracy, cultural values, and socioeconomic indicators to identify a model of two types of “traps” that hinder the development of democracy. They use historical data to detect causal factors and make predictions about the time expected for a given country to overcome these traps.
“Targeting Villages for Rural Development Using Satellite Image Analysis” (Varshney et al.) discusses two case studies that use data and machine learning techniques for international economic development—solar-powered microgrids in rural India and targeting financial aid to villages in sub-Saharan Africa. In the process, the authors stress the importance of understanding the characteristics and provenance of the data and the criticality of incorporating local “on the ground” expertise.
In “Human Rights Event Detection from Heterogeneous Social Media Graphs,” Chen and Neil describe efficient and scalable techniques to use social media in order to detect emerging patterns in human rights events. They test their approach on recent events in Mexico and show that they can accurately detect relevant human rights–related tweets prior to international news sources, and in some cases, prior to local news reports, which could potentially lead to more timely, targeted, and effective advocacy by relevant human rights groups.
“Finding Patterns with a Rotten Core: Data Mining for Crime Series with Core Sets” (Wang et al.) describes a case study with the Cambridge Police Department, using a subspace clustering method to analyze the department’s full housebreak database, which contains detailed information from thousands of crimes from over a decade. They find that the method allows human crime analysts to handle vast amounts of data and provides new insights into true patterns of crime committed in Cambridge…..(More)
Our New Three Rs: Rigor, Relevance, and Readability
Article by Stephen J. Del Rosso in Governance: “…Because of the dizzying complexity of the contemporary world, the quest for a direct relationship between academic scholarship and its policy utility is both quixotic and unnecessary. The 2013 U.S. Senate’s vote to prohibit funding for political science projects through the National Science Foundation, except for those certified “as promoting national security or the economic interests of the United States,” revealed a fundamental misreading of the nonlinear path between idea and policy. Rather than providing a clear blueprint for addressing emergent or long-standing challenges, a more feasible role for academic scholarship is what political scientist Roland Paris describes as helping to “order the world in which officials operate.” Scholarly works can “influence practitioners’ understandings of what is possible or desirable in a particular policy field or set of circumstances,” he believes, by “creating operational frameworks for … identifying options and implementing policies.”
It is sometimes claimed that think tanks should play the main role in conveying scholarly insights to policymakers. But, however they may have mastered the sound bite, the putative role of think tanks as effective transmission belts for policy-relevant ideas is limited by their lack of academic rigor and systematic peer review. There is also a tendency, particularly among some “Inside the Beltway” experts, to trim their sails to the prevailing political winds and engage in self-censorship to keep employment options open in current or future presidential administrations. Scholarship’s comparative advantage in the marketplace of ideas is also evident in terms of its anticipatory function—the ability to loosen the intellectual bolts for promising policies not quite ready for implementation. A classic example is Swedish Nobel laureate Gunner Myrdal’s 1944 study of race relations, The American Dilemma, which was largely ignored and even disavowed by its sponsors for over a decade until it proved essential to the landmark Supreme Court decision in Brown v. Board of Education. Moreover, it should also be noted, rather than providing a detailed game plan for addressing the problem of race in the country, Myrdal’s work was a quintessential example of the power of scholarship to frame critically important issues.
To bridge the scholarship–policy gap, academics must balance rigor and relevance with a third “R”—readability. There is no shortage of important scholarly work that goes unnoticed or unread because of its presentation. Scholars interested in having influence beyond the ivory tower need to combine their pursuit of disciplinary requirements with efforts to make their work more intelligible and accessible to a broader audience. For example, new forms of dissemination, such as blogs and other social media innovations, provide policy-relevant scholars with ample opportunities to supplement more traditional academic outlets. The recent pushback from the editors of the International Studies Association’s journals to the announced prohibition on their blogging is one indication that the cracks in the old system are already appearing.
At the risk of oversimplification, there are three basic tribes populating the political science field. One tribe comprises those who “get it” when it comes to the importance of policy relevance, a second eschews such engagement with the real world in favor of knowledge for knowledge’s sake, and a third is made up of anxious untenured assistant professors who seek to follow the path that will best provide them with secure employment. If war, as was famously said, is too important to be left to the generals, then the future of the political science field is too important to be left to the intellectual ostriches who bury their heads in self-referential esoterica. However, the first tribe needs to be supported, and the third tribe needs to be shown that there is professional value in engaging with the world, both to enlighten and, perhaps more importantly, to provoke—a sentiment the policy-relevant scholar and inveterate provocateur, Huntington, would surely have endorsed…(More)”