New paper by Tiropanis Thanassis, Hall Wendy, Hendler James, and de Larrinaga Christian in Big Data: “The Web Observatory project1 is a global effort that is being led by the Web Science Trust,2 its network of WSTnet laboratories, and the wider Web Science community. The goal of this project is to create a global distributed infrastructure that will foster communities exchanging and using each other’s web-related datasets as well as sharing analytic applications for research and business web applications.3 It will provide the means to observe the digital planet, explore its processes, and understand their impact on different sectors of human activity.
The project is creating a network of separate web observatories, collections of datasets and tools for analyzing data about the Web and its use, each with their own use community. This allows researchers across the world to develop and share data, analytic approaches, publications related to their datasets, and tools (Fig. 1). The network of web observatories aims to bridge the gap that currently exists between big data analytics and the rapidly growing web of “broad data,”4 making it difficult for a large number of people to engage with them….”
Why Libraries [Still] Matter
Jonathan Zittrain at Medium: “…libraries — real ones concerned with guarding and curating knowledge — remain crucial to free and open societies, and not simply because their traditional services within academia, from curation to preservation to research, remain in high demand by scholars. More broadly, they crucially complement the Web in its highest aspirations: to provide unfettered access to knowledge, and to link authors and readers in new ways. Here’s why.
First, information may be easy to copy, but it’s also easy to poison and destroy. The Web is a distributed marvel: click on any link on a page and you’ll instantly be able to see to what it refers, whether it’s offered by the author of the page you’re already reading, or somewhere on the other side of the world, by a different person writing at a different time for a different purpose. That the act of citation and linkage could be made so easy to forge and to follow, and accessible to anyone with a Web browser rather than special patron privileges, is revolutionary.
But the very characteristics that make the distributed Net so powerful overall also make it dicey in any given use. Links rot; sources evaporate. The anarchic Web loses some luster every time that something an author meant to share turns out to be a 404-not-found error.
I co-authored a study investigating link rot in legal scholarship and judicial opinions, and was shocked to find that, circa late 2013, nearly three out of four links found within all Harvard Law Review articles were dead. Half of the links in U.S. Supreme Court opinions were dead. Before the Web, the only common link was an analog: an author had to name with great precision a source, and a reader could nearly always take that citation to a library and expect to be able to access the source. Labor intensive, but the barriers to publishing meant that most stuff linked was in books and other systematized formats that libraries were likely to store. Post-Web, much can be published without burdensome intermediaries, but if it vanishes, it vanishes.
That’s why the HLS Library is proud to be a founding member of perma.cc, a consortium complementing the extraordinary Internet Archive, seeking to preserve copies of the sources that scholars and judges link to on the open Web. The preserved materials can be readily accessible for the ages, placed on the record within a formal, disinterested, distributed repository of the world’s great libraries. This is especially important as information might not only vanish, but be adulterated. When Barnes and Noble can offer a book as canonical as War and Peace with key changes quietly (if accidentally) made to its vocabulary, it’s a signal that our knowledge requires actual guardians ready to preserve and fight for its integrity, rather than, in the words of John Perry Barlow, merely vendors treating ideas as “another industrial product, no more noble than pig iron.”…”
The View From Your Window Is Worth Cash to This Company
Eric Jaffe in Atlantic CityLab: “A city window overlooking the street has always been a score in its own right, what with so many apartments stuck opening onto back alleys and dumpsters and fire escapes. And now, a company wants to straight up monetize the view. New York startup Placemeter is paying city residents up to $50 a month for street views captured via old smartphones. The idea is to quantify sidewalk life in the service of making the city a more efficient place.
“Measuring data about how the city moves in real time, being able to make predictions on that, is definitely a good way to help cities work better,” says founder Alex Winter. “That’s the vision of Placemeter—to build a data platform where anyone at any time can know how busy the city is, and use that.”
Here’s how it works: City residents send Placemeter a little information about where they live and what they see from their window. In turn, Placemeter sends participants a kit (complete with window suction cup) to convert their unused smartphone into a street sensor, and agrees to pay cash so long as the device stays on and collects data. The more action outside—the more shops, pedestrians, traffic, and public space—the more the view is worth.
On the back end, Placemeter converts the smartphone images into statistical data using proprietary computer vision. The company first detects moving objects (the green splotches in the video below) and classifies them either as people or as 11 types of vehicles or other common urban elements, such as food carts. A second layer of analysis connects this movement with behavioral patterns based on the location—how many cars are speeding down a street, for instance, or how many people are going into a store….
Efforts to quantify city life with big data aren’t new, but where Placemeter’s clear advance is its ability to count pedestrians. Cities often track sidewalk traffic with little more than a hired hand and a manual clicker and spot locations. With its army of smartphone eyes, Placemeter promises a much wider net of real-time data dynamic enough to recognize not only that a person exists but also that person’s behavior, from walking speed to retail interest to general interaction with streets or public spaces…”
Things Fall Apart: How Social Media Leads to a Less Stable World
Commentary by Curtis Hougland at Knowledge@Wharton: “James Foley. David Haines. Steven Sotloff. The list of people beheaded by followers of the Islamic State of Iraq and Syria (ISIS) keeps growing. The filming of these acts on video and distribution via social media platforms such as Twitter represent a geopolitical trend in which social media has become the new frontline for proxy wars across the globe. While social media does indeed advance connectivity and wealth among people, its proliferation at the same time results in a markedly less stable world.
That social media benefits mankind is irrefutable. I have been an evangelist for the power of new media for 20 years. However, technology in the form of globalized communication, transportation and supply chains conspires to make today’s world more complex. Events in any corner of the world now impact the rest of the globe quickly and sharply. Nations are being pulled apart along sectarian seams in Iraq, tribal divisions in Afghanistan, national interests in Ukraine and territorial fences in Gaza. These conflicts portend a quickening of global unrest, confirmed by Foreign Policy magazine’s map of civil protest. The ISIS videos are simply the exposed wire. I believe that over the next century, even great nations will Balkanize — break into smaller nations. One of the principal drivers of this Balkanization is social media Twitter .
Social media is a behavior, an expression of the innate human need to socialize and share experiences. Social media is not simply a set of technology channels and networks. Both the public and private sectors have underestimated the human imperative to behave socially. The evidence is now clear with more than 52% of the population living in cities and approximately 2 billion people active in social media globally. Some 96% of content emanates from individuals, not brands, media or governments — a volume that far exceeds participation in democratic elections.
Social media is not egalitarian, though. Despite the exponential growth of user-generated content, people prefer to congregate online around like-minded individuals. Rather than seek out new beliefs, people choose to reinforce their existing political opinions through their actions online. This is illustrated in Pew Internet’s 2014 study, “Mapping Twitter Topic Networks from Polarized Crowds to Community Clusters.” Individuals self-organize by affinity, and within affinity, by sensibility and personality. The ecosystem of social media is predicated on delivering more of what the user already likes. This, precisely, is the function of a Follow or Like. In this way, media coagulates rather than fragments online….”
Behavioral Political Economy: A Survey
Paper by Jan Schnellenbach and Christian Schubert: “Explaining individual behavior in politics should rely on the same motivational assumptions as explaining behavior in the market: That’s what Political Economy, understood as the application of economics to the study of political processes, is all about. In its standard variant, those who played the game of politics should also be considered rational and self-interested, unlike the benevolent despot of earlier models. History repeats itself with the rise of behavioral economics: Assuming cognitive biases to be present in the market, but not in politics, behavioral economists often call for government to intervene in a “benevolent” way. Recently, however, political economists have started to apply behavioral economics insights to the study of political processes, thereby re-establishing a unified methodology. This paper surveys the current state of the emerging field of “Behavioral Political Economy” and considers the scope for further research.”
New Data for a New Energy Future
(This post originally appeared on the blog of the U.S. Chamber of Commerce Foundation.)
Two growing concerns—climate change and U.S. energy self-sufficiency—have accelerated the search for affordable, sustainable approaches to energy production and use. In this area, as in many others, data-driven innovation is a key to progress. Data scientists are working to help improve energy efficiency and make new forms of energy more economically viable, and are building new, profitable businesses in the process.
In the same way that government data has been used by other kinds of new businesses, the Department of Energy is releasing data that can help energy innovators. At a recent “Energy Datapalooza” held by the department, John Podesta, counselor to the President, summed up the rationale: “Just as climate data will be central to helping communities prepare for climate change, energy data can help us reduce the harmful emissions that are driving climate change.” With electric power accounting for one-third of greenhouse gas emissions in the United States, the opportunities for improvement are great.
The GovLab has been studying the business applications of public government data, or “open data,” for the past year. The resulting study, the Open Data 500, now provides structured, searchable information on more than 500 companies that use open government data as a key business driver. A review of those results shows four major areas where open data is creating new business opportunities in energy and is likely to build many more in the near future.
Commercial building efficiency
Commercial buildings are major energy consumers, and energy costs are a significant business expense. Despite programs like LEED Certification, many commercial buildings waste large amounts of energy. Now a company called FirstFuel, based in Boston, is using open data to drive energy efficiency in these buildings. At the Energy Datapalooza, Swap Shah, the company’s CEO, described how analyzing energy data together with geospatial, weather, and other open data can give a very accurate view of a building’s energy consumption and ways to reduce it. (Sometimes the solution is startlingly simple: According to Shah, the largest source of waste is running heating and cooling systems at the same time.) Other companies are taking on the same kind of task – like Lucid, which provides an operating system that can track a building’s energy use in an integrated way.
Home energy use
A number of companies are finding data-driven solutions for homeowners who want to save money by reducing their energy usage. A key to success is putting together measurements of energy use in the home with public data on energy efficiency solutions. PlotWatt, for example, promises to help consumers “save money with real-time energy tracking” through the data it provides. One of the best-known companies in this area, Opower, uses a psychological strategy: it simultaneously gives people access to their own energy data and lets them compare their energy use to their neighbors’ as an incentive to save. Opower partners with utilities to provide this information, and the Virginia-based company has been successful enough to open offices in San Francisco, London, and Singapore. Soon more and more people will have access to data on their home energy use: Green Button, a government-promoted program implemented by utilities, now gives about 100 million Americans data about their energy consumption.
Solar power and renewable energy
As solar power becomes more efficient and affordable, a number of companies are emerging to support this energy technology. Clean Power Finance, for example, uses its database to connect solar entrepreneurs with sources of capital. In a different way, a company called Solar Census is analyzing publicly available data to find exactly where solar power can be produced most efficiently. The kind of analysis that used to require an on-site survey over several days can now be done in less than a minute with their algorithms.
Other kinds of geospatial and weather data can support other forms of renewable energy. The data will make it easier to find good sites for wind power stations, water sources for small-scale hydroelectric projects, and the best opportunities to tap geothermal energy.
Supporting new energy-efficient vehicles
The Tesla and other electric vehicles are becoming commercially viable, and we will soon see even more efficient vehicles on the road. Toyota has announced that its first fuel-cell cars, which run on hydrogen, will be commercially available by mid-2015, and other auto manufacturers have announced plans to develop fuel-cell vehicles as well. But these vehicles can’t operate without a network to supply power, be it electricity for a Tesla battery or hydrogen for a fuel cell.
It’s a chicken-and-egg problem: People won’t buy large numbers of electric or fuel-cell cars unless they know they can power them, and power stations will be scarce until there are enough vehicles to support their business. Now some new companies are facilitating this transition by giving drivers data-driven tools to find and use the power sources they need. Recargo, for example, provides tools to help electric car owners find charging stations and operate their vehicles.
The development of new energy sources will involve solving social, political, economic, and technological issues. Data science can help develop solutions and bring us more quickly to a new kind of energy future.
Joel Gurin, senior advisor at the GovLab and project director, Open Data 500. He also currently serves as a fellow of the U.S. Chamber of Commerce Foundation.
Driving Innovation With Open Data
Research Article by The GovLab’s Joel Gurin (Chapter 6 in the report, “The Future of Data-Driven Innovation.”): The chapters in this report provide ample evidence of the power of data and its business potential. But like any business resource, data is only valuable if the benefit of using it outweighs its cost. Data collection, management, distribution, quality control, and application all come at a price—a potential obstacle for companies of any size, though especially for small and medium-sized enterprises.
Over the last several years, however, the “I” of data’s return on investment (ROI) has become less of a hurdle, and new data-driven companies are developing rapidly as a result. One major reason is that governments at the federal, state, and local level are making more data available at little or no charge for the private sector and the public to use. Governments collect data of all kinds—including scientific, demographic, and financial data—at taxpayer expense.
Now, public sector agencies and departments are increasingly repaying that public investment by making their data available to all for free or at a low cost. This is Open Data. While there are still costs in putting the data to use, the growing availability of this national resource is becoming a significant driver for hundreds of new businesses. This chapter describes the growing potential of Open Data and the data-driven innovation it supports, the types of data and applications that are most promising, and the policies that will encourage innovation going forward. Read and download this article in PDF format. “
Building a Smarter University Big Data, Innovation, and Analytics
New book edited by Jason E. Lane : “The Big Data movement and the renewed focus on data analytics are transforming everything from healthcare delivery systems to the way cities deliver services to residents. Now is the time to examine how this Big Data could help build smarter universities. While much of the cutting-edge research that is being done with Big Data is happening at colleges and universities, higher education has yet to turn the digital mirror on itself to advance the academic enterprise. Institutions can use the huge amounts of data being generated to improve the student learning experience, enhance research initiatives, support effective community outreach, and develop campus infrastructure. This volume focuses on three primary themes related to creating a smarter university: refining the operations and management of higher education institutions, cultivating the education pipeline, and educating the next generation of data scientists. Through an analysis of these issues, the contributors address how universities can foster innovation and ingenuity in the academy. They also provide scholarly and practical insights in order to frame these topics for an international discussion.”
Codifying Collegiality: Recent Developments in Data Sharing Policy in the Life Sciences
New paper by et al in PLoS ONE: “Over the last decade, there have been significant changes in data sharing policies and in the data sharing environment faced by life science researchers. Using data from a 2013 survey of over 1600 life science researchers, we analyze the effects of sharing policies of funding agencies and journals. We also examine the effects of new sharing infrastructure and tools (i.e., third party repositories and online supplements). We find that recently enacted data sharing policies and new sharing infrastructure and tools have had a sizable effect on encouraging data sharing. In particular, third party repositories and online supplements as well as data sharing requirements of funding agencies, particularly the NIH and the National Human Genome Research Institute, were perceived by scientists to have had a large effect on facilitating data sharing. In addition, we found a high degree of compliance with these new policies, although noncompliance resulted in few formal or informal sanctions. Despite the overall effectiveness of data sharing policies, some significant gaps remain: about one third of grant reviewers placed no weight on data sharing plans in their reviews, and a similar percentage ignored the requirements of material transfer agreements. These patterns suggest that although most of these new policies have been effective, there is still room for policy improvement.”
CaseCommons
About: “The vision of Case Commons is to support the transformation of public human services through innovative technology. In the 21st century, web-native, real time technology and analytics all have the potential to radically change how public human services agencies meet the needs of the country’s most vulnerable children and families.
To fulfill this vision, we have designed and built revolutionary software for child welfare. Called Casebook, our tool has been collaboratively developed with agencies and practitioners, uses intuitive design to meet the needs of human services caseworkers and administrators, and is centered on the person and their family rather than isolated “cases.” Casebook helps support child welfare workers and policy makers in their effort to make decisions based on data, rather than on anecdote.
The mission of our organization is to:
• Change Lives: above all, Case Commons seeks to better serve, and to improve outcomes and life opportunities for vulnerable children and their families;
• Help the Helpers: Case Commons believes that new technology can and must support – not hinder – the frontline workers who serve our nation’s most vulnerable children and families; and
• Measure Results: Case Commons uses the latest technology to improve the quality and timeliness of data and analytics so that everyone can make better decisions. Supervisors can better support their workers, policymakers can understand what works, and everyone can use greater knowledge to transform service delivery and improve lives.
…
Casebook is a powerful example of technology innovation at work, and Case Commons is helping to lead a growing movement to revolutionize how government puts technology to work for Americans.
Read our paper on Casebook and the future of government innovation.“