Paper by Max Craglia & Lea Shanley: “The global landscape in the supply, co-creation and use of geospatial data is changing very rapidly with new satellites, sensors and mobile devices reconfiguring the traditional lines of demand and supply and the number of actors involved. In this paper we chart some of these technology-led developments and then focus on the opportunities they have created for the increased participation of the public in generating and contributing information for a wide range of uses, scientific and non. Not all this information is open or geospatial, but sufficiently large portions of it are to make it one of the most significant phenomena of the last decade. In fact, we argue that while satellite and sensors have exponentially increased the volumes of geospatial information available, the participation of the public is transformative because it expands the range of participants and stakeholders in society using and producing geospatial information, with opportunities for more direct participation in science, politics and social action…(View full text)”
Data scientists rejoice! There’s an online marketplace selling algorithms from academics
SiliconRepublic: “Algorithmia, an online marketplace that connects computer science researchers’ algorithms with developers who may have uses for them, has exited its private beta.
Algorithms are essential to our online experience. Google uses them to determine which search results are the most relevant. Facebook uses them to decide what should appear in your news feed. Netflix uses them to make movie recommendations.
Founded in 2013, Algorithmia could be described as an app store for algorithms, with over 800 of them available in its library. These algorithms provide the means of completing various tasks in the fields of machine learning, audio and visual processing, and computer vision.
Algorithmia found a way to monetise algorithms by creating a platform where academics can share their creations and charge a royalty fee per use, while developers and data scientists can request specific algorithms in return for a monetary reward. One such suggestion is for ‘punctuation prediction’, which would insert correct punctuation and capitalisation in speech-to-text translation.
While it’s not the first algorithm marketplace online, Algorithmia will accept and sell any type of algorithm and host them on its servers. What this means is that developers need only add a simple piece of code to their software in order to send a query to Algorithmia’s servers, so the algorithm itself doesn’t have to be integrated in its entirety….
Computer science researchers can spend years developing algorithms, only for them to be published in a scientific journal never to be read by software engineers.
Algorithmia intends to create a community space where academics and engineers can meet to discuss and refine these algorithms for practical use. A voting and commenting system on the site will allow users to engage and even share insights on how contributions can be improved.
To that end, Algorithmia’s ultimate goal is to advance the development of algorithms as well as their discovery and use….(More)”
Turning smartphones into personal, real-time pollution-location monitors
Kurzweil Newsletter: “Scientists reporting in the ACS journal Environmental Science & Technology have used smartphone and sensing technology to better pinpoint times and locations of the worst air pollution, which is associated with respiratory and cardiovascular problems.
Most such studies create a picture of exposure based on air pollution levels outside people’s homes. This approach ignores big differences in air quality in school and work environments. It also ignores spikes in pollution that happen over the course of the day such as during rush hour.
To fill in these gaps, Mark J. Nieuwenhuijsen and colleagues in Spain, The Netherlands, and the U.S. equipped 54 school children from from 29 different schools around Barcelona with smartphones that could track their location and physical activity. The children also received sensors that continuously measured the ambient levels of black carbon, a component of soot. Although most children spent less than 4 percent of their day traveling to and from school, this exposure contributed 13 percent of their total potential black carbon exposure.
The study was associated with BREATHE, an epidemiological study of the relation between air pollution and brain development.
The researchers conclude that mobile technologies could contribute valuable new insights into air pollution exposure….
Index: Prizes and Challenges
The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on prizes and challenges and was originally published in 2015.
This index highlights recent findings about two key techniques in shifting innovation from institutions to the general public:
- Prize-Induced Contests – using monetary rewards to incentivize individuals and other entities to develop solutions to public problems; and
- Grand Challenges – posing large, audacious goals to the public to spur collaborative, non-governmental efforts to solve them.
You can read more about Governing through Prizes and Challenges here. You can also watch Alph Bingham, co-founder of Innocentive, answer the GovLab’s questions about challenge authoring and defining the problem here.
Previous installments of the Index include Measuring Impact with Evidence, The Data Universe, Participation and Civic Engagement and Trust in Institutions. Please share any additional statistics and research findings on the intersection of technology in governance with us by emailing shruti at thegovlab.org.
Prize-Induced Contests
- Year the British Government introduced the Longitude Prize, one of the first instances of prizes by government to spur innovation: 1714
- President Obama calls on “all agencies to increase their use of prizes to address some of our Nation’s most pressing challenges” in his Strategy for American Innovation: September 2009
- The US Office of Management and Budget issues “a policy framework to guide agencies in using prizes to mobilize American ingenuity and advance their respective core missions”: March 2010
- Launch of Challenge.gov, “a one-stop shop where entrepreneurs and citizen solvers can find public-sector prize competitions”: September 2010
- Number of competitions currently live on Challenge.gov in February 2015: 22 of 399 total
- How many competitions on Challenge.gov are for $1 million or above: 23
- The America COMPETES Reauthorization Act is introduced, which grants “all Federal agencies authority to conduct prize competitions to spur innovation, solve tough problems, and advance their core missions”: 2010
- Value of prizes authorized by COMPETES: prizes up to $50 million
- Fact Sheet and Frequently Asked Questions memorandum issued by the Office of Science and Technology Policy and the Office of Management and Budget to aid agencies to take advantage of authorities in COMPETES: August 2011
- Number of prize competitions run by the Federal government from 2010 to April 2012: 150
- How many Federal agencies have run prize competitions by 2012: 40
- Prior to 1991, the percentage of prize money that recognized prior achievements according to an analysis by McKinsey and Company: 97%
- Since 1991, percentage of new prize money that “has been dedicated to inducement-style prizes that focus on achieving a specific, future goal”: 78%
- Value of the prize sector as estimated by McKinsey in 2009: $1-2 billion
- Growth rate of the total value of new prizes: 18% annually
- Growth rate in charitable giving in the US: 2.5% annually
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Value of the first Horizon Prize awarded in 2014 by the European Commission to German biopharmaceutical company CureVac GmbH “for progress towards a novel technology to bring life-saving vaccines to people across the planet in safe and affordable ways”: €2 million
- Number of solvers registered on InnoCentive, a crowdsourcing company: 355,000+ from nearly 200 countries
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- Total Challenges Posted: 2,000+ External Challenges
- Total Solution Submissions: 40,000+
- Value of the awards: $5,000 to $1+ million
- Success Rate for premium challenges: 85%
Grand Challenges
- Value of the Progressive Insurance Automotive X Prize, sponsored in part by DOE to develop production-capable super fuel-efficient vehicles: $10 million
- Number of teams around the world who took part in the challenge “to develop a new generation of technologies” for production-capable super fuel-efficient vehicles: 111 teams
- Time it took for the Air Force Research Laboratory to receive a workable solution on “a problem that had vexed military security forces and civilian police for years” by opening the challenge to the world: 60 days
- Value of the HHS Investing in Innovation initiative to spur innovation in Health IT, launched under the new COMPETES act: $5 million program
- Number of responses received by NASA for its Asteroid Grand Challenge RFI which seeks to identify and address all asteroid threats to the human population: over 400
- The decreased cost of sequencing a single human genome as a result of the Human Genome Project Grand Challenge: $7000 from $100 million
- Amount the Human Genome Project Grand Challenge has contributed to the US economy for every $1 invested by the US federal government: $141 for every $1 invested
- The amount of funding for research available for the “Brain Initiative,” a collaboration between the National Institute of Health, DARPA and the National Science Foundation, which seeks to uncover new prevention and treatment methods for brain disorders like Alzheimer’s, autism and schizophrenia: $100 million
- Total amount offered in cash awards by the Department of Energy’s “SunShot Grand Challenge,” which seeks to eliminate the cost disparity between solar energy and coal by the end of the decade: $10 million
Sources
- ‘And the winner is…’ Capturing the promise of philanthropic prizes. McKinsey & Company. July 2009.
- Collins, Francis and Prabhakar, Arati. BRAIN Initiative Challenges Researchers to Unlock Mysteries of Human Mind. The White House. April 02, 2013.
- Facts and Stats. InnoCentive. Last accessed March 2015.
- Horizon Prizes. European Commission. Last accessed March 2015.
- Implementation of Federal Prize Authority: Fiscal Year 2013 Progress Report. White House Office of Science and Technology Policy. May, 2014.
- Implementation of Federal Prize Authority: Progress Report. White House Office of Science and Technology Policy. March, 2012.
- Kalil, Tom and Dorgelo, Cristin. Identifying Steps Forward in Use of Prizes to Spur Innovation. White House Blog: Office of Science and Technology Policy. April 10, 2012.
- SunShot Prize: Race to 7-Day Solar. Energy.gov. Last accessed March 2015.
- The History. Longitude Prize. Last accessed March 2015.
Encyclopedia of Social Network Analysis and Mining
“The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining. While ESNAM reflects the state-of-the-art in social network research, the field had its start in the 1930s when fundamental issues in social network research were broadly defined. These communities were limited to relatively small numbers of nodes (actors) and links. More recently the advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. People around the world are directly or indirectly connected by popular social networks established using web-based platforms rather than by physical proximity.
Reflecting the interdisciplinary nature of this unique field, the essential contributions of diverse disciplines, from computer science, mathematics, and statistics to sociology and behavioral science, are described among the 300 authoritative yet highly readable entries. Students will find a world of information and insight behind the familiar façade of the social networks in which they participate. Researchers and practitioners will benefit from a comprehensive perspective on the methodologies for analysis of constructed networks, and the data mining and machine learning techniques that have proved attractive for sophisticated knowledge discovery in complex applications. Also addressed is the application of social network methodologies to other domains, such as web networks and biological networks….(More)”
Evaluating Complex Social Initiatives
Srik Gopal at Stanford Social Innovation Review: “…the California Endowment (TCE) .. and ..The Grand Rapids Community Foundation (GRCF) …are just two funders who are actively “shifting the lens” in terms of how they are looking at evaluation in the light of complexity. They are building on the recognition that a traditional approach to evaluation—assessing specific effects of a defined program according to a set of pre-determined outcomes, often in a way that connects those outcomes back to the initiative—is increasingly falling short. There is a clear message emerging that evaluation needs to accommodate complexity, not “assume it away.”
My colleagues at FSG and I have, based on our work with TCE, GRCF, and numerous other clients, articulated a set of nine “propositions” in a recent practice brief that are helpful in guiding how we conceptualize, design, and implement evaluations of complex initiatives. We derived these propositions from what we now know (based on the emerging field of complexity science) as distinctive characteristics of complex systems. We know, for example, that complex systems are always changing, often in unpredictable ways; they are never static. Hence, we need to design evaluations so that they are adaptive, flexible, and iterative, not rigid and cookie-cutter.
Below are three of the propositions in more detail, along with tools and methods that can help apply the proposition in practice.
It is important to note that many of the traditional tools and methods that form the backbone of sound evaluations—such as interviews, focus groups, and surveys—are still relevant. We would, however, suggest that organizations adapt those methods to reflect a complexity orientation. For example, interviews should explore the role of context; we should not confine them to the initiative’s boundaries. Focus groups should seek to understand local adaptation, not just adherence. And surveys should probe for relationships and interdependencies, not just perceived outcomes. In addition to traditional methods, we suggest incorporating newer, innovative techniques that provide a richer narrative, including:
- Systems mapping—an iterative, often participatory process of graphically representing a system, including its components and connections
- Appreciative inquiry—a group process that inquires into, identifies, and further develops the best of “what is” in organizations
- Design thinking—a user-centered approach to developing new solutions to abstract, ill-defined, or complex problems… (More)”
If Data Sharing is the Answer, What is the Question?
Christine L. Borgman at ERCIM News: “Data sharing has become policy enforced by governments, funding agencies, journals, and other stakeholders. Arguments in favor include leveraging investments in research, reducing the need to collect new data, addressing new research questions by reusing or combining extant data, and reproducing research, which would lead to greater accountability, transparency, and less fraud. Arguments against data sharing rarely are expressed in public fora, so popular is the idea. Much of the scholarship on data practices attempts to understand the socio-technical barriers to sharing, with goals to design infrastructures, policies, and cultural interventions that will overcome these barriers.
However, data sharing and reuse are common practice in only a few fields. Astronomy and genomics in the sciences, survey research in the social sciences, and archaeology in the humanities are the typical exemplars, which remain the exceptions rather than the rule. The lack of success of data sharing policies, despite accelerating enforcement over the last decade, indicates the need not just for a much deeper understanding of the roles of data in contemporary science but also for developing new models of scientific practice. Science progressed for centuries without data sharing policies. Why is data sharing deemed so important to scientific progress now? How might scientific practice be different if these policies were in place several generations ago?
Enthusiasm for “big data” and for data sharing are obscuring the complexity of data in scholarship and the challenges for stewardship. Data practices are local, varying from field to field, individual to individual, and country to country. Studying data is a means to observe how rapidly the landscape of scholarly work in the sciences, social sciences, and the humanities is changing. Inside the black box of data is a plethora of research, technology, and policy issues. Data are best understood as representations of observations, objects, or other entities used as evidence of phenomena for the purposes of research or scholarship. Rarely do they stand alone, separable from software, protocols, lab and field conditions, and other context. The lack of agreement on what constitutes data underlies the difficulties in sharing, releasing, or reusing research data.
Concerns for data sharing and open access raise broader questions about what data to keep, what to share, when, how, and with whom. Open data is sometimes viewed simply as releasing data without payment of fees. In research contexts, open data may pose complex issues of licensing, ownership, responsibility, standards, interoperability, and legal harmonization. To scholars, data can be assets, liabilities, or both. Data have utilitarian value as evidence, but they also serve social and symbolic purposes for control, barter, credit, and prestige. Incentives for scientific advancement often run counter to those for sharing data.
….
Rather than assume that data sharing is almost always a “good thing” and that doing so will promote the progress of science, more critical questions should be asked: What are the data? What is the utility of sharing or releasing data, and to whom? Who invests the resources in releasing those data and in making them useful to others? When, how, why, and how often are those data reused? Who benefits from what kinds of data transfer, when, and how? What resources must potential re-users invest in discovering, interpreting, processing, and analyzing data to make them reusable? Which data are most important to release, when, by what criteria, to whom, and why? What investments must be made in knowledge infrastructures, including people, institutions, technologies, and repositories, to sustain access to data that are released? Who will make those investments, and for whose benefit?
Only when these questions are addressed by scientists, scholars, data professionals, librarians, archivists, funding agencies, repositories, publishers, policy makers, and other stakeholders in research will satisfactory answers arise to the problems of data sharing…(More)”.
US government and private sector developing ‘precrime’ system to anticipate cyber-attacks
Martin Anderson at The Stack: “The USA’s Office of the Director of National Intelligence (ODNI) is soliciting the involvement of the private and academic sectors in developing a new ‘precrime’ computer system capable of predicting cyber-incursions before they happen, based on the processing of ‘massive data streams from diverse data sets’ – including social media and possibly deanonymised Bitcoin transactions….
At its core the predictive technologies to be developed in association with the private sector and academia over 3-5 years are charged with the mission ‘to invest in high-risk/high-payoff research that has the potential to provide the U.S. with an overwhelming intelligence advantage over our future adversaries’.
The R&D program is intended to generate completely automated, human-free prediction systems for four categories of event: unauthorised access, Denial of Service (DoS), malicious code and scans and probes which are seeking access to systems.
The CAUSE project is an unclassified program, and participating companies and organisations will not be granted access to NSA intercepts. The scope of the project, in any case, seems focused on the analysis of publicly available Big Data, including web searches, social media exchanges and trawling ungovernable avalanches of information in which clues to future maleficent actions are believed to be discernible.
Program manager Robert Rahmer says: “It is anticipated that teams will be multidisciplinary and might include computer scientists, data scientists, social and behavioral scientists, mathematicians, statisticians, content extraction experts, information theorists, and cyber-security subject matter experts having applied experience with cyber capabilities,”
Battelle, one of the concerns interested in participating in CAUSE, is interested in employing Hadoop and Apache Spark as an approach to the data mountain, and includes in its preliminary proposal an intent to ‘de-anonymize Bitcoin sale/purchase activity to capture communication exchanges more accurately within threat-actor forums…’.
Identifying and categorising quality signal in the ‘white noise’ of Big Data is a central plank in CAUSE, and IARPA maintains several offices to deal with different aspects of it. Its pointedly-named ‘Office for Anticipating Surprise’ frames the CAUSE project best, since it initiated it. The OAS is occupied with ‘Detecting and forecasting the emergence of new technical capabilities’, ‘Early warning of social and economic crises, disease outbreaks, insider threats, and cyber attacks’ and ‘Probabilistic forecasts of major geopolitical trends and rare events’.
Another concerned department is The Office of Incisive Analysis, which is attempting to break down the ‘data static’ problem into manageable mission stages:
1) Large data volumes and varieties – “Providing powerful new sources of information from massive, noisy data that currently overwhelm analysts”
2) Social-Cultural and Linguistic Factors – “Analyzing language and speech to produce insights into groups and organizations. “
3) Improving Analytic Processes – “Dramatic enhancements to the analytic process at the individual and group level. “
The Office of Smart Collection develops ‘new sensor and transmission technologies, with the seeking of ‘Innovative approaches to gain access to denied environments’ as part of its core mission, while the Office of Safe and Secure Operations concerns itself with ‘Revolutionary advances in science and engineering to solve problems intractable with today’s computers’.
The CAUSE program, which attracted 150 developers, organisations, academics and private companies to the initial event, will announce specific figures about funding later in the year, and practice ‘predictions’ from participants will begin in the summer, in an accelerating and stage-managed program over five years….(More)”
Open data could turn Europe’s digital desert into a digital rainforest
Joanna Roberts interviews Dirk Helbing, Professor of Computational Social Science at ETH Zurich at Horizon: “…If we want to be competitive, Europe needs to find its own way. How can we differentiate ourselves and make things better? I believe Europe should not engage in the locked data strategy that we see in all these huge IT giants. Instead, Europe should engage in open data, open innovation, and value-sensitive design, particularly approaches that support informational self-determination. So everyone can use this data, generate new kinds of data, and build applications on top. This is going to create ever more possibilities for everyone else, so in a sense that will turn a digital desert into a digital rainforest full of opportunities for everyone, with a rich information ecosystem.’…
The Internet of Things is the next big emerging information communication technology. It’s based on sensors. In smartphones there are about 15 sensors; for light, for noise, for location, for all sorts of things. You could also buy additional external sensors for humidity, for chemical substances and almost anything that comes to your mind. So basically this allows us to measure the environment and all the features of our physical, biological, economic, social and technological environment.
‘Imagine if there was one company in the world controlling all the sensors and collecting all the information. I think that might potentially be a dystopian surveillance nightmare, because you couldn’t take a single step or speak a single word without it being recorded. Therefore, if we want the Internet of Things to be consistent with a stable democracy then I believe we need to run it as a citizen web, which means to create and manage the planetary nervous system together. The citizens themselves would buy the sensors and activate them or not, would decide themselves what sensor data they would share with whom and for what purpose, so informational self-determination would be at the heart, and everyone would be in control of their own data.’….
A lot of exciting things will become possible. We would have a real-time picture of the world and we could use this data to be more aware of what the implications of our decisions and actions are. We could avoid mistakes and discover opportunities we would otherwise have missed. We will also be able to measure what’s going on in our society and economy and why. In this way, we will eventually identify the hidden forces that determine the success or failure of a company, of our economy or even our society….(More)”
The crowd-sourcing web project bringing amateur and professional archaeologists together
Sarah Jackson at Culture 24: “With only limited funds and time, professional archaeologists consistently struggle to protect and interpret the UK’s vast array of archaeological finds and resources. Yet there are huge pools of amateur groups and volunteers who are not only passionate but also skilled and knowledgeable about archaeology in the UK.
Now a new web platform called MicroPasts has been produced in a collaboration between University College London (UCL) and the British Museum to connect institutions and volunteers so that they can create, fund and work on archaeological projects together.
Work by UCL postdoctoral researchers Chiara Bonacchi and Adi Keinan-Schoonbaert and British Museum post doc researcher Jennifer Wexler established much of the ground work including the design, implementation and the public engagement aspects of the of the new site.
According to one of the project leaders, Professor Andrew Bevan at UCL, MicroPasts emerged from a desire to harness the expertise (and manpower) of volunteers and to “pull together crowd-sourcing and crowd-funding in a way that hadn’t been tried before”.
Although there are many crowd-sourcing portals online, they are either specific to one project (DigVentures, for example, which conducted the world’s first crowd-funded dig in 2012) or can be used to create almost anything you can imagine (such as Kickstarter).
MicroPasts was also inspired by Crowdcrafting, which encourages citizen science projects and, like MicroPasts, offers a platform for volunteers and researchers with an interest in a particular subject to come together to create and contribute to projects….(More)”