Paper by Mimi Recker, Min Yuan, and Lei Ye in the International Review of Research in Open and Distant Learning: “The widespread availability of high-quality Web-based content offers new potential for supporting teachers as designers of curricula and classroom activities. When coupled with a participatory Web culture and infrastructure, teachers can share their creations as well as leverage from the best that their peers have to offer to support a collective intelligence or crowdsourcing community, which we dub crowdteaching. We applied a collective intelligence framework to characterize crowdteaching in the context of a Web-based tool for teachers called the Instructional Architect (IA). The IA enables teachers to find, create, and share instructional activities (called IA projects) for their students using online learning resources. These IA projects can further be viewed, copied, or adapted by other IA users. This study examines the usage activities of two samples of teachers, and also analyzes the characteristics of a subset of their IA projects. Analyses of teacher activities suggest that they are engaging in crowdteaching processes. Teachers, on average, chose to share over half of their IA projects, and copied some directly from other IA projects. Thus, these teachers can be seen as both contributors to and consumers of crowdteaching processes. In addition, IA users preferred to view IA projects rather than to completely copy them. Finally, correlational results based on an analysis of the characteristics of IA projects suggest that several easily computed metrics (number of views, number of copies, and number of words in IA projects) can act as an indirect proxy of instructionally relevant indicators of the content of IA projects.”
Smartphone Movements Could Reveal Empty Parking Spots
Caleb Garling at MIT Technology Review: “Researchers have come up with a novel way to find parking spots with your smartphone. It promises to be much easier than driving around looking for an empty space, and doesn’t require the installation of pricey sensors or other methods for tracking available spots.
At the State University of New York at Buffalo, researchers built an app called PocketParker that does what they’re calling “pocketsourcing”—essentially, turning smartphones into passive sensors that track the location and movements of other users who’ve installed the app. A remote computer crunches the aggregate user actions and determines the likelihood that a lot has an open space. A paper about PocketParker will be presented at the ubiquitous computing conference UbiComp in Seattle next week.
While some parking lots employ sensors to gather information about capacity, PocketParker works without any such infrastructure. It pulls parking lot data from OpenStreetMap and calculates the number of spaces in a given lot based on its dimensions. During a study, researchers found that they could predict the number of spaces to within 6 percent of the actual number.
The app uses the smartphone’s accelerometer to determine where a user is and gauges whether he’s looking for a parking spot based on his movements. If a user drives slowly through a parking lot without stopping, that signals that the lot is full. If a user displays movements typical of walking and then suddenly speeds up and leaves the lot, that signifies that he likely just got into his car and drove away. The app calculates this in the background. “There should be no interaction required,” says SUNY Buffalo computer science professor and paper coauthor Geoffrey Challen….”
Citizen Science: The Law and Ethics of Public Access to Medical Big Data
New Paper by Sharona Hoffman: “Patient-related medical information is becoming increasingly available on the Internet, spurred by government open data policies and private sector data sharing initiatives. Websites such as HealthData.gov, GenBank, and PatientsLikeMe allow members of the public to access a wealth of health information. As the medical information terrain quickly changes, the legal system must not lag behind. This Article provides a base on which to build a coherent data policy. It canvasses emergent data troves and wrestles with their legal and ethical ramifications.
Publicly accessible medical data have the potential to yield numerous benefits, including scientific discoveries, cost savings, the development of patient support tools, healthcare quality improvement, greater government transparency, public education, and positive changes in healthcare policy. At the same time, the availability of electronic personal health information that can be mined by any Internet user raises concerns related to privacy, discrimination, erroneous research findings, and litigation. This Article analyzes the benefits and risks of health data sharing and proposes balanced legislative, regulatory, and policy modifications to guide data disclosure and use.”
Developing Public Policy To Advance The Use Of Big Data In Health Care
Paper by Axel Heitmueller et al in Health Affairs: “The vast amount of health data generated and stored around the world each day offers significant opportunities for advances such as the real-time tracking of diseases, predicting disease outbreaks, and developing health care that is truly personalized. However, capturing, analyzing, and sharing health data is difficult, expensive, and controversial. This article explores four central questions that policy makers should consider when developing public policy for the use of “big data” in health care. We discuss what aspects of big data are most relevant for health care and present a taxonomy of data types and levels of access. We suggest that successful policies require clear objectives and provide examples, discuss barriers to achieving policy objectives based on a recent policy experiment in the United Kingdom, and propose levers that policy makers should consider using to advance data sharing. We argue that the case for data sharing can be won only by providing real-life examples of the ways in which it can improve health care.”
Business Models for Open Innovation: Matching Heterogenous Open Innovation Strategies with Business Model Dimensions
New paper by Saebi, Tina and Foss, Nicolai, available at SSRN: “Research on open innovation suggests that companies benefit differentially from adopting open innovation strategies; however, it is unclear why this is so. One possible explanation is that companies’ business models are not attuned to open strategies. Accordingly, we propose a contingency model of open business models by systematically linking open innovation strategies to core business model dimensions, notably the content, structure, governance of transactions. We further illustrate a continuum of open innovativeness, differentiating between four types of open business models. We contribute to the open innovation literature by specifying the conditions under which business models are conducive to the success of open innovation strategies.”
The Crypto-democracy and the Trustworthy
New Paper by Sebastien Gambs, Samuel Ranellucci, and Alain Tapp: “In the current architecture of the Internet, there is a strong asymmetry in terms of power between the entities that gather and process personal data (e.g., major Internet companies, telecom operators, cloud providers, …) and the individuals from which this personal data is issued. In particular, individuals have no choice but to blindly trust that these entities will respect their privacy and protect their personal data. In this position paper, we address this issue by proposing an utopian crypto-democracy model based on existing scientific achievements from the field of cryptography. More precisely, our main objective is to show that cryptographic primitives, including in particular secure multiparty computation, offer a practical solution to protect privacy while minimizing the trust assumptions. In the crypto-democracy envisioned, individuals do not have to trust a single physical entity with their personal data but rather their data is distributed among several institutions. Together these institutions form a virtual entity called the Trustworthy that is responsible for the storage of this data but which can also compute on it (provided first that all the institutions agree on this). Finally, we also propose a realistic proof-of-concept of the Trustworthy, in which the roles of institutions are played by universities. This proof-of-concept would have an important impact in demonstrating the possibilities offered by the crypto-democracy paradigm.”
Bridging the Knowledge Gap: In Search of Expertise
New paper by Beth Simone Noveck, The GovLab, for Democracy: “In the early 2000s, the Air Force struggled with a problem: Pilots and civilians were dying because of unusual soil and dirt conditions in Afghanistan. The soil was getting into the rotors of the Sikorsky UH-60 helicopters and obscuring the view of its pilots—what the military calls a “brownout.” According to the Air Force’s senior design scientist, the manager tasked with solving the problem didn’t know where to turn quickly to get help. As it turns out, the man practically sitting across from him had nine years of experience flying these Black Hawk helicopters in the field, but the manager had no way of knowing that. Civil service titles such as director and assistant director reveal little about skills or experience.
In the fall of 2008, the Air Force sought to fill in these kinds of knowledge gaps. The Air Force Research Laboratory unveiled Aristotle, a searchable internal directory that integrated people’s credentials and experience from existing personnel systems, public databases, and users themselves, thus making it easy to discover quickly who knew and had done what. Near-term budgetary constraints killed Aristotle in 2013, but the project underscored a glaring need in the bureaucracy.
Aristotle was an attempt to solve a challenge faced by every agency and organization: quickly locating expertise to solve a problem. Prior to Aristotle, the DOD had no coordinated mechanism for identifying expertise across 200,000 of its employees. Dr. Alok Das, the senior scientist for design innovation tasked with implementing the system, explained, “We don’t know what we know.”
This is a common situation. The government currently has no systematic way of getting help from all those with relevant expertise, experience, and passion. For every success on Challenge.gov—the federal government’s platform where agencies post open calls to solve problems for a prize—there are a dozen open-call projects that never get seen by those who might have the insight or experience to help. This kind of crowdsourcing is still too ad hoc, infrequent, and unpredictable—in short, too unreliable—for the purposes of policy-making.
Which is why technologies like Aristotle are so exciting. Smart, searchable expert networks offer the potential to lower the costs and speed up the process of finding relevant expertise. Aristotle never reached this stage, but an ideal expert network is a directory capable of including not just experts within the government, but also outside citizens with specialized knowledge. This leads to a dual benefit: accelerating the path to innovative and effective solutions to hard problems while at the same time fostering greater citizen engagement.
Could such an expert-network platform revitalize the regulatory-review process? We might find out soon enough, thanks to the Food and Drug Administration…”
Bridging Distant Worlds: Innovation in the Civic Space
A digital white paper by Public Innovation: “In an increasingly complex world, today’s challenges are interconnected. Many have argued that our civic institutions are not equipped to respond with the same velocity at which technology is advancing other sectors of the economy. While this may, in fact, be a fair criticism of our electoral, fiscal, and policy structures, a new mindset is emerging at government’s service delivery layer.
Civic innovation offers a new approach to solving community problems that is emergent, generative, resilient, participatory, human-centered, and driven by a process of validated learning where core assumptions are tested quickly and iteratively – and lead to better solutions that are both impactful and durable. And perhaps most surprisingly, new markets are being created that enable creative problem solvers to sustain their social impact through activities that don’t rely on traditional models of grant funding.
While the Sacramento region is making significant progress in this space, our civic innovation and entrepreneurship ecosystem has yet to reach its full potential. The purpose of this white paper is to make the case for why now is the time for a Regional Civic Technology, Innovation and Entrepreneurship Agenda.
The paper concludes with a set of recommendations for collective action among the region’s public, private, nonprofit organizations, and, of course, our fellow citizens. Appendix A articulates this agenda in the form of a resolution to be adopted by as many cities and counties the region as possible.
A recurring theme in this paper is that technology is fundamentally changing the way humans interact with organizations and each other. In order for regional leaders and residents to be honest with ourselves, we must consciously choose whether or not we are going to raise our expectations and co-create a new civic experience.
Because the future is now and the opportunities are infinite…”
Agency Liability Stemming from Citizen-Generated Data
Paper by Bailey Smith for The Wilson Center’s Science and Technology Innovation Program: “New ways to gather data are on the rise. One of these ways is through citizen science. According to a new paper by Bailey Smith, JD, federal agencies can feel confident about using citizen science for a few reasons. First, the legal system provides significant protection from liability through the Federal Torts Claim Act (FTCA) and Administrative Procedures Act (APA). Second, training and technological innovation has made it easier for the non-scientist to collect high quality data.”
When Big Data Maps Your Safest, Shortest Walk Home
Sarah Laskow at NextCity: “Boston University and University of Pittsburgh researchers are trying to do the same thing that got the creators of the app SketchFactor into so much trouble over the summer. They’re trying to show people how to avoid dangerous spots on city streets while walking from one place to another.
“What we are interested in is finding paths that offer trade-offs between safety and distance,” Esther Galbrun, a postdoc at Boston University, recently said in New York at the 3rd International Workshop on Urban Computing, held in conjunction with KDD2014.
She was presenting, “Safe Navigation in Urban Environments,” which describes a set of algorithms that would give a person walking through a city options for getting from one place to another — the shortest path, the safest path and a number of alternatives that balanced between both factors. The paper takes existing algorithms, well defined in theory — nothing new or fancy, Galbrun says — and applies them to a problem that people face everyday.
Imagine, she suggests, that a person is standing at the Philadelphia Museum of Art, and he wants to walk home, to his place on Wharton Street. (Galbrun and her colleagues looked at Philadelphia and Chicago because those cities have made their crime data openly available.) The walk is about three miles away, and one option would be to take the shortest path back. But maybe he’s worried about safety. Maybe he’s willing to take a little bit of a longer walk if it means he has to worry less about crime. What route should he take then?
Services like Google Maps have excelled at finding the shortest, most direct routes from Point A to Point B. But, increasingly, urban computing is looking to capture other aspects of moving about a place. “Fast is only one option,” says co-author Konstantinos Pelechrinis. “There are noble objectives beyond the surface path that you can put inside this navigation problem.” You might look for the path that will burn the most calories; a Yahoo! lab has considered how to send people along the most scenic route.
But working on routes that do more than give simple directions can have its pitfalls. The SketchFactor app relies both on crime data, when it’s available, and crowdsourced comments to reveal potential trouble spots to users. When it was released this summer, tech reporters and other critics immediately started talking about how it could easily become a conduit for racism. (“Sketchy” is, after all, a very subjective measure.)
So far, though, the problem with the SketchFactor app is less that it offers racially skewed perspectives than that the information it does offer is pretty useless — if entertaining. A pinpoint marked “very sketchy” is just as likely to flag an incident like a Jewish man eating pork products or hipster kids making too much noise as it is to flag a mugging.
Here, then, is a clear example of how Big Data has an advantage over Big Anecdata. The SafePath set-up measures risk more objectively and elegantly. It pulls in openly available crime data and considers simple data like time, location and types of crime. While a crime occurs at a discrete point, the researchers wanted to estimate the risk of a crime on every street, at every point. So they use a mathematical tool that smooths out the crime data over the space of the city and allows them to measure the relative risk of witnessing a crime on every street segment in a city….”