Stefaan Verhulst

Blog by Stefaan G. Verhulst, IrynaSusha and Alexander Kostura: “Data Collaboratives refer to a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors (private companies, research institutions, and government agencies) share data to help solve public problems. Several of society’s greatest challenges — from climate change to poverty — require greater access to big (but not always open) data sets, more cross-sector collaboration, and increased capacity for data analysis. Participants at the workshop and breakout session explored the various ways in which data collaborative can help meet these needs.

Matching supply and demand of data emerged as one of the most important and overarching issues facing the big and open data communities. Participants agreed that more experimentation is needed so that new, innovative and more successful models of data sharing can be identified.

How to discover and enable such models? When asked how the international community might foster greater experimentation, participants indicated the need to develop the following:

· A responsible data framework that serves to build trust in sharing data would be based upon existing frameworks but also accommodates emerging technologies and practices. It would also need to be sensitive to public opinion and perception.

· Increased insight into different business models that may facilitate the sharing of data. As experimentation continues, the data community should map emerging practices and models of sharing so that successful cases can be replicated.

· Capacity to tap into the potential value of data. On the demand side,capacity refers to the ability to pose good questions, understand current data limitations, and seek new data sets responsibly. On the supply side, this means seeking shared value in collaboration, thinking creatively about public use of private data, and establishing norms of responsibility around security, privacy, and anonymity.

· Transparent stock of available data supply, including an inventory of what corporate data exist that can match multiple demands and that is shared through established networks and new collaborative institutional structures.

· Mapping emerging practices and models of sharing. Corporate data offers value not only for humanitarian action (which was a particular focus at the conference) but also for a variety of other domains, including science,agriculture, health care, urban development, environment, media and arts,and others. Gaining insight in the practices that emerge across sectors could broaden the spectrum of what is feasible and how.

In general, it was felt that understanding the business models underlying data collaboratives is of utmost importance in order to achieve win-win outcomes for both private and public sector players. Moreover, issues of public perception and trust were raised as important concerns of government organizations participating in data collaboratives….(More)”

Mark Gorenberg, Craig Mundie, Eric Schmidt and Marjory Blumenthal at PCAST: “Growing urbanization presents the United States with an opportunity to showcase its innovation strength, grow its exports, and help to improve citizens’ lives – all at once. Seizing this triple opportunity will involve a concerted effort to develop and apply new technologies to enhance the way cities work for the people who live there.

A new report released today by the President’s Council of Advisors on Science and Technology (PCAST), Technology and the Future of Cities, lays out why now is a good time to promote technologies for cities: more (and more diverse) people are living in cities; people are increasingly open to different ways of using space, living, working, and traveling across town; physical infrastructures for transportation, energy, and water are aging; and a wide range of innovations are in reach that can yield better infrastructures and help in the design and operation of city services.

There are also new ways to collect and use information to design and operate systems and services. Better use of information can help make the most of limited resources – whether city budgets or citizens’ time – and help make sure that the neediest as well as the affluent benefit from new technology.

Although the vision of technology’s promise applies city-wide, PCAST suggests that a practical way for cities to adopt infrastructural and other innovation is by starting in a discrete area  – a district, the dimensions of which depend on the innovation in question. Experiences in districts can help inform decisions elsewhere in a given city – and in other cities. PCAST urges broader sharing of information about, and tools for, innovation in cities.

Such sharing is already happening in isolated pockets focused on either specific kinds of information or recipients of specific kinds of funding. A more comprehensive City Web, achieved through broader interconnection, could inform and impel urban innovation. A systematic approach to developing open-data resources for cities is recommended, too.

PCAST recommends a variety of steps to make the most of the Federal Government’s engagement with cities. To begin, it calls for more – and more effective – coordination among Federal agencies that are key to infrastructural investments in cities.  Coordination across agencies, of course, is the key to place-based policy. Building on the White House Smart Cities Initiative, which promotes not only R&D but also deployment of IT-based approaches to help cities solve challenges, PCAST also calls for expanding research and development coordination to include the physical, infrastructural technologies that are so fundamental to city services.

A new era of city design and city life is emerging. If the United States steers Federal investments in cities in ways that foster innovation, the impacts can be substantial. The rest of the world has also seen the potential, with numerous cities showcasing different approaches to innovation. The time to aim for leadership in urban technologies and urban science is now….(More)”

Report by Nicholas Robin, Thilo Klein and Johannes Jütting for Paris 21: “Non-offcial sources of data, big data in particular, are currently attracting enormous interest in the world of official statistics. An impressive body of work focuses on how different types of big data (telecom data, social media, sensors, etc.) can be used to fll specifc data gaps, especially with regard to the post-2015 agenda and the associated technology challenges. The focus of this paper is on a different aspect, but one that is of crucial importance: what are the perspectives of the commercial operations and national statistical offces which respectively produce and might use this data and which incentives, business models and protocols are needed in order to leverage non-offcial data sources within the offcial statistics community?

Public-private partnerships (PPPs) offer signifcant opportunities such as cost effectiveness, timeliness, granularity, new indicators, but also present a range of challenges that need to be surmounted. These comprise technical diffculties, risks related to data confdentiality as well as a lack of incentives. Nevertheless, a number of collaborative projects have already emerged and can be

Nevertheless, a number of collaborative projects have already emerged and can be classified into four ideal types: namely the in-house production of statistics by the data provider, the transfer of private data sets to the end user, the transfer of private data sets to a trusted third party for processing and/or analysis, and the outsourcing of national statistical office functions (the only model which is not centred around a data-sharing dimension). In developing countries, a severe lack of resources and particular statistical needs (to adopt a system-wide approach within national statistical systems and fill statistical gaps which are relevant to national development plans) highlight the importance of harnessing the private sector’s resources and point to the most holistic models (in-house and third party) in which the private sector contributes to the processing and analysis of data. The following key lessons are drawn from four case studies….(More)”

Springwise: “Every year in Switzerland, emergency centers respond to around 1,000 call outs for lost and injured hikers. It can often take hours and significant manpower to locate lost mountaineers, but new software for quadcopter drones is making the hunt quicker and easier, and has the potential to help find human survivors in disaster zones around the world.

The drone uses a computer algorithm called a Deep Neural Network. The program was developed by researchers at the University of Zurich and the Dalle Molle Institute for Artificial Intelligence. The drone uses the algorithm to learn trails and paths through a pair of small cameras, interpreting the images and recognizing man-made pathways. Even when working on a previously unseen trail, it was able to guess the correct direction in 85 percent of the cases. The drones’ speed and accuracy make them more effective than human trackers.

The researchers hope that eventually multiple small drones could be combined with human search and rescue missions, to cover more terrain and find people faster. The drones can cover terrain quickly and check hazardous areas to minimize risk to human workers, and its AI can identify paths and avoid crashing without any human involvement….(More)”

Kristin Finklea at the Congressional Research Service: “Because modern-day criminals are constantly developing new tools and techniques to facilitate their illicit activities, law enforcement is challenged with leveraging its tools and authorities to keep pace. For instance, interconnectivity and technological innovation have not only fostered international business and communication, they have also helped criminals carry out their operations. At times, these same technological advances have presented unique hurdles for law enforcement and officials charged with combating malicious actors.

Technology as a barrier for law enforcement is by no means a new issue in U.S. policing. In the 1990s, for instance, there were concerns about digital and wireless communications potentially hampering law enforcement in carrying out court-authorized surveillance. To help combat these challenges, Congress passed the Communications Assistance for Law Enforcement Act (CALEA; P.L. 103-414), which among other things, required telecommunications carriers to assist law enforcement in executing authorized electronic surveillance.

The technology boundary has received renewed attention as companies have implemented advanced security for their products—particularly their mobile devices. In some cases, enhanced encryption measures have been put in place resulting in the fact that companies such as Apple and Google cannot unlock devices for anyone under any circumstances, not even law enforcement.

Law enforcement has concerns over certain technological changes, and there are fears that officials may be unable to keep pace with technological advances and conduct electronic surveillance if they cannot access certain information. Originally, the going dark debate centered on law enforcement’s ability to intercept real-time communications. More recent technology changes have potentially impacted law enforcement capabilities to access not only communications, but stored data as well….(More)”

Matt Haikin at Aptiva: “Last year, Aptivate led a consortium of researchers and practitioners to explore the role of technology in citizen-engagement and participation in the development sector, and how to evaluate the success of such activities…

The guide was researched, developed and written by the multidisciplinary team of Matt Haikin (Aptivate), Savita Bailur (now at Caribou Digital), Evangelia Berdou (IDS), Claudia Lopes (now at Africa’s Voices), Jonathan Dudding (ICA:UK) and Martin Belcher (now at Palladium Group).

The result – ‘Evaluating Digital Citizen Engagement: A practical guide’ will be published in electronic form on the World Bank’s Open Knowledge Repository any day now.

The Guide forms part of the recommended reading for the World Bank’s high profile Coursera course Citizen Engagement : A game changer for development? …So what can you expect to find in the Guide…

• Practical tools and guidelines for use in evaluating or designing activities in the expanding field of digital citizen engagement
• Resources for anyone seeking to better understand the role of digital technology in citizen engagement.
• Five ‘lenses’ you can use to explore different perspectives through which digital citizen engagement might be viewed (Objective, Control, Participation, Technology, Effects)Detailed advice and tips specific to technology and citizen engagement through every stage of a typical evaluation lifecycle (Scoping, Designing, Planning & Implementing, Analysing, Sharing, Reflecting & Learning)
• Toolkits to help you design your own research questions and evaluation designs …(More)”

Open Access Button: “Hidden data is hindering research, and we’re tired of it. Next week we’ll release the Open Data Button beta as part of Open Data Day. The Open Data Button will help people find, release, and share the data behind papers. We need your support to share, test, and improve the Open Data Button. Today, we’re going to provide some in depth info about the tool.

You’ll be able to download the free Open Data Button on the 29th of February. Follow the launch conversation on Twitter and at #opendatabutton.

How the Open Data Button works

You will be able to download the Open Data Button on Chrome, and later on Firefox. When you need the data supporting a paper (even if it’s behind a paywall), push the Button. If the data has already been made available through the Open Data Button, we’ll give you a link. If it hasn’t, you’ll be able to start a request for the data. Eventually, we want to search a variety of other sources for it – but can’t yet (read on, we need your help with that).

The request will be sent to the author. We know sharing data can be hard and there’s sometimes good reasons not to. The author will be able to respond to it by saying how long it’ll take to share the data – or if they can’t. If the data is already available, the author can simply share a URL to the dataset. If it isn’t, they can attach files to a response for us to make available. Files shared with us will be deposited in the Open Science Framework for identification and archiving. The Open Science Framework supports data sharing for all disciplines. As much metadata as possible will be obtained from the paper, the rest we’ll ask the author for.

The progress of this request is tracked through our new “request” pages. On request pages others can support a request and be sent a copy of the data when it’s available. We’ll map requests, and stories will be searchable – both will now be embeddable objects.

Once available, we’ll send data to people who’ve requested it. You can award an Open Data Badge to the author if there’s enough supporting information to reproduce the data’s results.

At first we’ll only have a Chrome add-on, but support for Firefox will be available from Firefox 46. Support for a bookmarklet will also be provided, but we don’t have a release date yet….(More)”

Kevin Ebi at Smart Cities Council: “Most cities and utilities want to get smarter. They see the smart cities movement as delivering more than some incremental improvement. They see it as a meaningful transformation — one that delivers far more than just some cost savings.

Despite all that, the latest Black & Veatch Strategic Directions: U.S. Smart City/Smart Utility Report finds they plan to move slower — not faster — to become smarter. But understanding the obstacles can help you overcome them.

First, the good news
Cities don’t need to be sold on the idea of becoming smarter. More than 90% see the smart cities movement as being transformational with long-term lasting impacts.

Nearly 80% believe it should start with initiatives that have lasting benefits — even if that work is largely behind the scenes (and therefore less likely for the public to notice.) A similar number also believe that data analytics will significantly improve decision making. And nearly all believe it’s a comprehensive effort; it’s more than just buying some new technology.

The smart cities revolution is also inclusive. More than three-quarters say that energy, water and telecommunications providers should play a leadership role in smart cities initiatives — they shouldn’t be relegated to a supporting role.

And growing numbers see smart cities initiatives as something more than just a vehicle to cut costs. This year, more respondents — cities leaders and utilities alike — see the potential to become more sustainable, better manage community resources and to attract business investment.

But there’s also room for improvement
Despite clearly understanding the value of smart cities initiatives, the survey finds respondents are losing faith the transition can happen quickly. Last year, the study found that nearly 1 in 5 thought the smart cities model would be widespread in American cities within the next five years. This year, not even 1 in 10 believe that timeline is achievable.

Instead, more than a third now believe the implementation could take a decade. Nearly a quarter believe it could take 15 years. More than 80% believe the U.S. is lagging the world in the smart cities revolution.

What’s holding them back
Part of the problem may be a big knowledge gap. While people responding to the survey say they understand the potential, more than half say their city still doesn’t understand what it means to be a “smart city.”

And while half the cities and utilities are assessing their readiness — a third are even working on roadmaps — nearly two-thirds still don’t understand where the payoff point is. That may be adding to the money woes….(More)”

Ziad Al Achkar, Isaac L. Baker, Nathaniel A. Raymond at Harvard Humanitarian Initiative: “At present, accepted methodologies for wind disaster damage assessments rely almost exclusively on responders having ground access to the affected area to document damage to housing structures.  This approach can prove both time consuming and inefficient, and does not support the use of drones and satellites.

Geospatially-based damage assessments offer potential improvements to this process in terms of providing responding agencies with previously unavailable information about hard to reach, often non-permissive environments, at a scale and speed not possible through ground-based counts of damaged structures.

This guide provides the first standard method for conducting these types of damage assessments through the analysis of drone and satellite imagery. The “BAR Methodology” has been developed by the Signal Program on Human Security and Technology at HHI to address this critical gap in this evolving area humanitarian practice….(More)”