Stefaan Verhulst

Report by Liat Racin and Eric Gordon: “It’s widely accepted that community-academic collaborations have the potential to involve more of the people and places that a community values as well as address the concerns of the very constituents that community-based organizations care for. Just how to involve them and ensure their benefit remains highly controversial in the digital age. This report provides an overview of the concerns, values, and the roles of digital data and communications in community-academic research partnerships from the perspectives of Community Partner Organizations (CPOs) in Boston, Massachusetts. It can serve as a resource for researchers and academic organizations seeking to better understand the position and sentiments of their community partners, and ways in which to utilize digital technology to address conflicting notions on what defines ‘good’ research as well as the power imbalances that may exist between all involved participants. As research involves community members and agencies more closely, it’s commonly assumed that the likelihood of CPOs accepting and endorsing a projects’ or programs’ outcomes increases if they perceive that the research itself is credible and has direct beneficial application.

Our research is informed by informal discussions with participants of events and workshops organized by both the Boston Civic Media Consortium and the Engagement Lab at Emerson College between 2015-2016. These events are free to the public and were attended by both CPOs and academics from various fields and interest positions. We also conducted interviews with 20 CPO representatives in the Greater Boston region who were currently or had recently engaged in academic research partnerships. These representatives presented a diverse mix of experiences and were not disproportionately associated with any one community issue. The interview protocol consisted of 15 questions that explored issues related to the benefits, challenges, structure and outcomes of their academic collaborations. It also included questions about the nature and processes of data management. Our goal was to uncover patterns of belief in the roles, values, and concerns of CPO representatives in partnerships, focusing on how they understand and assign value to digital data and technology.

Unfortunately, the growing use and dependence on digital tools and technology in our modern-day research context has failed to inspire in-depth analysis on the influences of ‘the digital’ in community-engaged social research, such as how data is produced, used, and disseminated by community members and agencies. This gap exists despite the growing proliferation of digital technologies and born-digital data in the work of both social researchers and community groups (Wright, 2005; Thompson et al., 2003; Walther and Boyd 2002). To address this gap and identify the discourses about what defines ‘good’ research processes, we ask: “To what extent do community-academic partnerships meet the expectations of community groups?” And, “what are the main challenges of CPO representatives when they collaboratively generate and exchange knowledge with particular regard to the design, access and (re)use of digital data?”…(More)”.

Lisa M. Federer et al at PLOS One: “A number of publishers and funders, including PLOS, have recently adopted policies requiring researchers to share the data underlying their results and publications. Such policies help increase the reproducibility of the published literature, as well as make a larger body of data available for reuse and re-analysis. In this study, we evaluate the extent to which authors have complied with this policy by analyzing Data Availability Statements from 47,593 papers published in PLOS ONE between March 2014 (when the policy went into effect) and May 2016. Our analysis shows that compliance with the policy has increased, with a significant decline over time in papers that did not include a Data Availability Statement. However, only about 20% of statements indicate that data are deposited in a repository, which the PLOS policy states is the preferred method. More commonly, authors state that their data are in the paper itself or in the supplemental information, though it is unclear whether these data meet the level of sharing required in the PLOS policy. These findings suggest that additional review of Data Availability Statements or more stringent policies may be needed to increase data sharing….(More)”.

Blog by Hamed Alemohammad: “Advances in sensor technology, cloud computing, and machine learning (ML) continue to converge to accelerate innovation in the field of remote sensing. However, fundamental tools and technologies still need to be developed to drive further breakthroughs and to ensure that the Global Development Community (GDC) reaps the same benefits that the commercial marketplace is experiencing. This process requires us to take a collaborative approach.

Data collaborative innovation — that is, a group of actors from different data domains working together toward common goals — might hold the key to finding solutions for some of the global challenges that the world faces. That is why Radiant.Earth is investing in new technologies such as Cloud Optimized GeoTiffs, Spatial Temporal Asset Catalogues (STAC), and ML. Our approach to advance ML for global development begins with creating open libraries of labeled images and algorithms. This initiative and others require — and, in fact, will thrive as a result of — using a data collaborative approach.

“Data is only as valuable as the decisions it enables.”

This quote by Ion Stoica, professor of computer science at the University of California, Berkeley, may best describe the challenge facing those of us who work with geospatial information:

How can we extract greater insights and value from the unending tsunami of data that is before us, allowing for more informed and timely decision making?…(More).

Paper by Simon Forge for the European Parliament Think Tank: “Data is not static in a personal/non-personal classification – with modern analytic methods, certain non-personal data can help to generate personal data – so the distinction may become blurred. Thus, de-anonymisation techniques with advances in artificial intelligence (AI) and manipulation of large datasets will become a major issue. In some new applications, such as smart cities and connected cars, the enormous volumes of data gathered may be used for personal information as well as for non-personal functions, so such data may cross over from the technical and non-personal into the personal domain. A debate is taking place on whether current EU restrictions on confidentiality of personal private information should be relaxed so as to include personal information in free and open data flows. However, it is unlikely that a loosening of such rules will be positive for the growth of open data. Public distrust of open data flows may be exacerbated because of fears of potential commercial misuse of such data, as well of leakages, cyberattacks, and so on. The proposed recommendations are: to promote the use of open data licences to build trust and openness, promote sharing of private enterprises’ data within vertical sectors and across sectors to increase the volume of open data through incentive programmes, support testing for contamination of open data mixed with personal data to ensure open data is scrubbed clean – and so reinforce public confidence, ensure anti-competitive behaviour does not compromise the open data initiative….(More)”.

The Economist: “Quayside, an area of flood-prone land stretching for 12 acres (4.8 hectares) on Toronto’s eastern waterfront, is home to a vast, pothole-filled parking lot, low-slung buildings and huge soyabean silos—a crumbling vestige of the area’s bygone days as an industrial port. Many consider it an eyesore but for Sidewalk Labs, an “urban innovation” subsidiary of Google’s parent company, Alphabet, it is an ideal location for the world’s “first neighbourhood built from the internet up”.

Sidewalk Labs is working in partnership with Waterfront Toronto, an agency representing the federal, provincial and municipal governments that is responsible for developing the area, on a $50m project to overhaul Quayside. It aims to make it a “platform” for testing how emerging technologies might ameliorate urban problems such as pollution, traffic jams and a lack of affordable housing. Its innovations could be rolled out across an 800-acre expanse of the waterfront—an area as large as Venice.

Sidewalk Labs is planning pilot projects across Toronto this summer to test some of the technologies it hopes to employ at Quayside; this is partly to reassure residents. If its detailed plan is approved later this year (by Waterfront Toronto and also by various city authorities), it could start work at Quayside in 2020.

That proposal contains ideas ranging from the familiar to the revolutionary. There will be robots delivering packages and hauling away rubbish via underground tunnels; a thermal energy grid that does not rely on fossil fuels; modular buildings that can shift from residential to retail use; adaptive traffic lights; and snow-melting sidewalks. Private cars are banned; a fleet of self-driving shuttles and robotaxis would roam freely. Google’s Canadian headquarters would relocate there.

Undergirding Quayside would be a “digital layer” with sensors tracking, monitoring and capturing everything from how park benches are used to levels of noise to water use by lavatories. Sidewalk Labs says that collecting, aggregating and analysing such volumes of data will make Quayside efficient, liveable and sustainable. Data would also be fed into a public platform through which residents could, for example, allow maintenance staff into their homes while they are at work.

Similar “smart city” projects, such as Masdar in the United Arab Emirates or South Korea’s Songdo, have spawned lots of hype but are not seen as big successes. Many experience delays because of shifting political and financial winds, or because those overseeing their construction fail to engage locals in the design of communities, says Deland Chan, an expert on smart cities at Stanford University. Dan Doctoroff, the head of Sidewalk Labs, who was deputy to Michael Bloomberg when the latter was mayor of New York City, says that most projects flop because they fail to cross what he terms “the urbanist-technologist divide”.

That divide, between tech types and city-planning specialists, will also need to be bridged before Sidewalk Labs can stick a shovel in the soggy ground at Quayside. Critics of the project worry that in a quest to become a global tech hub, Toronto’s politicians may give it too much freedom. Sidewalk Labs’s proposal notes that the project needs “substantial forbearances from existing [city] laws and regulations”….(More)”.

Benjamin Y. Clark and Jeffrey L. Brudney in Computer Supported Cooperative Work (CSCW): “This article examines the citizen representativeness of crowdsourcing achieved through 311 systems—the non-emergency and quality of life service request reporting systems used by local governments. Based on surveys of San Francisco residents conducted in 2011, 2013, and 2015, our findings suggest that no systematic biases exist in participation rates across a range of socio-economic indicators. In addition, the findings provide evidence that participation may be responding positively to the city’s responsiveness, thus creating a self-reinforcing process that benefits an increasingly diverse and representative body of users. This inquiry builds on earlier studies of Boston and San Francisco that show that 311 systems did not bias response to traditionally disadvantaged groups (lower socioeconomic status or racial/ethnic minorities) at the demand level nor from high-volume users….(More)”.

Paper by Krithika Randhawa, Ralf Wilden Macquarie and Joel West: “Despite the increased research attention on crowdsourcing, we know little about why and how seeker organizations use this open innovation mechanism. Furthermore, previous studies have focused on profit-seeking firms, despite the use of open innovation practices by public sector organizations to achieve societal benefits. In this study, we investigate the organizational and project level choices of government (seekers) that crowdsource from citizens (solvers) to drive open social innovation, and thus develop new ways to address societal problems, a process referred to as “citizensourcing”.

Using a dataset of 18 local government seekers that use the same intermediary to conduct more than 2,000 crowdsourcing projects, we develop a model of seeker crowdsourcing implementation that links a previously-unstudied variance in seeker intent and engagement strategies, at the organizational level, to differences in project team motivation and capabilities, in turn leading to varying online engagement behaviors and ultimately project outcomes. Comparing and contrasting governmental with the more familiar corporate context, we further find that the non-pecuniary orientation of both seekers and solvers means that the motives of government crowdsourcing differ fundamentally from corporate crowdsourcing, but that the process more closely resembles a corporate-sponsored community rather than government-sponsored contests. More broadly, we offer insights on how seeker organizational factors and choices shape project-level implementation and success of crowdsourcing efforts, as well as suggest implications for open innovation activities of other smaller, geographicallybound organizations….(More)”.