Here on Data-Smart, Chris Bousquet examined efforts by state and local governments including New York City, Maryland, and New Mexico to use analytics to spot and prevent fraud. While all three of these governments track financial anomalies to identify fraud, New Mexico has also implemented behavioral interventions in the unemployment insurance application process that nudge residents likely to commit fraud. Lawmakers must be careful, however, to structure anti-fraud efforts in a way that benefits, rather than harms, residents that report honestly.

NYU’s Furman Center introduced New York City Neighborhood Data Profiles, a one-stop platform for viewing and downloading neighborhood housing and demographic data. The web platform provides an in-depth look at demographic, housing market, land use, and neighborhood services indicators for the city’s 59 Community Districts, which can be used to understand housing and demographic trends and inform policy conversations.

Also on the topic of New York City housing, the New York City Commission on Human Rights has partnered with city’s data analytics office to use open data to identify landlords who discriminate based on source of income. While it is illegal in New York to deny housing vouchers from potential tenants, many landlords do so anyway at the expense of poor or homeless New Yorkers. For this initiative, the Commission on Human Rights is using open data on crime, education, number of apartment buildings, and presence of voucher holders in order to target buildings with disproportionately low numbers of tenants using vouchers. Read more at Civicist.

In our latest installation of From Research to Results, Chris Bousquet analyzed Professor Hsiaoping Yeh’s paper “The effects of successful ICT-based city services: From citizens’ perspectives.” For the paper, the author surveyed Taiwanese residents to make an empirical case that tools like broadband networks and Internet of Things (IoT) sensors—referred to in academic literature as smart city information and communication technologies (ICTs)— improve quality of life for residents. The article therefore justifies cities’ implementation of such technologies, but also concludes that integrating residents’ needs and preferences into application development processes is critical to creating an effective smart city infrastructure.

NextCity profiled a new data visualization tool that presents a decade of Seattle Department of Transportation crash data and uses National Safety Council standards to put a price on total damages. That app depicts a map of crash locations, causes, severity, weather and road conditions, cost, and a number of other pieces of information. For example, the tool shows that in 2016, there were 13,622 traffic collisions in Seattle resulting in 3,885 injuries, 166 serious injuries and 23 fatalities, resulting in a total cost of $222,827,800.

Based on his experience with New York City’s BigApps competition, Stephen Goldsmith published an article in GovTech outlining six suggestions for rolling out engaging and productive civic tech competitions. Goldsmith’s proposals include defining a clear focus area, engaging with the civic tech community, inviting non-technical participants, making resulting products open source, supporting apps after the competition, and using competitions as recruiting tools.

The City of Louisville has released data from its AIR Louisville initiative, a two-year data-driven collaboration among public, private, and philanthropic organizations to use digital health technology to improve asthma. Participants saw an 82 percent reduction in asthma rescue inhaler use, twice the number of symptom-free days, and 14 percent increase in nights without symptoms. The program used Propeller Health’s medication inhaler sensors, which tracked when, where and how often residents of Louisville experienced asthma symptoms and alerted users when they should use their inhalers.

Harvard’s Civic Analytics Network will host a webinar, “The Power of Data Visualization in Cities,” on Thursday July 20th from 5pm to 6pm ET. The webinar will be moderated by Stephen Goldsmith, Director of CAN and the Innovations Program at the Harvard Kennedy School, and the presentation will highlight some of the best data visualization products created by city governments across the country. It will open to the public and available at this link. The meeting access code is 319-183-894 and the password is Mapping.

GCN reported that the New York City Police Department (NYPD) is having difficulties transferring data and analytics processes from a Palantir crime analysis platform to its new, home-grown Cobalt system. Since 2012, the NYPD has used a Palantir system that allows officers to upload arrest records, parking tickets, license plate scans and more and make connections between those data elements. So far, Palantir has not produced the full analysis in a format that would work with the new software despite multiple requests from NYPD, citing concerns with exposing its intellectual property.

The Association for Information Systems published a paper titled, “The Role of Open Data in Driving Sustainable Mobility in Smart Cities.” This report presents findings of a detailed analysis of mobility open data initiatives in nine smart cities – Amsterdam, Barcelona, Chicago, Dublin, Helsinki, London, Manchester, New York and San Francisco. The authors analyze the nature and availability of open mobility datasets and how they have fostered organic innovation and sustainable growth in smart cities, offering a model intended to inform the design of open data mobility projects

CityLab profiled Esri’s new ArcGIS Hub, an online platform that clusters datasets around specific citywide initiatives in the hope that people can more readily tap into information applicable to their lives. On the platform, users can track city progress on stated metrics, as well as mine full datasets available on the government’s portal.

Harvard Kennedy School discussed a paper written by a number of Harvard and MIT researchers that demonstrates how new computer vision technology can identify neighborhoods ripe for capital improvements. Using algorithms to analyze Google Street View images of more than 1.6 million street blocks in five U.S. cities, the research team was able to better understand the key demographic and economic characteristics common to neighborhoods that experience significant physical improvements over time. The study found that education, population, appearance, and proximity to a city center are all predictors of improvement.