By Data-Smart City Solutions • March 31, 2017

Each week we will bring you a summary of what happened this week on our site, on Twitter, and in the wider world of civic data. Suggest stories on Twitter with #ThisWeekInData.

Here on Data-Smart, Stephen Goldsmith wrote a brief highlighting What Works Cities’ new Certification program, which recognizes cities with high-performing data programs with the goal of sharing best practices. Certification measures city performance in open data, data governance, performance analytics, low-cost evaluations, results-driven contracting, and repurposing for results; examples of best practices include Seattle in open data policy, Boston in results-driven policy, and Washington D.C. in low-cost evaluations. Goldsmith also wrote a post for Better, Faster, Cheaper outlining the program.

Also on Data-Smart, Chris Bousquet examined ethical considerations around the government practice of nudging—using insights from behavioral science to promote preferable behaviors. While nudging has the potential to produce tremendous value for governments, some object to the practice on the basis that it violates citizens’ autonomy or falls outside government’s proper responsibilities. However, Bousquet argues that nudging is neither in principle ethical nor unethical, but that whether individual nudges are ethical hinges on their transparency, ability to withstand public scrutiny, and coherence with public values.

We also posted Stephen Goldsmith’s keynote address at Joint Venture Silicon Valley’s 2017 State of the Valley conference, an annual town meeting where stakeholders discuss challenges and opportunities in the Valley. Goldsmith discussed how technology is changing the way policymakers think about governance, offering a model of distributed governance, which leverages technology to empower citizens.

Route Fifty discussed the use of predictive policing to combat violent gun crimes in Stockton, CA. In 2014, the city launched a model that analyzes data on non-domestic violence-related gun crimes to identify trends and flag forecast zones where incidents are likely to occur. The police department began deploying resources to these zones in increasing numbers, and preliminary numbers for March through May 2016 shows 40 to 60 percent month-to-month decreases in non-domestic gun violence-related crimes in forecast zones. 

GovTech identified Syracuse, NY’s efforts to drive innovation through strategic partnerships with What Works Cities and others as a model for small and midsized cities to achieve data excellence.  Through What Works Cities, Syracuse has partnered with the Center for Government Excellence at Johns Hopkins University and the Sunlight Foundation to improve its performance management and open data practices. The city also partnered with Bloomberg Philanthropies to create an innovation team to reform its infrastructure. Key to Syracuse’s success has been its ability to leverage the network provided by What Works Cities and adopt solutions that have worked in other cities.

GovTech also profiled San Diego’s initiative to deploy 3,200 multi-sensor pods across the city, the largest pod deployment in the U.S. to date. These pods will listen for gunshots, observe traffic, and monitor air temperature, producing anonymous data that the city hopes to push out to developers and use itself to inform parking reforms, traffic regulations, and pedestrian safety initiatives.

Harvard Business Review examined the use of digital technologies and data analytics to improve leak detection in water infrastructure. The world loses 25-35 percent of water due to leaks and bursts, but predictive models and systems of water main sensors can help predict and prevent breaks before they happen. However, implementing such initiatives requires emphasizing potential monetary and social benefits to stakeholders and reforming processes to meet the requirements of advanced analytics.  

Harvard announced a new Data Science Initiative, a University-wide program that will teach students to use statistics and computer science to extract knowledge from complex and messy information sources. The program hopes to encourage cross-disciplinary collaboration, embedding principles of data science in departments ranging from public health to government and even art.