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Tech Helps Planners Weigh Development, Historic Preservation - Vimarsana News

Tech Helps Planners Weigh Development, Historic Preservation

Tech Helps Planners Weigh Development, Historic Preservation A University of Pennsylvania project aims to make it easier for city planners to gauge resident preference for preserving historic homes against municipal needs for higher-density housing. May 28, 2021 •  Shutterstock/Spiroview Inc MetroLab Network has partnered with Government Technology  to bring its readers a segment called the MetroLab Innovation of the Month Series, which highlights impactful tech, data and innovation projects underway between cities and universities. If you’d like to learn more or contact the project...

How has COVID-19 changed 'superstar cities'? - Vimarsana News

How has COVID-19 changed 'superstar cities'?

How has COVID-19 changed ‘superstar cities’? A new analysis found that overall mobility in large U.S. cities has yet to return to pre-pandemic levels, and some are also experiencing changing segregation patterns, with potential implications that could last well beyond the pandemic. A new study, recently presented at the GISRUK conference, found that overall mobility in large U.S. cities has yet to return to pre-pandemic levels. Using tools from geographic information system (GIS) analysis and data science, geospatial researc...

Source: upenn.edu
Metro21 Lunch and Learn: Public Policy Analytics: Code and Context for Data Science in Government - Metro21: Smart Cities Institute - Vimarsana News

Metro21 Lunch and Learn: Public Policy Analytics: Code and Context for Data Science in Government - Metro21: Smart Cities Institute

Metro21 Lunch and Learn: Public Policy Analytics: Code and Context for Data Science in Government Postponed until a later date. Join Metro21 as we hear Dr. Ken Steif discuss his project, "Public Policy Analytics: Code & Context for Data Science in Government."   How do algorithms in government differ from business? In business, revenue is the only relevant bottom line, but in government algorithms must optimize for several disparate bottom lines like equity, fairness, bureaucracy, politics and more. In his new book, 'Public Policy Analytics: Code & Context for Data Science in Government', D...

Source: cmu.edu