Getting a better approximation of the age of a NYC’s building can improve assigning the building to a structural type that includes type of construction and relevant building code in effect. Mapping the age and type of building would help NYC DOB and the City on a number of fronts, which include enabling NYC DOB to be more effective in enforcing building and construction safety and evaluating risk when adjacent or nearby subsurface construction is proposed. Furthermore, the more precise characterization of NYC buildings will improve efforts by the City to craft policies aimed at energy efficiency (TWG) as it drives to 80% GHG reductions by 2050 (80X50) and determining natural disaster vulnerability of its building stock (HAZUS).

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The State regulates Construction and Demolition Waste (CDW) — its generation, recycling and reuse — and collects all data on CDW. There is no city source of data for CDW. For the city to innovate policy with respect to CDW by leveraging its capital program as one way to close material loops, which would generate environmental sustainability and financial sustainability benefits, understanding where CDW goes from the demolition process through the recycling process is the most important single step.

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In collaboration with DDC, Microsoft AI team has developed a predictive machine learning model that forecasts monthly distribution of cash flow for DDC’s active projects. DDC intends to operationalize this model and possibly integrate into our dashboards. Assistance is needed of a data scientist to collaborate with DDC in operationalizing the model whereby DDC can prepare the visuals and data scientist can assist with operationalizing the machine learning components.

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Rights CoLab is working with the Sustainability Accounting Standards Board (SASB) to develop and define a strengthened set of disclosure standards that investors can use to persuade companies to improve labor rights for both direct employees and workers in their supply chains. The project has two components: a data science project and an Independent Advisory Group. Our coalition of labor experts, data scientists, and SASB partners is focused on improving social disclosure standards that drive real gains in human rights.

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DEP uses near real-time water quality data to guide its operations (i.e., the selection and routing of water) to achieve optimum quality for consumers. Historical data is used to evaluate the effectiveness of watershed protection programs, and model predictions of future water quality are used to understand potential impacts to the water supply under different infrastructure and climate scenarios.

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Under United States securities laws corporations must disclose material risks to their operations. Human rights issues, especially in authoritarian countries, rarely show up in the information that data providers offer to investors, in part due to the risks to those subject to these abuses. The result is a dearth of data on human rights materiality and the tendency of investors to overlook human rights risks of the companies that they finance.

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42% of New York City greenhouse gas emissions result from on-site fossil fuel combustion in residential and commercial buildings; space heating is, by far, the majority contributor. Both New York State and NYC have policies to dramatically reduce emissions that will require a transformation in the way buildings are heated, including major efforts in existing buildings. This transition is inextricably linked to existing energy equity issues that we believe significantly overlap across NYC (and elsewhere). These include unreliable heating in the winter, susceptibility to extreme heat (an increasing occurrence with climate change) and struggles to afford energy needs. Various known data sources for NYC are available, though they are disparate and have not been analyzed holistically. Further, we believe there are potential engineering and policy solutions to these challenges. In this project, the DSI scholar will access (and search for where not yet known to qSEL researchers) relevant data sets, analyze those data sets to identify communities exposed to all or a subset of these issues, and assist qSEL researchers in developing models to evaluate possible solutions. The project has the possibility of extending through Summer 2020, subject to fundraising efforts and the success of the Spring 2020 project.

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