On Thursday and Friday, we finished up research on Albany’s housing programs. These include the Community HOME Investment Program, the Tenant Based Rental Assistance Program, and others, which can be found here.
After we met with Dr. Asensio on Monday, we dove into the housing data with exploratory data analysis. The housing data records each housing project funded by HOME or Community Development Block Grants and the amount that was funded. First, we looked for identifiers in the dataset; these are attributes that uniquely describe each record. Later, we will use the identifiers to link across different datasets. We also found the range of dates, counted the number of observations, and checked that the data was formatted correctly. Ultimately, the data was relatively clean and comprehensive. We will perform the same review on the other datasets over the next few days.
In addition to performing some initial analysis on the data, we brainstormed some response variables to measure the success of the various housing programs. This would involve bringing outside data from organizations like the U.S. Census Bureau, the Centers for Disease Control and Prevention, and NeighborWorks America. Some measures could be median income, unemployment rate, property values, and percent homeownership.
Yesterday, we joined a group call with Albany’s Technology and Communications (TAC) Department and a support team from ESRI to discuss the construction of the ArcGIS Hub. In this call, TAC assigned us some tasks which aligned closely with our project’s goals in the near future. These include performing analytics on the housing and utilities data as well as review other GeoHubs to devise a design for Albany’s ArcGIS Hub. Some examples of other GeoHubs we’re looking at are here and here.
Before we start developing the ArcGIS Hub, we must first build a database to house all necessary datasets such as that for housing, utilities, and weather. We’ll have a lot to do in the next week, like finding linkages across the datasets and looking into different database frameworks. We also plan to investigate Albany spatially, visualizing income level, political boundaries, and the distribution of projects across these boundaries. By our next meeting, we will determine which success measures are possible to calculate and decide on a linking strategy.