NY Health Centers and Assessments actions – Map Visualization


Visualization

Introduction.

The project centered around creating a visualisation project in Carto. The data for the project was retrieved from the carto platform and NYC.gov website. The data used was on NY Health Centers and Assessments actions. Actions on Applications in 2016 Reducing Assessments or Reclassifying Property. Listed here are Tax Commission actions during 2016 reducing assessments or reclassifying property. (NYC.gov, 2017) Though the assessment action data was reduced to get only a general overview, the idea was to see what areas of New York health center coincided with these assessment imposed on top of them and how that could be reflected in a spatial join of some sort.

 

Visualizations that inform/inspired the design.

The existing visualizations that inspired this map had to deal with areas impacted by income disparity in NYC. While the final map visualization for this project is not about income disparity, it was this idea of areas of higher income and value that helped raise curiosity and guide the direction this project would take. 

 

One of the amazing things that is becoming more popular in our society and with technological advancements is the way in real time a visualization can clearly reveal information of such nature simply based on dataset input to a visualization program.

Materials used in lab.

The materials used in the lab were the Carto platform, and the NYHealthCenter file already in Carto as a shapefile as well as the  the data for the Assessment actions that was downloaded as csv files from NYC.gov and imported into Carto. The NY HealthCenter shapefile dataset contained the number of health centers district, borocode, boronames, data on shape area and shape length. The data for the assessment action contained a more robust set of rows and columns that were specifically edited for this project. It contained column, census tract, council district, community board, post year, granted reduction amount, property address and owner name to name a few of the columns that were in the data set. In understanding the importance of the assessment action, according to the Members of the Tax Commission in its annual report “Annual property tax assessments are the basis for the RPT levy, the City’s largest single source of revenue. There are over one million parcels of real property in the City generally identified by the borough, block and lot number on the tax maps maintained by the Department of Finance. Each year the Department of Finance sets tentative assessed values, which are reflected on the tentative assessment roll it publishes in January for the fiscal year beginning the following July 1.”(Annual report, 2016)

Methods used to create visualization.

To create the map visualization, once the data had been imported, the base map was selected. Carto  provides a wide array of designed maps different in colors and design styles. Positron  a cleaner map that has a light color not too strong or heavy to the eyes was selected. It was important to select a map that would afford an easy progression to the other elements like color and point shapes that would later be added to the visualization. Next the NY Health Center file was clicked and opened up on the map. Under Analysis in the Carto interface the assessment file was selected and then due to the nature of the data “Count” was selected to aggregate the data. Once the data was aggregated a suitable color was selected to help reflect the weighted distribution of the areas. Once this was complete, the assessment action file was then selected and a cluster was run on the data. The Pop-up information box was populated with information that was intended to be reflected on each point selected.  The hexagon shaped points was selected to reflect the assessment actions at specific locations to give a better flow to the information plotted in the map.

 

Results of visualizations.

The Spatial joint analysis of the NY Health Centers and the Assessment actions have no correlation in actual reality besides same area or location being New York. In general the intention was to see what areas were overlapped and to see if any insights could be observed or inferred from what was plotted. However the data NY Health Center was only intended for informational purposes only and the source did not warrant the completeness or accuracy of the data for other uses. As mentioned earlier,to help understand the context of the role Assessment actions in NYC and how they are designated, further research was made. On page 3 of the report, “State law divides all real property in the City into four classes for purposes of taxation. Class one includes one-, two- and three-family homes, most residentially-zoned vacant land outside Manhattan and certain condominiums of up to three stories.3 Class two consists of all primarily residential property not in class one. Utility company equipment is in class three. All other nonresidential property is in class four” (Annual report, 2016)

 

 

Assessment actions play an important role in revealing the amount of the grant reduction awarded to the property which is important to owners.  While a property’s assessed value is a function of that property’s tax class designation, market value, assessment ratio and eligibility for exemption (Annual report, 2016) .  There was a curiosity to see if the areas of NY Health centers possibly had an affect on these assessment valuations. In the Visualization, the areas with the darker shades of color reflect areas with hire reduction grants.

 

However not to make any conclusions from the visualizations, it was noticed that areas of hire assessment actions did have higher concentrations of Health Centers, needles to say this correlation is not inferring causation from neither data sources. But such insights are what make visualizations interesting.

Future directions.

It will be interesting to further explore if in reality there is a correlation of some sort between the assessment action zoned buildings and NY Health centers. It is circumstances like these that make data visualization such a powerful tool. By comparing data sets and having the data itself speak to the situations

 

Reference

http://www.nyc.gov/html/taxcomm/downloads/pdf/annual_report.pdf

http://www1.nyc.gov/assets/planning/download/pdf/data-maps/open-data/nyhc_metadata.pdf?ver=17c