I wanted to question cartoDB about the relationship(s), if any, between senior centers and the amount and types of outdoor activities set up by the NYC Housing Authority (NYCHA). My original plan was to map out the senior centers, noting those maintained by NYCHA, and determine if there are clusters of age-appropriate outdoor activities nearby. I expected that a correlation should exist between the neighborhoods surrounding senior centers and the quality of outdoor activities available to them.
This proved difficult to measure. The datasets on outdoor activities by NYCHA (in the year 2013, the latest data online) are not clearly marked in terms of the intended audience. Although NYCHA Citywide Special Events is a returned value when searching for datasets related to senior citizens, the actual spreadsheet includes seven senior appropriate events (out of 108 total) and of these seven events, three were indoor, three were outdoor and the seventh unspecified at the Brooklyn Museum. There was one occurrence of separate event hosted in celebration of Black History Month at an indoor senior center in Castle Hill, the Bronx. The Creative Arts Unit of the NYCHA Department of Citywide Programs was the sole producer of these events, suggesting focus on this unit may be valuable to senior advocates.
To further develop an understanding of where senior centers are located around the city, we applied the shapefiles for NYC health leveled under the point map of senior centers and then controlling for a heat map.
Of the three inspiring visualizations, the most ambitious and interesting is the NYCHenge, which I pulled on November 16th at http://nychenge.com/map.html#13/40.7347/-73.9957/11/16. This fascinating map, put together by the CartoDB team, allows you to see the relative location of sunset phenomena around the city on specific dates. If you know your city pretty well, you can dash away to have a look in person. The map has a zoom feature and lots of pretty red splats – to indicate the mini-henges. The team used OSM: Openstreetmap (free editable online world map) and SunCalc, also open source, along with JavaScript, their “vector rendering engine Mapnik” and CartoDB SQL API. https://cartodb.com/case-studies/nychenge/.
This map of Madrid’s subway complaints, https://congosto.cartodb.com/viz/e5da12e2-9fe7-11e4-bc43-0e853d047bba/public_map, has the exact color and style that makes a map useful. There is a coding legend at the bottom right that helps to find the cluster and locations of the ten or so common complaints. It gets a little difficult to read when multiple complaints occur at the same location, but the MTA could offer a map like this, particularly if riders can update in real time.
Third inspiration is from a selection of maps previously posted at the OpenEarth site run by a group of professional as a “free and open source initiative to deal with Data, Models and Tools in earth science & engineering projects.” The image below, is one of three outstanding uses of Google Earth posted here https://datavisualization.ch/tools/stunning-examples-of-data-visualization-in-google-earth/.

Materials used
Free version of cartoDB, with data and shapefiles from NYC Open Data including the Senior Center Directory, NYCHA Citywide Special Events (although not included in the final map). Batch Geo and Google Refine were used to locate and parse the senior centers and NYC Planning Health was underplayed beneath the senior center points.
Methods used
Pulling the data sets was relatively easy with some trouble converting the files in terms of latitude and longitude and cleaning up inconvenient typos that prevented smooth data transition.
The final project included a heat map, which showed clustering of senior centers in lower Manhattan and the Upper East Side. It is interesting that zoom control offered disparate views of the clustering, but still within the limits of logic. For instance, zooming out showed much more clustering in downtown Brooklyn than appeared when the city boroughs were balanced. Also, the point of center for the mobile screen version seemed logically to include the deepest clusters.

Results were very satisfying and logical, the heat map generated concentrations of senior centers in mid-Manhattan, UES and downtown Brooklyn. It gave a good idea of the prevalence of senior centers across the city with the least amount in the far reaches of Brooklyn and Queens and a sparse amount in Staten Island.
In the actual map, you can drill down to specific neighborhoods to see the street/neighborhood locations of the centers.

Through exchanges with classmates, we learned many extra features that can be added to the maps, such as icons and photos. A link to transit directions could be helpful.
The original question of finding and mapping constructive outdoor activities that is age-appropriate and gets seniors outdoors should be pursued. Within NYC Open Date there are datasets of landmarks, parks and other types of outdoor spaces that can be used. Presenting these types of easily interactive maps, very simply displayed and robust for elder hands and legacy media predispositions, might allow them to find their preferred spaces. A social network of great spaces for seniors could evolve.
In terms of using cartoDB, I think the idea of different representation of the information depending on zoom level will need more investigation for confidence in this type of mapping.