Gap at St Vincent's Hospital

Title: Manhattan Skate Map
Affiliation: Jackson Vandeberg (Designer/Creator)
Subject Matter: Skate spots in Manhattan
Data Types: Locations and “names” of skate spots, locations of public transportation, photos of skate spots and skate spot features, “security” rating based on legality of skating in given location
Citations: None, the creator accepts submissions to the map via email.
Legend: Iconography for streets, skate spots, locations of subway stations and security ratings
Format: A basic html web page with the map itself made up of gif images laid out in a grid. Each “skate spot” location (represented by a colored dot) links to a subpage with photos of major features and possibly a description or security rating. Subway locations are color-coded to correspond to the color of the subway lines which are accessible.

For my map critique I took a look at something I’d stumbled upon when I made the decision to start skateboarding again after a 12 year hiatus, Jackson Vandeberg’s Manhattan Skate Map. I discovered the map while searching for skateboard retail shops in the city and was immediately drawn in by the information, if not the aesthetics. Vandeberg’s map catalogs “skate spots,” (the areas where street skaters congregate to practice their craft) and the features available at those spots. The word features, to a skater, pertains to the types of terrain available at a given location (i.e. stairs, banks, curbs, rails, etc). The map extends from 64th Street to Battery Park, covering a fairly large portion of the geography of Manhattan. While the map isn’t the most compelling thing in the world to look at, the colors are basic, the graphics and streets look like they were simply and sparingly drawn in Adobe Illustrator, the information it contains is invaluable to the fledgling (or returning) skateboarder looking to attack the streets of Manhattan. To demonstrate this I’d like to draw mostly on the Wood/Fels methodology as outlined in Shannon’s blog post.

The map is presented on a basic HTML web page. The welcome screen familiarizes the visitor with the small legend. Red colored dots represent skate spots, colored dots (corresponding to the subway lines) represent MTA Subway stops, and when you click through to each individual skate spot’s location page the major features are represented in photos, along with a security scale (in “pigs”) which denotes whether or not the site is consider a legal place to skateboard (zero) or completely unskateable (four). The map of Manhattan can be viewed all at once or in smaller sectionals which can be navigated cardinally via clickable arrows. The legend page also includes an appeal to the visitor to contact the map’s creator if there is a need to update information, or for suggestions or comments.

As I said before, the data in the map is presented in a neat, if slightly boring manor. The map is legible and navigable. The streets are shown in white, city blocks in blue, and parks are green. Skate spots are designated with a red dot, and Subway stops are shown with an “MTA” logo circle corresponding to the available train lines, divided in a “pie” format if there happens to be more than one. Considering the physical nature of skateboarding and its ties to the streets I suppose I assumed the map would have a little more “whiz-bang” feel, perhaps some more vibrant colors or graffiti, something to catch the eye. However it appears this was not the intention of the creator, as from the site you can access his graphic design portfolio which contains art that is rather flashy and eye-catching, so here the understatedness must be a conscious choice.

Vandeberg’s map is meant to be a resource for New York skaters and those visiting the city. The data seems to be focused on locating and visualizing the skate spots. Spots and the means to access them via public transportation are prominent on an otherwise spartan map. Detail views of each location contain photos of various features from various angles, a way to ensure the user of the map that when they arrive they are in fact in the correct location. There is also an additional political meaning behind the map that lends itself to street skateboarding’s history is a sport of questionable legal standing. The “pig” scale to denote the presence of police and security at the skate spots displays an antagonism towards law enforcement and firmly plants the creator of the map within an ideological camp of skaters that projects an anti-hero mentality.

If I have any criticisms of the map it is that the visuals should have been thought out a little better. Blue green and red, while primary and bold colors, don’t do this map any particular justice. If there were a bit more “popping” between the color selections perhaps the map would also be easier to read, especially on smaller screens like those found on portable devices. Additionally, while the map and the creator seem open to collaboration with the skating community at large, the email method of contributing info to the map/database seems a little dated. It seems the whole package could be updated with a little Web 2.0 functionality to improve work flow and efficiency. Perhaps comments and forums aren’t necessary, but even a simple form submission for new data would probably make the project seem a little more open.

In application to both my project and our effort as a class, this map fostered one major idea in my mind. For this map I almost wanted there to be, in addition to photographs of skate “features,” a sort of spatial recreation of the skate spots themselves. This could be a rough 3D mockup based on the photo data, no need for much detail other than x, y and z. With this 3D mockup you could introduce sensors which you could attach to the skateboards of local skaters and generate speed, velocity and other date to then display in the 3D space. This visualization of the “lines” of the skate spot would allow new skaters (and those coming back into the sport) to see what the contributors of a certain spot like about their location. While one skater might arrive at a location and see it as almost unskateable, perhaps the skater who submitted that site knows the secret method to making the location fun and challenging.

This type of sensor data could possibly be useful in my own project. While I am looking at video gaming, not a very physical activity, similar sensors to those described above could show patterns of use between the various games located in an arcade. Which games get the most traffic? Which games lend themselves to motion, which to sitting still? If sensors could be installed on the games themselves we could even look at which games invited the most pressure on their controls, the most striking of their sides in frustration or celebration. This type of kinetic data could be valuable to any kind of project really, but I am not sure of the feasibility of its execution. Regardless, the Manhattan Skate Map, aside from personally giving me a number of hints on where to start skating in the city, is a great example of a map which presents a very specific set of streamlined data in an accessible and straightforward way. While it isn’t particularly modular, in its execution it seems to be a good realization of the goal of its creator.