On April 25 I had the honor of presenting at 360|intersect. My talk was titled Desperately Trying to Remove the Air Quotes Around the Word “Artist”. I present artwork I’ve created over the past year, and reflect on my struggle to identify as an artist.
The video recording of my talk is below, it’s about 45 minutes long.
Census tracts are ranked by median family income and the poorest areas are cut out of the city and discarded. San Francisco is quickly becoming one of the most expensive cities in the world, but real world gentrification will take decades to fully push out all the poor people. With this map we do so in a single fell swoop.
Laser cut wood
Three panels present different views of crime in San Francisco: narcotics, prostitution, and vehicle theft. The height of each map shows the relative density of each type of crime, as if crime were elevation. The mountain peaks are exaggerated, jutting out into the viewer’s face.
Drug arrests occur throughout the city, but are heavily concentrated in the Tenderloin and Mission neighborhoods. Prostitution shows a stark contrast, with nearly all arrest occurring along only a few streets. And vehicle theft occurs heavily throughout nearly the entire city, highlighting that you can get your car stolen nearly anywhere you park.
3D printed plastic mounted on painted plywood
12″ x 12″ x 8″
Narcotics
Vehicle Theft
Prostitution
San Francisco is presented as a wooden box, seemingly sleek and clean. You’re invited to open the box to see what’s under the surface, revealing a map of sex offender hotspots. This map reminds us of the often invisible aspects of our cities we either can’t see or choose to ignore.
Laser cut wood
13″ x 13″ x 8″
The density of a decade of Portland burglaries is mapped using layered sheets of laser cut cardstock, producing a reverse topological map. The deeper valleys represent the highest concentrations of burglaries over a ten year period between 2004-2013.
Laser cut cardstock
15″ x 15″
Two maps compare vehicle theft and prostitution. The data points are aggregated as hexagons and raised off the wall to represent the relative distribution of crime. Vehicle thefts peak in Old Town, but also occur highly throughout the city. The prostitution map is more concentrated and shows a cliff rising along 82nd Avenue.
3D printed PLA plastic mounted on painted plywood
15″ x 15″ x 8″
Prostitution peaks along 82nd Ave
Vehicle Theft is heavily spread out throughout Portland, but peaks in Old Town
Prostitution
Vehicle Theft
Viewed from most angles, this self portrait presents a distorted, grotesque image. Spikes form in seemingly arbitrary patterns, casting shadows over the valleys of the sculpture. But when viewed from the right angle, with the light shining from precisely the right direction, the shadows line up and work together to form the image. The portrait is a stark reminder that how one sees oneself depends entirely on finding the right perspective.
For ideal viewing stand approximately 6 feet back and view the portrait straight on.
3D printed plastic mounted on painted plywood
15 x 15 x 8
This map mimics a typical traffic map but represents the number of driving under the influence (DUI) arrests along each street over the course of 10 years. Red, orange, yellow, and green are used to denote relative frequencies of DUIs.
I’ve been working on a utility called shp2stl that converts geographic data in shapefiles to 3D models, suitable for 3D printing. The code is published as a NodeJS package, available on npm and GitHub.
You can control the height of each shape by specifying an attribute of your data to use. Each shape will be placed along the z-axis based on the shape’s value relative to the max range in the data. Additionally, if you want more detailed control you can specify a function to use to extrude each shape.
Here’s an example using the recent South Napa earthquake, first as the source shapefile:
Then converted to a 3D model using shp2stl:
And finally printed with a 3D printer:
This is a map of murders throughout the Bay Area. Constellations are formed by connecting homicides from 2013 that are in close geographic proximity to each other. Homicides from 2014 are also layered on to provide a bit more context, although not used to form the constellations.
