Finally taking my own advice, I’ve bought a MakerBot Replicator and I’m using it to print out my art.
It takes about ten hours to print a Balloon Dog:
The print quality is fascinating. It’s incredibly detailed and smooth, but it looks like it has been woven from a single long thread (which in a way it has) which gives it a very finely serrated quality.
I’m uploading pictures of work in progress and finished prints to MediaGoblin, take a look!
My Uploads project is getting there.
This is a low-resolution record of my mind (brain eeg via Mindwave) and body (a depth image/point cloud via Kinect) created using Python and played back using an OpenFrameworks application that uses the Twitter streaming API to match current emotional state data to the recorded states. It’s watching me watch Blade Runner…
Free Brit Art! [description+slogan] by Rob Myers
– Ruth Catlow.
Rob Myers does Damien Hirst (and Agnes Martin, and Ellsworth Kelly, and Barnett Newman, and Robert Ryman, and…
– Curt Cloninger.
Via The Jackdaw:
The Yale Center for British Art, New Haven, has placed digital images of its collections online. So far, so familiar. What is extraordinary is that all the images have been made available for reproduction free of charge, in superb high-resolution format, with no restriction over use… Other institutions in the USA are now considering whether to follow. The British Museum is a major institution that had already taken the same step in the UK. Otherwise the outlook in Britain is depressingly outdated, with museums and galleries, as this journal has frequently pointed out, obstructing not only scholarship but also wider familitarity with their collections throught the imposition of restrictive conditions on use and punitive fees. What makes it worse, much worse, are the outrageous claims to ‘copyright’ that are attached to use of images, preposterously applied to the mechanical reproductions of original works of art long out of copyright. This loathsome practice must stop.
– Robin Simon, The British Art Journal
Here’s a finished board, with the LEDs that are used as senses attached to wires made more rigid with heat shrink (this hides the resistors as well). The peculiar colour cast of the image is due to a coloured light being on in the background.
And here’s a plot of the light levels detected by each sense as I shone a light at them and shaded them with my hands.
That’s a Bluetooth wireless small sensorium. The code to support this is a bit hacky as rxtx doesn’t seem to want to play with Bluetooth serial ports, but it works.
The code is in the repository:
https://gitorious.org/robmyers/small-sensoria
Then a WiFi Arduino that could work with Thingspeak directly. And multiple sensoria could interact.
The values can be plotted linearly:
Or radially:
Next I am going to make the Arduino unit more independent by adding a Bluetooth shield, battery power, and wiring the LEDs up to it.
You can get the Arduino and Processing source code here:
I have written a script to download a dataset containing collection information from the UK Government Art Collection site and save it in tab-seperated-value files and an sqlite database for easy access. As the data is from a UK government agency it’s under the OGL.
You don’t need to run the script, a downloaded dataset is included in the project archive:
https://gitorious.org/robmyers/government-art-collection/
https://gitorious.org/robmyers/government-art-collection/trees/master/2011-12-11
The dataset doesn’t feature as many collections as the GAC website claims to feature, but the script does omit many duplicates. This project was inspired by Kasabi‘s scraper, adding the ability to download code and data in an easy-to-use format.
The examples of Psychogeodata given so far have used properties of the geodata graph and of street names to guide generation of Dérive. There are many more ways that Psychogeodata can be processed, some as simple as those already discussed, some much more complex.
There are some general strategies that most of the following techniques can be used as part of.
Joining the two highest or lowest examples of a particular measure.
Joining the longest run of the highest or lowest examples of a particular measure.
Joining a series of destination waypoints chosen using a particular measure.
The paths constructed using these strategies can also be forced to be non-intersecting, and/or the waypoints re-ordered to find the shortest journey between them.
Other mathematical properties of graphs can produce interesting walks. The length of edges or ways can be used to find sequences of long or short distances.
Machine learning techniques, such as clustering, can arrange nodes spatially or semantically.
Simple left/right choices and fixed or varying degrees can create zig-zag or spiral paths for set distances or until the path self-intersects.
Find long or short street names or street names with the most or fewest words or syllables and find runs of them or use them as waypoints.
Find all the street names on a particular theme (colours, saints’ names, trees) and use them as waypoints to be joined in a walk.
Streets that are particularly straight or crooked can be joined to create rough or smooth paths to follow.
If height information can be added to the geodata graph, node elevation can be used as a property for routing. Join high and low points, flow downhill like water, or find the longest runs of valleys or ridges.
Information about Named entities extracted from street, location and district names from services such as DBPedia or Freebase and used to connect them. Dates, historical locations, historical facts, biographical or scientific information and other properties are available from such services in a machine-readable form.
Routing between peaks and troughs in sociological information such as population, demographics, crime occurrence, ploitical affiliation, property prices can produce a journey through the social landscape.
Points of interest in OpenStreetMap’s data are represented by nodes tagged as “historic”, “amenity”, “leisure”, etc. . It is trivial to find these nodes to use as destinations for walks across the geodata graph. They can then be grouped and used as waypoints in a route that will visit every coffee shop in a town, or one of each kind of amenity in alphabetical order, in an open or closed path for example. Making a journey joining each location with a central base will produce a star shape.
Places of worship (or former Woolworth stores can be used to find https://en.wikipedia.org/wiki/Ley_line using linear regression or the techniques discussed below in “Geometry and Computer Graphics”.
The words of poems or song lyrics (less stopwords), matched either directly or through hypernyms using Wordnet, can be searched for in street and location names to use as waypoints in a path. Likewise named entities extracted from stories, news items and historical accounts.
More abstract narratives can be constructed using concepts from The Hero’s Journey.
Nodes found using any other technique can be grouped or sequenced semantically as waypoints using Wordnet hypernym matching.
Renamed Tube maps, and journeys through one city navigated using a map of another, are examples of using isomorphism in Psychogeography.
Entire city graphs are very unlikely to be isomorphic, and the routes between famous locations will contain only a few streets anyway, so sub-graphs are both easier and more useful for matching. Better geographic correlations between locations can be made by scoring possible matches using the lengths of ways and the angles of junctions. Match accuracy can be varied by changing the tolerances used when scoring.
Simple isomorphism checking can be performed using The NetworkX library’s functions . Projecting points from a subgraph onto a target graph then brute-force searching for matches by varying the matrix used in the projection and scoring each attempt based on how closely the points match . Or Isomorphisms can be bred using genetic algorithms, using degree of isomorphism as the fitness function and proposed subgraphs as the population.
Another key contemporary application of graph theory is Social Network Analysis. The techniques and tools from both the social science and web 2.0 can be applied directly to geodata graphs.
Or the graphs of people’s social relationships from Facebook, Twitter and other services can mapped onto their local geodata graph using the techniques from “Isomorphism” above, projecting their social space onto their geographic space for them to explore and experience anew.
Computer geometry and computer graphics or computer vision techniques can be used on the nodes and edges of geodata to find forms.
Shapes can be matched by using them to cull nodes using an insideness test or to find the nearest points to the lines of the shape. Or line/edge intersection can be used. Such matching can be made fuzzy or accurate using the matching techniques in “Isomorphism”.
Simple geometric forms can be found – triangles, squares and quadrilaterals, stars. Cycle bases may be a good source of these. Simple shapes can be found – smiley faces, house shapes, arrows, magical symbols. Sequences of such forms can be joined based on their mathematical properties or on semantics.
For more complex forms, face recognition, object recognition, or OCR algorithms can be used on nodes or edges to find shapes and sequences of shapes.
Classic computer graphics methods such as L-sytems, turtle graphics, Conway’s Game of Life, or Voronoi diagrams can be applied to the Geodata graph in order to produce paths to follow.
Geometric animations or tweens created on or mapped onto the geodata graph can be walked on successive days.
GPS traces generated by an individual or group can be used to create new journeys relating to personal or shared history and experience. So can individual or shared checkins from social networking services. Passenger level information for mass transport services is the equivalent for stations or airports.
Data streams of personal behaviour such as scrobbles, purchase histories, and tweets can be fetched and processed semantically in order to map them onto geodata. This overlaps with “Isomorphism”, “Semantics”, and “The Social Graph” above.
Temperature, brightness, sound level, radio wave, radiation, gravity and entropy levels can all be measured or logged and used as weights for pathfinding. Ths brings Psychogeodata into the realm of Psychogeophysics.
This series of posts has made the case for the concept, practicality, and future potential of Psychogeodata. The existing code produces interesting results, and there’s much more that can be added and experienced.
(Part one of this series can be found here, part two can be found here . The source code for the Psychogeodata library can be found here .)
