http://www.turbulence.org/Works/song/method/method.htmlhttp://www.turbulence.org/Works/song/mono.htmlFor example, the picture above was built from the first line of a very simple piece: Mary Had a Little Lamb. Each arch connects two identical passages. To clarify the connection between the visualization and the song, in this diagram the score is displayed beneath the arches.
http://www.visualcomplexity.com/vc/project_details.cfm?id=717&index=717&domain=This visualization represents the 140 MPhil and PhD research students at the Royal College of Art, and their relationships to funding agencies and institutional partners. Research RCA commissioned the visualization as a large-format poster for its 2009 exhibition, as well as a condensed version for the exhibition catalogue.
http://www.chrisharrison.net/projects/bibleviz/index.htmlBiblical Social Network (People and Places)Soon after finishing the cross-references arc visualization, I set out to create a new data set derived from the Bible’s text. This time I wanted to better capture the story, most notably the people and places, and the interactions between them. I did this by building a list of biblical names (2619 in total) and parsing a digital copy of the King James Bible. Each time two names occurred in the same verse, a connection was created between them. This produced essentially a social network of people and places. Because such relationships had no ordering or structure (unlike the cross references), I used a spatial clustering algorithm I developed for one of my other projects. This process causes related entities and highly connected groups to coalesce. I themed the output like an old piece of parchment.Additional details: Entities with less than 40 connections are drawn at an angle. Those with 40 or more connected entities are rendered horizontally - size is linearly proportional to the number of connections. The graph contains over 10,000 connections, too many to be useful and thus made purposely faint as not to overwhelm the piece. The names On, So, and No were excluded since they are both names and words (and I wasn't doing anything clever like named entity recognition when parsing the text).
http://www.metaportaldermedienpolemik.net/blog/Blog/2007-03-27/rotk-social-networkUsing Rhizome Navigation I analyzed the protagonist's relationships from the movie Lord Of The Rings: The Return Of The King. The size of a name relates to how many times it is mentioned within the movie script. The name positions are calculated by parsing the screenplay and analyzing which names appear close to each other in the text.Some thoughts: Frodo and Sam are very close to each other (of course), and it's interesting that the two stand between Gollum and The Ring. Although Aragorn is linked to both Arwen and Eowyn, the relationship seems not very strong (when compared to Frodo/Sam and Gandalf/Pippin for example). Both women appear at the opposite end of the graph. The relationships Gandalf/Pippin and Frodo/Sam seem equally weighted. This could also be an indication how the main storylines of the scripts are weighted.
http://infosthetics.com/archives/2011/01/notabilia_revealing_the_discussions_on_the_deletion_of_wikipedia_articles.htmlMoritz Stefaner'sNotabilia [notabilia.net] reveals the sentiment within the community discussions that focus on keeping or deleting specific Wikipedia entries. Any Wikipedia editor has the power to nominate an article for deletion and, if this nomination is legitimate, a community discussion takes place where follow editors have the opportunity to make their voices heard. The online visualization visualizes 100 Article for Deletion (AfD) discussions that took the longest amount of time. A discussion is represented by a thread starting at the bottom center. Each time a user joins an AfD discussion and recommends to 'keep', 'merge', or 'redirect' the article a green segment leaning towards the left is added. Each time a user recommends to 'delete' the article a red segment leaning towards the right is added. As the discussion progresses, the length of the segments as well as the angle slowly decay.Note that the visualized subset might not be representative, as more extensive data suggests that the largest part of these discussions ends after only a few recommendations have been expressed.
http://benfry.com/allstreets/All StreetsBen FryAll of the streets in the lower 48 United States: an image of 26 million individual road segments. No other features (such as outlines or geographic features) have been added to this image, however they emerge as roads avoid mountains, and sparse areas convey low population. This began as an example I created for a student in the fall of 2006, and I just recently got a chance to document it properly. Alaska and Hawaii were initially left out for simplicity's sake, but I felt guilty because of the sad emails received from zipdecode visitors. Unfortunately, the two states don't "work" because there aren't enough roads to outline their shape, so I left them out permanently. More technical details can be found here and additional updates here.
What is “dataesthetics”?<br />Or, what does data have to do with aesthetics?<br />
Definitions<br />Aesthetics<br />Concerned with beauty, taste, and perception.<br />Branch of philosophy contrasted with Logic.<br />“De gustibus non estdisputandum.”<br />Data<br />Discrete items of information.<br />Organized into regular structures.<br />Usually serves as the basis of Logic (reason and evidence.)<br />
There is a logic to art and an art to logic<br />
Flagellation, Piero della Francesca, c. 1448-49<br />
Demonstration of internal light source in Flagellation by Pierodella Francesca <br />
Digital Representation<br />“The use of discrete impulses or quantities arranged in coded patterns to represent variables or other data in the form of numbers or characters.”<br />i.e. Mapping of an object onto numbers and patterns<br />Examples:<br />Color as RGB<br />Space, time ...<br />But can be done with almost anything<br />
Other examples<br />http://www.ted.com/talks/hans_rosling_reveals_new_insights_on_poverty.html<br />http://3.bp.blogspot.com/_70Gw2abmBeI/TQ0sv2Fs6vI/AAAAAAAAA6Q/yu67k0UWCGc/s1600/AHMap.jpeg<br />http://www.visualcomplexity.com/vc/<br />http://infosthetics.com/<br />
Dimensions of Contrast<br />Hand-made vs. auto-generated<br />The use of space to signify dimensions<br />Use of colors, shapes, etc.<br />Interpretability<br />Levels: data models vs. data “reports”<br />
Focus<br />Abstract representations (graphs, trees, networks, user interfaces, etc.)<br />Tools:<br />PHP, CSV, MySQL, HTML, GraphViz, other network display and analysis tools<br />
In this course<br />You will learn how to acquire and extract data from different kind of sources<br />Of interest to the humanities and social sciences<br />You will learn how to use basic tools to express these data visually and interactively<br />You will acquire a vocabulary with which to express and frame your design decision<br />
Resources<br />WordPress site is accessible from UVaCollab<br />Readings for Tuesday will be posted today<br />Download and install jEdit<br />Enable Home Directory Service <br />See http://itc.virginia.edu/homedir/<br />Unix accounts will be created on STUDIO1<br />
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