» Demystifying Networks, Parts I & II Journal of Digital Humanities Scott B. Weingart Part 1 of n: An Introduction This piece builds on a bunch of my recent blog posts that have mentioned networks. Elijah Meeks already has prepared a good introduction to network visualizations on his own blog, so I cover more of the conceptual issues here, hoping to reach people with little-to-no background in networks or math, and specifically to digital humanists interested in applying network analysis to their own work. Some Warnings A network is a fantastic tool in the digital humanist’s toolbox—one of many—and it’s no exaggeration to say pretty much any data can be studied via network analysis. The danger here is two-fold. When you’re given your first hammer, everything looks like a nail. The Basics Nothing worth discovering has ever been found in safe waters. Anyone with a lot of time and a vicious interest in networks should stop reading right now, and instead pick up copies of Networks, Crowds, and Markets and Networks: An Introduction. Networks The Stuff Scott B.
Small Design Firm NRC: Naturalist Tables, Raleigh, North Carolina, 2012 Small Design Firm developed two completely custom interactive tables for the Nature Research Center at the North Carolina Museum of Natural Sciences. Visitors to the museum are invited to pick up actual specimens from the museum collection and place them on to the table surface. There are over a hundred available specimens, ranging from mounted insects and preserved amphibians, to mammal study skins and bird skulls. Project Details NRC: Storm Central & Real Time Weather Station, Raleigh, North Carolina, 2012 The Storm Central desk features three stations at which visitors can track a hurricane or make their own weather forecast. The Tracking activity provides an introduction to the anatomy of a hurricane and explores the multitude of factors that contribute to their unpredictable nature. Nearby, a model of a weather station shows how meteorologists collect data in the field. Project Details Project Details Project Details Project Details
Nifty Corners Cube - freedom to round More than one year has passed from the first version of Nifty Corners. While it was more of a proof of concept, and the second version presented some big improvements, there was still something missing. So here I present Nifty Corners Cube, that are simpler and more flexible than the previous versions. New features If you're new to Nifty Corners, I suggest to look in particular at the article on the first version to understand the concept behind them. There are several improvements and new features introduced in Nifty Corners Cube which make it more versatile and simpler to use than the previous versions: Together with the many novelties, that we'll discover through several examples, two features of the previous version has been abandoned. Nifty Corners Cube: introduction Nifty Corners Cube are a solution to get rounded corners without images, and this third version is build by three main components: The parameters Example 1: a single div The first example has been already presented.
Digital Humanities Now Gephi, an open source graph visualization and manipulation software The Graph Of TV Actors « Griff's Graphs This time I wanted to see the relationship between TV actors. I’m not especially interested in TV series but I am quite interested in how they work together. The fact that many actors have been in a number of TV series creates a great network of information. Method: I first went to Freebase’s tried to download every actor available their corresponding TV shows. Unfortunately, Freebase had over 57,000 nodes which disabled me from querying what I wanted. The Graph: The Graph Of TV Actors Click here to zoom around. As one would expect there are sub-networks within the entire graph. Some of the sub-networks include: Gilmore Girls, Alias and Arrested Development Saved By The Bell and Frasier The Power Rangers All of these actors have worked together in a number of TV series. As you might have noticed, the TV series here are reasonably old. I couldn’t label the central regions because it is so entangled. Future One could feasibly create a map for film actors also. Anyway, just a short one today.
Vis Group | Voyagers and Voyeurs: Supporting Asynchronous Collaborative Information Visualization The sense.us collaborative visualization system. (a) An interactive visualization applet, with a graphical annotation for the currently selected comment. The visualization is a stacked time-series visualization of the U.S. labor force, broken down by gender. Here the percentage of the work force in military jobs is shown. (b) A set of graphical annotation tools. abstract This paper describes mechanisms for asynchronous collaboration in the context of information visualization, recasting visualizations as not just analytic tools, but social spaces. materials and links citation
Top 10 CSS Table Designs By R. Christie Tables have got to be one of the most difficult objects to style in the Web, thanks to the cryptic markup, the amount of detail we have to take care of, and lack of browser compatibility. A lot of time could be wasted on a single table although it’s just a simple one. This is where this article comes in handy. First things first Link We start with a valid xhtml 1.0 strict markup. <table id="..." You can read more about xhtml table markup in HTML Dog’s Table Section1. Before we start, let’s review the general rule of thumb for styling of tables: Tables love space. Now that we are all set up let’s get going, shall we? Overview of this article Page 1: Top 10 CSS Table Designs
Datafication: How the Lens of Data Changes How We See Ourselves Digital media allow us to produce, collect, organise and interpret more data about our lives than ever before. Our every digital interaction contributes to vast databases of information that index our behaviour from online movie choices to mapping networks of connections across Twitter. In an age of uncertainty, big data sets promise to provide an objective lens through which to understand the world, and both individuals and institutions like schools are turning to data to drive analysis and action. But what does this increasing datafication mean for how we understand the world, and how we understand learning? Learning to Read Digital Data Data can be reassuring. But our interpretation of data is also skewed by how that data is represented. Data Reflects the Past and Drives Future Behaviour As we engage in online activity, we leave trails of data in our wake that are added to the huge databases held by Facebook, Google and marketing companies. Remixing Data