Well, it wasn’t easy, but now we’ve included support for the procedural loading and playing of YouTube videos directly within E15. Through the use of the poorly documented Google Data APIs, E15 users can access all kinds of interesting YouTube video metadata to aid their visualizations. The new E15 interface with the new console. Now with YouTube.

With the recent browser integration, E15 is now able to support custom user scripting. Because E15 has a Python interpreter at its core, page content can be searched, and browsing automated. As an example, we have integrated a spidering script into E15:In this example, a Python script directs the procedural traversal of a set of links originating from a single Flickr page. The end result is a space of pages that can then be visually explored. And if visual exploration is not enough, text-based filtering of results can reveal pages that would have otherwise been hard to find in a large set of pages:

When we give the E15 demo to sponsors here at the Media Lab, a question we’re often asked is whether or not the pages we’ve loaded are still “active”. Unfortunately, E15 was not built for this type of support. We’re trying to enable experiences and interactions with web content beyond the web browser, not to simply re-create the browser experience within a 3D environment. However, there is an important relationship between the browser and web content, and E15 needs to have the ability to talk directly to the browser. As a result, we’ve recently integrated a full-fledged web browser into E15:

With a browser, it becomes trivial to leverage the existing features of E15 to visually represent browser interactions. As a simple first demo, we can load a page into the embedded E15 browser, navigate through a set of pages, and construct a visual history of pages traversed. Show below is the result of the traversal of 9 links starting from google:

We’ve been using E15 to experiment with different layouts of web content in a 3D environment. The Python scripting interface makes it possible for us to have access to a wide variety of datasets using existing libraries to grab content from blogs, Flickr, Facebook, Wikipedia, and just about any other site with an API or RSS feed. What to do with the web content is a much more challenging problem than actually acquiring the content.

In some early sketches of web content layouts, I had arranged webpages around the perimeter of a circle. While searching for more interesting equations to use for laying out pages, I found an awesome Wikipedia page called List of Curves with over 50 different types of mathematical curves. The problem with this page, however, is that it has no pictures of the curves. I want to see what all the curves look like, but I’m not about to click through every single page, one at a time.

So, I wrote a Python script that uses the MediaWiki API for Wikipedia to find all the articles linked from the List of Curves article, finds the images linked from those articles, and finally renders all the images in E15 with the relevant article titles:

If you’re curious about how these pages were laid out, I used a rose curve with 8 petals — pictures of this curve are in the middle of the screenshot below:

One more screenshot:

I’ll be working with the same data more this week, so check back soon for more images, and probably a video or two!