The recent release of City Nature leaves behind several static, dynamic, and interactive pieces that, for one reason or another, were not integrated into the final site. One of the reasons I created this blog was to showcase the work I was doing which, often, would not otherwise make it into the world.
Much of the models and data visualization that get produced is not specifically designed for publication, but rather to serve as an object of consideration and discussion during meetings and workshops. Others are built for presentations. Finally, even those that are designed to be final, whether as a figure accompanying an article or as a standalone work in a site like ORBIS or City Nature, end up being discarded. Whether due to performance issues, or lack of content, or more generic inaccessibility, various digital objects created during the course of a digital humanities project may not make it into the final publication.
One object that didn’t get it into City Nature was a representation of global water resource issues that displayed the 6000+ cities with a population over 50,000, rated by water security according to several different measures. From these, a dozen cities that typified the issues facing their region were selected to be described in a short narrative. All of this was delivered on a D3-based globe or traditionally-projected map:
But the performance was poor except in Chrome and, more importantly, the content and narrative never came together, which meant you had a cool interactive data visualization that wasn’t driven by a robust research agenda. The cutting room floor is littered with these, which can sometimes be dusted off, tuned up (this was built before Bostock changed everything again with topojson) and used for new research.
Often times they’re simply discarded. But that doesn’t mean they were a waste. Coding skills are improved as a result, of course, and the researchers working with these objects come away with an enhanced sophistication in their understanding of the data, the research, and the mechanisms to represent it. I think of this as the Salon Model of digital humanities, where working with digital objects, even with no plan to utilize them for high-level analysis or publication, results in significantly improved digital literacy necessary to perform quality digital humanities scholarship.
Another interactive data visualization piece was created to show a city composed not of the neighborhoods that it was actually made of but instead of neighborhoods most similar to each other based off the characteristics we measured.
You can see the interactive version here:
It’s a great concept, I think, but it proved illegible to most users and, as with many of these objects, performed poorly when integrated into the larger site.
There’s more on the floor. For instance, I’ve pointed before to a topic model browser I made in Protoviz that allows the reader to compare writing about species in the IUCN Red List compared to the same entries for those species on Wikipedia to compare the differences in language of the two species databases.
In process is a new version of this, using my much-improved skills and D3, which will hopefully leverage the lessons folks have learned about representing the results of topic modeling.
It’s my hope that at some point we’ll have a better process for releasing and annotating these objects, and I’d hope there’s a larger solution to better raise the visibility and understanding of this process for those currently on the outside. Until then, I’ll try to keep posting the code on Github and giving some explanation of them here.