This is the first post in a series questioning general relationship between digital humanities and the sciences. Specifically, the main concern is whether, and to what extent, DH contributes to the scientification of the humanities. That is to say, does DH lead the humanities away from the qualitative and ineffable and toward the quantitative and numerable? Does DH pose new questions as to the study and integrity of the humanities? How might we begin to articulate the potential benefits and limitations of DH when investigating these questions?
This is an ongoing debate between the proponents and critics of DH. The purpose of this series will be to examine the question of the relationship of the human sciences with the natural sciences, and to see how technology and the digitization of knowledge affects that relationship. Such a survey will lead, in part one, to a brief examination of the original distinction between the natural and human sciences, and then, in part two, to the question of technology as applied to human knowledge. Part three will focus on the contemporary relationship between Natural and Human sciences and how DH arises from that relationship.
A series of short blog posts is, of course, inadequate to resolve these big questions with any satisfaction. The purpose of this series is, instead, to raise the questions and begin to search for resources in addressing them. Relevant discussion comes from topics such as hermeneutics and philosophy, but touches on nearly every area of humanistic research. The question is as historical as it is philosophical, and we first have to question how we came to view the natural and human sciences as separate, discrete spheres of knowledge altogether.
After being on hiatus for a few years, UNT Comic Studies made a grand return in Spring 2017! Now hosted by the UNT Libraries, the Comic Studies Project invited poet, cartoonist, librarian, and author Sommer Browning to speak about Comics as Poetry for a rejuvenating restart to the program. During the webinar, people listened to the conversation both physically on the 2nd floor of the Willis Library and remotely for people who wanted to join in the conversation at a distance.
RAWGraphs offers hexagonal binning as an option for representing dispersions in datasets with an exceptionally large number of data points. This visualization visually clusters the most populated areas on a gridded surface and assigns a color based on the number of points in the region.
This example uses a public data set from Kaggle of data from 5000+ movies on IMDB. The x-axis shows IMDb movie ratings, and the y-axis displays gross revenue. Because there are so many data points in this set, it may be difficult to visualize the data in a clear and coherent way. However, hexagonal binning simplifies the data by clustering and color-coding it.
After setting up the visualization, this is what RAW gave me:
This year at The Digital Public Library of America (DPLA) Fest 2017 in Chicago, I had the opportunity to attend the Making the Case for Sustaining Your Digital Library Workshop. The workshop was hosted by two employees of the Foundation Center and was sponsored by a grant from the Knight Foundation.
The large group of us gathered in Chicago Public Library’s Harold Washington Library Center as a part of Hubs the day before the conference. The workshop participants were led through helpful activities and discussions, given grant-seeking insider knowledge, and had time to practice using the methods. We also brainstormed ideas to help us better communicate and build relationships with potential funders. One activity I enjoyed was called Roses, Thorns, and Buds wherein participants were asked to write down on colorful post-it notes the Positives (Roses), Challenges (Thorns), and Opportunities (Buds) for the projects we were looking to sustain. Group members then clustered the ideas to identify trends that were both plaguing and encouraging across our institutions.
When I was asked within hours of becoming employed as the Collaborative Programs Graduate Assistant at UNT to work at a Data Rescue event, I had virtually no idea what I would be doing or how I could contribute to something like rescuing data. While familiar with general computer use, hearing “Data Rescue” implied a level of technical ability that felt beyond my expertise. However, I would soon learn that the Data Rescue initiative provides opportunities for people at all technical levels to contribute their skills. Specifically, I found my opportunity in telling the Data Rescue story.
A dendrogram is a tree diagram that is usually used for showing taxonomic relationships, but any data that lends itself to hierarchical data clustering can be displayed using a dendrogram. RAWGraphs offers two variations on dendrograms: the circular dendrogram and the cluster dendrogram. I had some fun playing around with different data sets to provide examples of these two visualizations.
A circular, or radial cluster, dendrogram starts with more general classifications at the center and fans out to more specific classifications at the extremities. RAW give the user the option of using as many hierarchical steps as they want, and these can be in the form of strings, numbers, or dates.
I found a dataset from Kaggle that classified different Pokémon based on their type or types. I used the circular dendrogram to display this data, starting with their first type in the center and fanning out to their second type (if they had one) and then their name.
Digital Frontiers is an annual conference that explores advances and new research in humanities and cultural memory through the lenses of digital scholarship, technology, and multidisciplinary discourse. The conference recognizes creativity and collaboration across academic disciplines by bringing together researchers, students, librarians, archivists, genealogists, historians, information and technology professionals, and scientists.
The Digital Frontiers program committee invites poster & infographic proposals for the 2017 conference (September 21-23). The program committee encourages imagination and originality in programming proposals and promotes the inclusion of student research. Proposals may be for:
Poster proposals should be in the form of an abstract of no more than 250 words describing the topic to be presented. Please do not submit the final poster! Further guidelines and specifications will be provided upon acceptance.
A poster that presents a central hypothesis, research methodology, and outcomes in a clear, visually-appealing format.
Posters should offer a general summary of your findings and main points, and may be accompanied by a brief talk.
Recommended size 36 x 48, please include the estimated size of your submission in the proposal if it exceeds the recommended size.
Infographic submissions should include a 250 word description of the visualization including the methods, tool(s), dataset, and/or purpose, and an optional near-final version of the complete infographic if available (drafts are not required at submission).
An infographic that offers a single, informative visual image, or series of images, that represents data or information pertinent to your central research question(s).
The infographic should contain all of the information necessary for understanding your argument or main point.
Recommended size no less than 600 x 600 pixels to no more than 600 x 4800 pixels.
Proposals will be peer reviewed, with final decisions made by the program committee.
Video games stand as an utterly unique medium in today’s world. Nothing else comes close to what they offer and what they achieve. No other medium involves the same level of artistic interactivity and audience driven design. It is for this reason that both ludological and narratological studies fundamentally fail in regards to video games; they are both forms of study based on preexisting mediums. Ludology, the study of games as games, fails because it lacks the recognition of video games as story driven and containing more than just a series of game rules and mechanics. And narratology, the study of narrative, fails because it principally denies the idea that narrative can be in any way interactive, which is a fundamental basis of video games. To say that either approach holistically describes a proper study and understanding of video games is simply not valid. Now, this isn’t to say that certain elements of these studies can’t be used or adapted to better understand and interpret video games and video game design. There’s no need to reinvent the wheel here, and this is evident by seeing and analyzing the common patterns that video games hold between these two schools of thought. And so here we start with narrative.
Alluvial Diagrams represent flows and show correlations between categorical dimensions over time. This option visually links the number of elements sharing the same categories and is useful to see the evolution of clusters (such as the number of people belonging to a specific group).
The user is provided quite a bit of freedom when using the alluvial diagram through RAWGraphs. You can incorporate as many steps as you like, consisting of numbers, strings, or dates. The interface also allows you to choose your own colors, or you can use the ones that are automatically selected.
Last semester, we worked with some data from the Museum of Modern Art to play around with this visualization. The data provided the names of the directors and department heads of the museum from the 1930s to the present. We thought it would be interesting to see where these people completed their education and if there were any relationships between their institution and the department with which they were involved. Using resources including Wikipedia and the MoMA website itself, we were able to fill in the institutions for each of the individuals on the list (surprisingly, several of the directors and department heads don’t appear to have terminal degrees). We then uploaded this data into RAW and found that the alluvial diagram did a wonderful job of showing some strong relationships:
This representation strongly suggests that if you would like a job at the Museum of Modern Art, especially in the department of Painting and Sculpture, you might consider attending Harvard. It also provides a little bit of insight into the hiring trends of each department. It is clear that some departments, such as the Department of Media and Performance Art, tend to hire more from certain institutions (The University of Geneva) than others. Illustrating this information over time with a bump chart or possibly an animated viz would further illuminate these trends, but the alluvial diagram is suggestive and offers prompts for potential further inquiry.
For this example, we only incorporated two steps: institution and department, but it would be interesting to see what other relationships we could show. With more research and more data refining, we may be able to see how specific degrees and level of education related to each individual’s position in the MoMA.
Look out for more posts on the visualizations available through RAWGraphs!
Special shout out to Jeremy Singer-Vine for his rad weekly curated newsletter of open data sets “Data Is Plural,” where we discovered the MOMA data.