Project and the Field of the Digital Humanities:
One of the biggest challenges that Digital Studies as a whole faces is how abstract and complex its fundamental products are. There is often a high threshold for complexity leaving many creators and users confused because they lack specific knowledge of the particular processes of the Digital Studies. In the realm of Digital Mapping, the various coordinate systems, terms, and file types prevent creators from going as far beyond traditional mapping ideas as they could and keeps the layman away from using the products, as only those immersed in the study of Digital Mapping can understand the scope of the complexity of some of the projects. They may be able to see the big picture, but unlike text files or images, very few understand the mechanics of the processes. With the Digital Map App of Davidson College, I hope to create a simple linking of the ideas of geospatial data that serves as both a practical tool for navigation as well as a simple example of how geospatial data can be approached by an average user.
Stephen Ramsay and Rockwell’s “Developing Things: Notes toward an Epistemology of Building in the Digital Humanities” offers a clear and concise summation of the general issues surrounding digital studies as a whole. Ramsay and Rockwell argue that the abstract nature of Digital Studies as a whole has left many within the community questioning and arguing about what the definition is. This is in part due to the wide range of complex ideas that are a part of different segments of the Digital Humanities, how “but their work is all about XML, XSLT, GIS, R, CSS, and C” (Ramsay, Rockwell). While many average users of computers understand how text can be bolded oritalicized and at least know that JPEG and PNG files refer to images, for most people the aforementioned file types are simply gibberish. In addition, in Ramsay and Rockwell’s discussion, there is no uniformity in the use of these file types across even the subsections of the Digital Humanities. Not every map is made with GIS, and not every program is run by C. This complexity is part of why it seems Ramsay and Rockwell have left out discussion of the Digital Humanities for the common man, the only noticeable omission in the article. While I would have liked the discussion there, if the Digital Humanities departments cannot define themselves, then it would be difficult for a layman to have any idea where to start.
There are many attempts to explain the concept of geospatial data, a important concept to the subject of digital mapping, to the layman with mixed results. The Environmental Protection Agency (EPA) attempts to define geospatial data for those wishing to keep records, but their definitions and procedure reveal the outdated approaches that those working outside the Digital Humanities often take, whether out of ease or necessity. While offering advice on how to store records, the EPA states that “Geospatial data records are often in special formats (e.g., oversized paper maps or data sets). Therefore, it is especially important to identify the geospatial data records with appropriate metadata, so the records can be easily accessed and retrieved with other, related records” (Environmental Protection Agency, Frequent Questions about Geospatial Data and Records). Rather than believe the EPA is ignorant to the more condensed ways of storing geospatial data, it rather seems that they must suggest less compact ways of storing data by the virtue that they are simpler for the user in the face of the overwhelming complexity that shapefiles and raster layers may bring to the uninitiated record keeper. While the FAQ may not be a good robust description of the idea of geospatial data, it must limit itself to inefficient simplicity in order to explain itself to users.
However, even without the need to focus on practical applications like record keeping, the definition of geospatial data can remain elusive. Even the handbook of geospatial data, a “user manual” for those who are trying to understand geospatial servers, must resort to relating text and webpages into its language in order to convey just what geospatial data is. While the guide book makes the claim that “Soon a search for spatial data will be as easy as a Google search for a web page (OpenPlans, GeoServer 2.6.x User Manual) they also bring up “browser” based systems and offer very few concrete examples that truly explain what geospatial data is supposed to be. The handbook tries to argue that geospatial data is fundamentally different from other types of data, yet only describes it using comparisons.
However, to understand geospatial data one only needs to look as far as the concept of spaces and places in people minds, commonly referred to as a “mental map.” Ozkul and Gauntlett’s “Locative Media in the City: Drawing Maps and Telling Stories” in Mobile Stories, serves as both an easy to comprehend discussion of what mental maps are as well as how people view geospatial data within their own minds. In their study, users were asked to “draw a map of London showing ‘frequently visited places’” (Ozkul Gauntlett 114). What surfaced did not take the form of raster layers, CSS code, or shapefiles placed by a complex coordinate system. Rather, people drew pictures and words in order to explain how geospatial data related to the real world. They also discussed concepts outloud that described how they viewed geospatial data, though they might not have personally called their ideas as such (114). This thorough discussion highlights one of the key difficulties that surrounds the abstract nature of many discussions on digital humanities. Text, pictures, and other common forms of data are not separate entities from geospatial data but rather simply another lense with which to view the various types of data that make up the world as a whole.
Data is not nearly as sectioned off into buckets of categories with no overlap as those who are obsessed with the quantitative over the qualitative might want you to think. Images like photographs can easily contain text, from a photo of a book to a simple captioned image. Text can be used to create images such as ASCII[1] art or emoticons[2]. The tools we use to create these are the same at their base as well. Webpages are made up of pixels which create both text and images, all of which are founded in the same code. There are different tools that produce similar results, but it is not the intrinsic makeup of these types of data that defines what they are but rather how we as people choose to interpret them. Likewise, geospatial data doesn’t need to be made up of completely different types of components from webpages or any other medium. What geospatial data does is combine the same elements that we use daily to produce other types of data in a way that people interpret as having to do with the space and place around them. This simplicity is something I hope to achieve with the Davidson Mapping App I am creating with the MIT aiAppInventor software[3].
Rather than trying to keep a purity of only geospatial data, the Davidson Mapping App attempts to look at text and image data through a geospatial lense. The current Davidson map[4] uses shapes and symbols as primary indicators of space, yet often that is confusing since people don’t tend to think in terms of those particular symbols but rather in terms of descriptions and mental pictures (Ozkul, Gauntlett). Therefore, the Mapping App adds textual descriptions and identifiable images to the available data to give users the best sense of where these spaces are, what they look like, and what they contain. Practically speaking, the text gives the buildings a sense of what they are commonly used for and the specific areas inside them, such as Hance Auditorium on the fourth floor of Chambers which, according to several Davidson students, was a very difficult place to locate the first time. The images help give the users’ mental maps a better foundation than the symbols; rather than simplistic shapefiles to go off of, users can have an image of the building or space in their minds that matches up very closely to what they will see when they approach the space. However, the app serves a purpose in getting users familiar with geospatial data itself as well.
MIT’s aiAppInventor is a program built around simplicity and therefore is a perfect medium to try to convey geospatial data in a clear and simple manner. The apps are programmed using predetermined blocks of code, which keeps the interface simple for both creators and users. While at first this design may seem limiting, it helps to streamline the application of use. One cannot incorporate GIS files or Excel data spreadsheets into this tool. Therefore, the cartographer and the layman are on common ground and data does not need to be translated from a complicated form back into simplistic terms. The app inventor does not work well for complicated projects, but is a great tool for understanding basic components of data and for presenting those components to a user.
In order to get definition at the higher levels of digital studies, we must first people to explain ourselves on simple terms to the average person. While there will always be an important place for discussion at the higher level of the subject, it’s important to make the Digital Humanities to be as accessible as possible for the common person as basic math, science, language or art is. Tools that appeal to our interpretation of geospatial data rather than the semantics about it will help us better understand what the essence of Digital Mapping within the Digital Humanities really is.
[1] ASCII art is made up of pictures using only the 128 characters from American Standard Code for Information Interchange.
[2] Emoticons use the characters on a keyboard to denote certain facial expressions or emotions.
[3] http://appinventor.mit.edu/explore/
[4]http://www.davidson.edu/Documents/About/Visit/Campus%20Map/Campus-Map-8-5×11-2013.pdf
