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Tools

Mapping with Kepler.gl

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The kepler.gl mapping tools highlight time-space relationships and trends in a dataset. Starting with a CSV file of 130 text entries for the Slave Narratives project as its data source, kepler.gl produced a point map that visualized the locations of interviews with former slaves living in Alabama in 1937. Just the basic point map alone provided insight into where most interviews took place and where former slaves settled within Alabama after their emancipation. The heat and cluster map features articulated this information even more effectively; these visualizations distilled 130 individual location data points into concentrated “masses” that conveyed trends about the volume of interviews in different regions of the state. Unsurprisingly, most centered around the major cities of Mobile, Montgomery and Birmingham. The category feature in kepler.gl took the analysis one step further – not only could I learn about the number and locations of interviews but also about the interviewees themselves. This did require me to switch back to a point map; however, at this point, I was interested in more detailed information and found myself zooming in on specific cities to learn more about the nature of the work that these former slaves performed (the type categories being house, field, both or unknown).

At the same time, there are some limitations on these tools to consider. First, they are only as good as the underlying data. In the case of the Slave Interview project, the dataset included exact latitude and longitude coordinates which made for a very crisp and accurate visualization. Alternatively, the MGG project team encountered some issues in this space which they managed to address somewhat effectively. A considerable number of locations in the Damron guides did not list clear addresses that the project team could link to coordinates. As a result, some of their data entries use generalized city/town locations that produce skewed or misleading results. The project team dealt with this by creating an option to filter out these particular results, leaving the decision to the individual user based on their preference.

Other limitations worth mentioning are the embedded assumptions contained within maps, which Presner and Shepard foreground in their discussion of “spatial humanities.” While I believe that each of the projects and activities lent themselves best to a “traditional” cartography, in other circumstance, particularly when approaching topics in ancient history, a different approach may be appropriate. Presner and Shepard correctly identify these concerns, but do not help the reader to understand alternatives to overcome the modern, Western biases inherent in mapping. Perhaps in practice this would look like a mapping tool that focuses more on one object’s location in reference to another object, landmark or natural feature rather than on GPS coordinates, as ancient peoples would have understood their world more in these terms without a fully developed sense of latitude and longitude.

Tools

Text Analysis with Voyant

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Using the Voyant text mining tools for the first time, I found the word frequency data and the corresponding visualizations (such as the Cirrus word cloud and the Trends graph) to be incredible valuable for gathering insights about the WPA Slave Narrative interviews. When done correctly, to include flagging common “stopwords” to filter out irrelevant data, an analysis of word frequency can prove fruitful for understanding the topics of emphasis for the authors of the corpus. And yet more than telling us the about the corpus as a whole, the distinctive words tool also makes an intra-text analysis possible – one in which the user can compare different sections of the corpus against each other. In the case of the WPA Slave Narrative documents, this tool revealed differences in dialects between interviewees of different states.

But as Sinclair and Rockwell remind us, these tools do not create inherent meaning from their results; determining the significance of the results still relies upon the researcher. For example, the Link tool revealed a relationship between the word “big” and the word “house.” Taking the results at face value would suggest that interviewees were simply referring to the physical size of the structures on the plantations they worked. However, as the student using the tool, it was up to me to connect this with the historical concept of the “big house,” which was embedded with cultural connotations connected to slave hierarchies and treatment on the plantation. Furthermore, as the Signs@40 activity demonstrates, our analysis is only as good as our corpus. In the process of selecting a corpus, whether from an archive or a journal in the case of Signs@40, we depend on the conscious or unconscious decisions of archivists and publishers make about what types of sources belong. Guldi refers to this as the “silence” of archives (523), and the Signs@40 project’s focus on the history of only one journal to serve as a stand-in for feminist discourse over several decades was one of its shortfalls.

Databases, Tools

Humanities Data

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Two of the most significant benefits to scholarship of creating data from humanities sources are that 1) the data often prompts additional questions and avenues for research about those sources as a result of their new arrangement, and 2) properly cleaned and normalized data can allow for visualizations to aid our understanding of the sources. In terms of new questions that arise as a result of data, the Tudor Network, Fairfax Court Slavery Index and Early African American Film projects drove home the idea of relationships in a way that the original sources alone may not have. One example of how these projects reveal new relational information comes from the African American film data table – the linking of film data to people data allows one to compile a filmography for a particular actor who might have otherwise been lost to history. Because data can also feed into visualization software, these relationships can be visualized in a way that makes these projects more amenable to public view and study.
In each of these three projects, the team of scholars was clear about their methodology to gathering, cleaning and normalizing the data. Hoekstra and Koolen’s article emphasizes this need for methodological transparency regarding data creation, a point that may be obvious for researchers in the social sciences but one that not all humanities scholars may fully appreciate. Posner attributes this to the fact that traditionally humanities scholars have been less interested in the reproducibility of results, in contrast with other fields. In the Fairfax Slavery Index project, for example, the project scholars explain in great detail which types of records they chose to include, how they defined categories related to one’s status as enslaved or free, and even how they chose to notate different currencies. Finally, in addition to the need for disclosure of these modelling methods, Drucker draws attention to the ethical concerns related to data collection and privacy, particularly given that some jurisdictions such as the EU have enacted very strict data privacy laws (26).
Reviews, Tools

Why Metadata Matters

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Metadata plays an essential role in making digital humanities projects productive endeavors that offer useful information to scholars and the general public. The Carbajal and Caswell reading comprehensively addresses the purpose and benefits of metadata as well as how to approach metadata with a critical eye. Most fundamentally, metadata allows for more specific categorization and easier searching of digital records (1106).
The previous module on digitization highlights how the end result of digitization can be the separation of an object from its original cultural context. While metadata may not fully resolve this problem, detailed metadata organized in a thoughtful way can go a long way in restoring some of that context for users. Yet metadata can also introduce new issues of cultural context – any activity involving categorization or description contains inherent cultural biases that should force users to pause and question the choices of the metadata’s creators (1109-1110).
Two digital tools that facilitate the use of metadata for digital humanities projects are Tropy and Omeka. Tropy allows users to import PDFs and images for storage and organizing with tags and other metadata. The software can handle large projects and accepts a wide variety of file types for images. Additionally, after uploading my kitchen item photos during the module activity, Tropy gave me several options for metadata templates rather than forcing me to start from scratch building descriptive categories.
Omeka, while requiring a bit more technical savvy, does an effective job of building on the raw metadata one might include in Tropy and enhancing it for public display online. What I found most beneficial about Omeka was the visual customization options for my items and the corresponding data. It forced me to consider which presentation options would be most appropriate to different types of data and images. And just like with Tropy, Omeka provides a preset Dublin Core of metadata elements which takes some of the burden of developing taxonomy off the creator. As a digital humanities novice, I appreciated having this built-in as a starting point.
Guides

A Guide to Digitization

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The act of digitization has implications for both how we experience an object aesthetically and what kind of information we can gather from an analysis of that object. The kitchen item digitization project spoke very effectively to the former, as one example. Uploading pictures and 3D visualizations of an orange (despite being a rather mundane object) drove home the realization that we use all of our senses to interpret an object, not just our sight. Thus, what is lost when digitizing is the way in which an object acts upon our other senses. Yet, our vision can still activate our other senses, and high-quality digitization should involve consideration of how well the newly-created image captures features which engage our sense of smell, taste, hearing and touch. In the case of the orange, I wanted to ensure that the 3D visualization adequately rendered the small speck on the fruit that looked like it was beginning to rot. This gives the viewer a sense of its taste even without it being physically there to bite.
Many of the benefits of digitization as described in the readings — such as OCR software allowing for searchable documents (Terras 2) and greater accessibility/viewability (Drucker 164) — seemed fairly self-evident (though this could be my own generational bias which causes me to take these benefits for granted). Admittedly, I found Terras‘ and Drucker’s discussions of the drawbacks to digitization to be more compelling and surprising, as they were points which I had not considered previously. Drucker’s assertion that digitization can separate an object from its cultural context resonated with me (166-167); in conjunction with her later example of the Caligula statue, the point made me reflect on a course I took last fall on Roman art in the Augustan period. Several times during that class, the professor stressed the importance of context when analyzing archaeological finds. Just as important as the object itself is its findspot relative to other objects. This is perhaps the most critical aspect of an object’s cultural significance that can be obscured or lost when only engaging with it digitally. This, along with Terras’ reminder that a digital collection is a result of deliberate choices of inclusion/exclusion which can contain bias (259), should not stop us from relying on digital materials but rather force us to engage them more critically.
Databases

Finding Digitized Sources for My Art History Research Project

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At this point early in the semester, I am just beginning to form potential questions and avenues of inquiry for my research project, which will likely focus on the self-portraits of German Renaissance artist Albrecht Durer. The preliminary research I’ve done thus far reflects two possibilities for the project: one envisions a more traditional formal analysis of the self-portraits visually enhanced through an online exhibit in Omeka, while the other would involve selecting a corpus of scholarly literature over a specific period of time to develop a picture of historiographic change on the subject with the help of the Voyant text analysis tool.

With this in mind, I’d like to briefly discuss my research efforts and thought process. For the first concept of this project, I used a GMU Library database called ARTSTOR to search the term “Durer self-portrait” for images that could be used for an online exhibit. It’s important to note that most images available on ARTSTOR have copyright restrictions that would prevent one from using the image on a public-facing blog (even one used for primarily educational purposes). But the purpose of ARTSTOR was to search within a scholarly database to identify the specific images that I could then look for elsewhere in a more “copyright friendly” search tool like Google Image. Google gave me the option to search the same images with a public domain filter, giving me results that were usable on my blog.

For this historiography iteration of the project, I started with the Rijksmuseum database (one of the suggested online collection links from my professor) and searched for any texts related to “Durer.” As a primarily image-based collection, I knew that I would not need to use very specific terms to find the limited number of texts available and generate a manageable number of results. With less than 10 results in all, I identified early scholarly writings on Durer. Again, the Rijksmuseum served only as a starting point, since the texts I found were only available for pickup in hard copy at the Rijksmuseum in the Netherlands. But it did allow me to then conduct searches on alternative platforms, in this case, the University of Heidelberg Digital Library. As discussed in Alan Bilansky’s “Search, Reading, and the Rise of Database,” my goal was rapid “strategic reading” of sources at this stage of the project, and the database’s search tool made this task possible. Searching “Durer Selbstporträt 1500” in the University’s digital library (since most results were in German), I was able to quickly assess which digitized books would be appropriate to include in a corpus to feed into Voyant for text analysis.

Guides

Copyright and Terms of Use: What You Can Do with Digitized Sources

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One very crucial, yet sometimes overlooked, aspect of digital humanities scholarship is adherence to copyright law. While most researchers and scholars understand how to conduct proper attribution and citation in a traditional written research project, digital humanities projects often involve a wider range of audiovisual material which complicates this process by implicating lesser-known aspects of copyright law. Below is a brief guide which should hopefully assist those seeking to perform due diligence in regard to copyright when putting together their projects:

  • When browsing a digital collection, locate the copyright and terms of use information for the collection/organization/site as a whole before attempting to find copyright information for specific pages or objects on the site.
  • While the location of copyright information can vary widely by site, in many cases, you will want to look for pages such as “About,” “Policies,” “Legal Notices” or “Resources.”
  • Terms of Use/Service pages will most often be found at the bottom of each site page as part of a lower menu bar (usually accompanied by Accessibility, Contact Us, etc.)
  • The copyright information or terms of use for the site may provide a blanket policy for material on the site or may state that the copyright status of each object varies. You should also note whether the Terms of Use are intended to be legally binding or are meant to serve as guidelines. For example, you are not legally required to attribute a work that is in the public domain; however, a site may request in its Terms of Use that you still attribute the work nonetheless as a courtesy.
    1. Full copyright protections – The strictest terms of use include full copyright protection for the material. Unless covered under fair use (see below), the material cannot be used on your project without formal written consent from the copyright holder.
      1. Fair use exceptions include non-commercial use (such as for educational purposes), transforming or commenting on the material in some way, or only using a small, non-essential element of the work. Franky Abbott from Digital Public Library of America provides a great overview of the concept of fair use along with a helpful visual (start at 32:35).
    2. Creative Commons licensed – These are works whose copyright protections have not expired but the creator has allowed for reuse within certain parameters. Look for specific acronyms to determine how this material can be used. In some cases, you may freely reuse as long as you attribute to the original creator (BY). You may also see ShareAlike (SA) which tells the user of the material that they must reuse under the same license as the original, no stricter and no more lenient.
    3. Public Domain – A work in the public domain no longer has copyright protections and can be used freely in a digital humanities project. This could be a result of expiration or the creator’s choice to release their work into the public domain. It is important to determine whether the work is published or unpublished, as this distinction can determine when the copyright expires.
Definitions

A Definition of Digital Humanities

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After seeing how scholars have attempted to define and scope the term “Digital Humanities” over a course of a few decades, I will attempt my own definition based on the elements that I find most convincing:

Digital Humanities is a field of study centered on the development, use, and critical examination of computer-based tools and methods that expand the possibilities for interdisciplinary, humanistic inquiry. The goals of digital humanities scholarship are to digitally preserve the past and its cultural artifacts, increase access to knowledge, foster collaboration among scholars and with the public, and disrupt traditional barriers to academic publishing.

There are a few important features to note about this definition. First, I refer to Digital Humanities as a field of study, not simply a methodology or technique. This distinguishes my definition from early definitions, excerpted in Activity 2.2, that are mostly concerned with digital archiving of physical material as a supplement to traditional print scholarship. Instead, I believe Digital Humanities, as of 2026, has moved far beyond this notion to include theoretical frameworks and scholarly debate over issues and practices.

Second, as a field that has grown and matured over a period of 25+ years, I feel it’s important to state some (mostly) agreed upon goals of Digital Humanities. The fact that the field of Digital Humanities does have some explicit goals is representative of a move past the experimentation and defining phase of its development as a discipline. While there were certainly some more revolutionary goals described in a few activity excerpts as well as the Fiormonte, Ricaurte, and Chaudhuri reading, I decided to limit this portion of the definition to endeavors which I felt represented a common theme across definitions post-2010.

Lastly, I’ll simply add that my definition above attempts to strike a balance between inclusivity and clarity. This is a tension that existed in many of the more recent definitions of Digital Humanities – some definitions were so expansive that they almost become meaningless. For example, I did not find Rafel Alvarado’s definition (“The digital humanities is what digital humanists do…” [Activity 2.2]) to be particularly helpful for a new person who may be exploring this field of study for the first time.