The ultimate question that required an answer throughout this module was: why create data from humanities sources? Ultimately, the question of data lies in what the scholar seeks to discover. By creating data from your projects, one can find many aspects not previously understood from their work. One can discover patterns, relationships, and structures that are not apparent in reading the work. As Thomas Padilla shows in our readings, creating data creates greater possibilities for understanding and studying research. Using various tools such as data visualization, mapping, or spatial analysis allows large collections to be observed and comprehended far more easily than simple analysis. Specifically, I learned how complex and comprehensive data collection can be with our work on various projects such as the Tudor Networks, the Fairfax County Probate Records, and the Early African American Film. These projects highlighted this, but directly working with the Works Progress Administration Slave Narratives project and creating data specifically really made me realize how important creating data from documents, letters, and various other sources is to create a broader analysis field. In the case of the Slave Narratives, this data adds more humanity and greater emphasis on that individual story and how it connects to a broader context. Even though I only worked with three individuals, I felt a better connection to their story when I created their data. I also understood that with the right tools and sources, data creation is not as difficult as I once thought.

The questions that the data lets you answer that other methods do not are as follows: What patterns are seen throughout the given information?  What are the shifts and trends that occur throughout? What are common themes throughout the data? By creating data and answering these questions, the understanding of the subject is far greater than that of other projects.

When a scholar creates data from various sources, transparency is always key. The first aspect is transparency about how the scholar interpreted the data, whether it excluded certain items, created a common theme with names, and how the data was digitized. Normalization and the direct mention of this process are critical for the transparency of data creation. By explicitly stating how the data was developed and what factors created the data, the scholar creating the data has less ground for potential biases. Beyond the risk of biases, scholars can craft false arguments that would cause some to create the wrong conclusion. Specifically, stating what was undertaken to create the data and what was excluded is essential to the integrity of the field and the legitimacy of the scholar.

Before completing the metadata module, I had no real clue what metadata even was. I had heard the term used but had never truly engaged with it. Now, I fully understand its complexities and importance. A definition is essential to begin discussing metadata. Metadata is facts or attributes describing an item, such as a book, document, computer file, image, or artwork. These attributes are used to convey the digitized item and assist in the cataloging and processing digitized artifacts. Beyond this, it gives the item context in the greater field of research. Because of the nature of the current world, it is hard to access all material in person, and thus, the digitized image and its metadata assist immensely. In this unit, I digitized various items in my kitchen through photographs. The image below is of four skillet pans sitting on a stove. The metadata for this object is broken down into categories based on the Dublin Core metadata vocabulary. The critical pieces included are the title, the subject, a description of the photo, the source, the format, and the rights associated with the item.

This other photo was of many of the various coffee syrups and my toaster.

Using these images, I created metadata concerning the various dimensions of the photo and attributes of valuable resources such as Tropy, where I can store all of the images and the metadata surrounding them. After exporting the metadata to Omeka, I created a cohesive and well-organized exhibit of my digitized sources and utilized the metadata. This has been an amazing learning experience for me as I have discovered all of the valuable resources available for no cost and can improve the efficiency of one’s research. Metadata gives one easy access to the rights, format, type, original location, and where the item is stored.

Metadata is essential in the digital humanities because it provides an easy means of finding crucial aspects of media included in research. The key areas of particular importance to the digital humanities are prominence information or the original location and history of the item. Without this, the item merely becomes another ordinary object. As a historian, provenance is especially important in understanding the historical context.  Another key area of essential metadata is the rights of the object. When researching, one always has to be cautious not to violate copyright and fair use, and thus, having the rights information included with the data makes it far more simplistic. Finally, understanding the creator and where the item is currently housed is essential to digital humanities scholarship. Knowing where the object was digitized and is stored helps the researcher better understand the object within the archival context. Still, it also assists in understanding if any inherent biases are present. This is crucial because these biases could potentially harm one’s research.

Digital humanities scholarship also greatly benefits from the programs Tropy and Omeka. Tropy allows for importing all objects needed to catalog and create metadata in one central location, and the interface is highly accessible for the less technologically inclined. Storing these objects and creating metadata makes one step of the research process much more manageable. Using Tropy to create metadata also allows for the export of this data into Omeka. Omeka utilizes Dublin Core metadata vocabulary that is more detailed and provides more context to the items. Beyond this, Omeka allows digital humanities scholars to create exhibits to share their resources through a digital professional environment. Omeka is also important in the metadata organization and creates another central location for the research process. Overall, using, creating, and sharing metadata through platforms like Tropy and Omeka is pivotal to the digital humanities and the future of research.