When an artifact is digitized, the goal is to create consistent images of documents by converting an analogue signal or code into a digital signal or code (Terras, 2012). Through this process, any items accessible through photography, sound, and moving images can be digitized using various techniques (Terras, 2012). For example, in this module, I captured photographs of items from my kitchen for digitization, including still photos and videos of a recipe, a bowl of fruit, and a container of shelled and jarred beans. The representations I captured of these items varied, with the video versions offering a more comprehensive, contextualized view than the photographs.

Additionally, while the goal of digitization is to create consistent images of documents and artifacts, the process relies on artifacts that are “fundamentally individual and inconsistent” (Terras, 2012). Therefore, I cannot capture every aspect of an item during digitization, and the digitized item is not always a faithful representation of its image. Digitization can capture more information from a three-dimensional object, such as a bowl of fruit, than from a two-dimensional object, such as a typed recipe on paper. In the example of the bowl of fruit I photographed for digitization, several physical and sensory attributes were transferred, including the colors of the fruit, the relative sizes of the fruit pieces and the bowl, and even the texture of some fruit pieces. Compared with the digitized recipe, fewer physical and sensory attributes were transferred to this bowl of fruit. It is impossible to know how a recipe tastes, smells, weighs, or feels. The video versions of these items were more accurate in their representation, allowing viewers to see all sides of the items. Videotaping some items even provided the physical attributes of sound and scale. This process, however, was considerably time-consuming.

Working with digitized representations affects how we understand different kinds of items and our ability to use them for various purposes across several key areas. First, we need to recognize that the digitized images we access online are not always faithful representations of the original image. Second, we need to understand that the person who captured images or digitized items may or may not have been guided by standards in the process, as exemplified by the variations of the digitized image “Afro-American Army Teamsters” (Conway, 2009).

Third, we need to understand that digitized items are subjective and shaped by the digitizer. Conway (2009) argues that this is mediated by the relationship between the object’s maker and its viewer. Moreover, before digitization, the digitizer must determine whether the appearance is ideal for “certain viewing conditions”. For example, the Frey/Reilly Model shows how choices in the scanning process, based on the digitizer’s intent, can shape our understanding of a digitized image (Conway, 2009). For example, if the digitizer intends to represent an image as it appears, as in the “Ute Family” photo, the image is rendered As IS (Conway, 2009).

Fourth, we should carefully consider our interpretation of digitized items, as their meanings can be affected by the digitization process, from creating an archival master image to accessing derivatives. Image post-processing is a complex process, often with unexpressed goals (Conway, 2009).

Finally, the machinery of DH project funding constrains the range of DH projects funded, the digitized materials accessible, and the diversity of voices represented in DH collections (Terras, 2012; Terras, 2022). The DH agenda shift, increasingly driven by the economic and political landscape and by the desire for audience engagement (Terras, 2012). Consequently, funding of DH projects shapes and is shaped by visible and invisible agendas. As a result, for every digitized representation one chooses, one should consider which items are not digitized that might have provided a greater, more contextualized understanding of the image (Conway, 2009).