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On March 6, Lyneise Williams, Professor of Art History at the University of North Carolina at Chapel Hill, spoke with the Seminar about her work at the crossroads of computational archive science, art history, and material studies. Dr. Williams’ work involves analyzing visual representations of race; her book, Latin Blackness in Parisian Visual Culture, 1852-1932,  was published by Bloomsbury in 2019. In her talk with us, Dr. Williams pointed out that analyzing such visuals requires attention to reproduction, mediation, and digital surrogacy. In other words, when a reader of Williams’ book encounters an image of the 20th century Panamanian boxer Alfonso Teofilo Brown, they are not seeing the image itself—and certainly not the human depicted in the image—but, instead, a highly mediated reproduction. Certain details might be lost in translation, and the more often an image is reproduced, the more it is likely to deteriorate; thus, what we analyze is not only the image itself, but also its journey through space and time to get to our eyes. If you’ve ever watched a hilariously blurry Youtube video of something from the 1980’s you’re familiar with what’s called “generation loss” –the more copies exist from a single original, the less likely it is that you’re getting a truly representative visual. Dr. Williams’ described her ongoing difficulties with this issue, particularly as it applies to race. Most recently: when she studies microfilm scans of early-20th century newspapers, it is rare that adequate care is taken to preserve photographs within newspapers of Black subjects. While the words of the Read More

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In the midst of COVID-19 induced social isolation, with many institutions like museums closing their doors, digital surrogates are forced to temporarily take the place of embodied experience. While most of our distancing is temporary — for some objects, their surrogates are all we have. The weight that replicas have to bear is dependent on their function. If the original object is destroyed, through intentional or accidental means, the record of that original no longer serves as a finding aid — something that points the way to an attainable original. If our reproductions will serve in place of original objects, predicting what will be meaningful about the original is necessary, demanding, and maybe impossible. Such mindful practices are also undeniably worth it. Dr. Lyneise Williams has articulated the stakes of this issue well in, “What Computational Archival Science Can Learn from Art History and Material Culture Studies.” Why not just keep the original? Why put so much pressure on replicas? There are cases that require replicas to rise up to the task of “replacement.” Space is often an issue. Thousands of newspapers have been microfilmed, which is a much smaller and more stable form. The stability is also a key reason why originals are often not saved. Newspaper is produced cheaply, and the paper itself degrades over time. These concerns are not trivial, particularly since the housing of archival documents requires a stable environment (reminder: you shouldn’t store things you want to save in non-climate-controlled areas like basements or sheds). Sometimes it is impractical or even Read More

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In: Matthew Lincoln
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On February 7th, one of the Seminar’s very own participants headed our lunchtime discussion; Dr. Matthew Lincoln, a research software engineer at Carnegie Mellon University Libraries, talked with us about museum informatics, archive management, and computational approaches to humanities projects. Although his transition to software engineer is relatively recent, his experience with data modelling and analysis is definitely not—before his move to Carnegie Mellon, Dr. Lincoln earned a Ph.D. in art history from University of Maryland, where he used computational methods to study 16th-18th century Dutch printmakers. This, along with his work on data engineering at the Getty Research Institute’s Getty Provenance Index Databases, makes him uniquely attuned to multiple aspects of building data sets and archiving. As Dr. Lincoln himself articulated during his talk, using large data sets as a Ph.D. candidate—what he worded as the “available technology”—alerted him to particular data absences within library and museum holdings; in other words, researchers can only carry out the large-scale digital projects that data actually exist for. If you’ve ever searched for an eBook only to find that a digital version of this text does not (yet) exist, you know this feeling; it is, on a smaller scale, the same feeling a researcher might have if they, for example, wanted to compare one particular library system’s entire collection to another—but there is no usable data with which to do such a project. The project idea is there, the necessary data is not. This is where and why Dr. Lincoln’s job becomes so essential; his work has helped Read More

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While all of the Sawyer Seminar speakers so far have been scholars or users of information ecosystems, Matt Lincoln is potentially unique in coding them. His Ph.D. in Art History, time as a data research specialist at the Getty Research Institute, and most recently, work as a research software engineer at Carnegie Mellon University have given him substantial knowledge about museums’ information systems, as well as the broader context of the seminar. For Lincoln, “data” consists of collections of art and associated facts and metadata. In his public talk, entitled “Ways of Forgetting: The Librarian, The Historian, and the Machine,” Dr. Lincoln focused on a case study from his time at the Getty, in which he was working on a project restructuring the way art provenance data were organized in databases. Lincoln argued that depending on who the creator or end-user of the information would be (whether librarian, historian or computer), the way the data are structured can vary. A historian would likely prefer open-ended text fields in which to establish a rich context with details specific to the piece, whereas a librarian would opt to record the same details about every piece, and a computer would prefer the data to be stored in some highly structured format, with lists of predefined terms that can populate each field. On top of balancing these disparate goals, Lincoln cited a particularly poignant Jira ticket, which asked: “Are we doing transcription of existing documents or trying to represent reality?” This question might well be answered with “both” since the Read More