Beyond the Women's Building

This week, we took a more critical look at the process of discovery in collections and what methods are being tested to make it easier to find things in databases of visual information. It was interesting to look at collection access from a user experience design point of view; facilitating use of the materials is what I believe the core function of any collection should be, but often it is swept to the side with the assumption that anyone who gets as far as your search bar already knows exactly what they are looking for. This problem is often further exacerbated by the complexities of searching for images, whose indexing relies almost exclusively on the information found in their metadata. For example, if you were trying to trace the origin of the pigeon-breast silhouette of early 1900s women’s clothing, there is a slim chance that searching “pigeon breast” would bring up every example of this silhouette in a textile collection. In order for a catalog entry to show up with that search term, its cataloger would have needed to add those words to its description in some shape or form via tags, subject headings, or plain-text description. This is where semantic searching comes in, which requires some level of cultural understanding of a query on the part of an information retrieval system and not just simple 1:1 text matching. Unfortunately, while many commercial search engines utilize this function, not many search algorithms in collections management software are advanced enough to do so. 

We looked at two projects in particular that took a machine learning/neural network approach to ameliorating some of these difficulties: “Training the Archive” and IMGS.AI. Both projects center on the central idea of clustering as a form of determining relevance, which they are able to do via image recognition tools that can pull out details such as color, shape, and other purely visual features. To be quite frank, I was not very impressed with the use cases of either of these methodologies. Both projects identify the need for a method of determining visual similarity in search that does not necessarily rely on metadata, and I do agree that this is especially true for large volumes of images, but in my opinion the question of “what can we do with AI tools” seems to have taken precedent over “what problems are people actually having while navigating databases.” IMGS.AI uses sound information retrieval theory with a clever way of instantaneously incorporating user evaluation, but in practice, its interface is highly unclear and essentially amounts to a “hot or cold” game with the database. “Training the Archive” uses a similar clustering system to replicate the knowledge and aesthetic sensibilities of a curator, and while it is true that it was able to pick out some stylistically similar images, I think it’s a bit bold to jump to the claim that it has the potential to become “The Unbiased Curator’s Machine.” It’s an interesting thought experiment, but a very loaded way to present a tool that has its own set of problems with real-world consequences.

The project I thought was most successful was Mitchell Whitelaw’s “generous interface” for the Australian Prints and Printmaking database. With options for guided browsing and search, there are many different entry points into the same collection. In particular, I thought the subjects explorer was a fantastic visualizer for similarity that made image metadata abundantly clear in its interface. The more related a topic was, the more saturated it appears in the sidebar menu, making it very easy to jump between subjects and filter down results. While it requires structured inputs and may not be as flexible as the previous examples, I think the ultimate result is much more navigable and offers more utility to the way people are actually searching and browsing for materials.

I wish more repositories had a way to visualize links between people, organizations, topics, and collections that was so simple to use! The downside to this approach though, as with many tools that yield exciting results, is that it is highly labor intensive and that labor is practically invisible. For each of the 40,000+ works in this collection, each one already had clear, structured metadata with those links between artists and works already established. This is fantastic for a small to mid-sized collection such as this, but this process must be nearly impossible to scale (in a timely manner) for large institutions. For example, the collections I work with at the City of Raleigh currently number at over 35,000+ items accumulated since 1992. I can say from experience that I am constantly updating old descriptions, adding tags and subject headings, creating new scans and photos, and measuring objects in the collection, and there are still at least hundreds of subpar catalog entries that would lead researchers directly into dead ends. And that is just the size of a small local history museum- the North Carolina Museum of History has over 150,000 items in its collection, and huge institutions like the Smithsonian have millions. The sheer amount of labor required to standardize that volume of data is truly astronomical, and I’m not sure how we can create that level of utility and simplicity without either massive funding or the exploitation of GLAM workers- either directly or by training new tools on their work. 

I’ll admit, when searching for more collections interfaces to explore, I had a difficult time finding one to share! Not many had very robust exploration options, and most limited browsing to a collection-by-collection basis. I ended up looking at the collections website for the Indianapolis Museum of Art (my hometown art museum as a child), and found it to be pretty intuitive for browsing. On the landing page, there’s an assortment of featured works along with links for popular searches. I hadn’t seen a museum site that had that feature or that exact wording before, but it shows that they have a knowledge of what bridges already exist between their audience and their collection and a desire to encourage those bridges.

There are also easily accessible sections that show only open access or public domain images. The catalog is extremely clear about copyright, which can be so helpful. Often there is just a vague “the creator owns this” statement on catalog entries that is baked into cataloging systems.

I also appreciated that you can view past exhibitions from an exhaustive list, and that all works from the exhibition are represented. Most recent exhibition collections also have images of all of the works used where copyright allows, and catalog entries for every image contain information about its copyright. I wouldn’t say it’s a perfect interface, but it does have some pretty solid methods of exploration.

Bönisch, Dominik. “The Curator’s Machine: Clustering of Museum Collection Data through Annotation of Hidden Connection Patterns between Artworks.” International Journal for Digital Art History, no. 5 (2020): 5.20-5.35. https://doi.org/10.11588/dah.2020.5.75953.

Offert, Fabian, and Peter Bell. “IMGS.AI.: A Multimodal Search Engine for Digital Art History.” International Journal for Digital Art History, no. 9 (2023): 5.28-5.39. https://doi.org/10.11588/dahj.2023.9.91295.

Whitelaw, Mitchell. “Generous Interfaces for Digital Cultural Collections.” Digital Humanities Quarterly 009, no. 1 (2015).

            Digital collections are one of the most helpful research resources an institution can provide. Coming from the perspective of an art historical researcher, I typically arrive at a museum or cultural institution’s site knowing what I want to see. Not every museum site visitor is conducting research, though, and it is important for institutions’ digital collection searches to accommodate both audiences. Fabian Offert and Peter Bell, Dominik Bonisch, Tim Sherratt, and Mitchell Whitelaw write about new and past digital collections and interfaces that explore the potential of digital resources to effectively organize digital collection to be more user-friendly.

            Sheratt offers examples of how people can creatively use publicly available digital records in his article, “It’s all about the Stuff: Collections, Interfaces, Power, and People.” Written in 2011, Sherratt demonstrates the potential to push digital collections beyond only making them available online. One of his examples is the project “The Real Face of White Australia,” which he uses to explain how digital databases have the ability to turn records from tools of oppression to a restoration of humanity. In the case of “The Real Face of White Australia,” Sherratt and Kate Bagnall used photographs that government officials in the 19^th and 20^th centuries required non-white Australians—which included Chinese, Japanese, and Indian immigrants in addition to indigenous Australians—to submit so that they could re-enter the country if they traveled abroad. Because the National Archives of Australia digitized these records and made them public, Sheratt and Bagnall could use these photographs to create a searchable database and craft biographies for these people to offer a counter-history to the myth of a “White Australia.” This project demonstrated how digital records could be used analytically and to restore marginalized perspectives in history.

            Transitioning from Sherratt’s accounts of early forays into digital collection organization, Bonisch and Offert and Bell report on experiments with generative models to improve the intuitiveness of digital collections through pattern recognition. Bonisch explains an experiment using the massive, digitized collection of the Danish National Statens Museum for Kunst to create a model trained to “think like a curator.” Working in a bottom-up pattern, the artificial intelligence treats each separate piece as its own data point and gradually narrows it down based on similar visual features and metadata. Offert and Bell discuss the use of imgs.ai, an artificial tool also aimed at increasing the browse and searchability of several collections. Although it cannot search across collections, imgs.ai works with a few museums including the Rijksmuseum, the Metropolitan, and the Getty. This model begins by presenting the viewer with a random series of all the museum’s digitized images. The user can click on an individual image to see more images with similar features. In this way, the model keeps “a human in the loop” in its searches. From Sherratt’s early examples of using digital collections to create interactive, analytical databases, Bonisch, Offert, and Bell take the technology forward another step with generative technology creating and recognizing patterns between images.

            Exploring digital collections is essential for any student of art history. In my experience, the digital collections of the Metropolitan, Philadelphia Museum of Art, and the Rijksmuseum are particularly user-friendly for researchers—especially those that have a very clear idea of what they are looking for. While conducting research for my undergraduate thesis about a wardrobe with German decorative influences, I needed to search the collections of a few Swiss and German museums. From a book detailing the Historisches Museum Basel’s collection, I found the accession number of a wardrobe that I believed would be particularly helpful to include in my work. The collection site proved to be very accurate for finding that particular wardrobe. When I used the keyword “wardrobe” to search for more examples, the results were limited. The case was even more drastic in the collection search for the Bayerisches National Museum. This digital collection could only recognize German words (Fig. 1 and 2).

Fig. 1: Search results from the Bayerisches National Museum digital collection search using the keyword “wardrobe”

Fig. 2: Search results from the Bayerisches National Museum digital collection search using the keyword “schrank“

This small experiment between primarily German collections may only prove my own lingual Anglo-centricity, but it does introduce another challenge to organizing and improving the accessibility of digital collections. Is there a way for metadata attached to images to be easily translated? In a world where digital and online spaces can feasibly grant access to collections from any corner of the globe, will language still be a barrier? Or will tools that primarily use visual features, like imgs.ai, mitigate this problem?

            Digital collections are important for institutions not only for research but to grant accessibility to all. This not only includes academics, but also the casual browser. While collections databases should be able to execute advance search functions, institutions should also provide intuitive and engaging interfaces to browse through. Whitelaw discusses this idea in his article “Generous Interfaces for Digital Collections.” Whitelaw praises the intuitive nature of the Rijksmuseum website and offers a few examples of user-friendly interfaces in Australia including “Discover the Queenslander,” a magazine archive, and “Manly Images,” a series of digitized images in the collection of the Manly Public Library. I think that the Rijksmuseum is also a great example of an institution that balances accurate, thorough, and intuitive search functions with engaging content for the casual browser. Its “Art Explorer” tab is particularly exceptional because it provides prompts to encourage leisurely audiences to interact with its collections. In the future, I think that institutions should look to the Rijksmuseum’s website as an example for both leisurely browsing and detailed searches.

            After this week, I firmly believe that digitized collections should be accessible to academics and general audiences alike. Bonisch and Offert and Bell’s articles highlighted the potential to make digital collections even more user-friendly while Sherratt’s article the great work that digital collections management has already accomplished. Whitelaw emphasized the necessity of “generous” interfaces to de-mystify searches and encourage browsing for general interest. Moving forward, it will be exciting to see—and even participate in—the new methods that institutions will discover to make their collections even more engaging and accessible to the world.

6 September 2026

It is no surprise that the global rise of the Internet since the late 1990s has ushered in the era of online, digitized collections from art museums around the world. From the expansive collections housed at the Metropolitan Museum of Art in New York and the Louvre in Paris to the comparatively smaller collections housed at institutions such as the Ackland Art Museum in Chapel Hill, NC, art museums have increasingly digitized their collections to make them more accessible to the public. But are these collections really more accessible? Who is the “public” that are using these online collections? Are some collections more accessible to members of the public with a higher prior knowledge of art and art history than others?

For this week’s blog post, I am going to take a deep-dive into Michael Whitelaw’s “Generous Interfaces for Digital Cultural Collections”¹, a 2015 article that examines the user interfaces (UI) of various online digital collections for usability. More specifically, I will examine a handful of online collections in 2026 using the same metrics Whitelaw uses in determining the user-friendliness of his chosen collections. 

At the conclusion of the article, Whitelaw supports what he refers to as “generous spaces” in UI design, defining them as providing “rich, navigable representations of large digital collections; they invite exploration and support browsing, using overviews to establish context and maintain orientation while revealing detail at multiple scales.”² In other words, the most effective digital collections are paired with UIs that are a middle-ground for scholarly research and casual browsing. Generous spaces are ones that prioritize both collection search-ability and spontaneous discoveries, catering to a wide array of potential online users. 

As an art historian, I typically visit an online collection with a specific work in mind, therefore using the collection to find that item. Rarely do I visit an online collection to browse casually. I open up the webpage, find the search feature, and type in the information I already know about the work I am searching for. Any results beyond this work are purely superfluous in my search, and many times non-related objects actively hinder my search if my search parameters are not detailed enough. For example, when I was working on a project on the statuette of Juno housed at the Ackland Art Museum, I often consulted the museum’s “eMuseum” to double-check information. The collection UI opens up to its main page, which is headed by a search box and a “View All Works” button. As someone with a specific object in mind, I usually just typed “statuette of Juno” into the search box and it eMuseum returned the object I was looking for.

But this isn’t the case in all instances. As someone who works with ancient Mediterranean antiquities, many objects lack official titles and are instead given descriptive names such as “Marble Portrait of a Young Woman” or “Monumental Hydria”. These names make it difficult to search for specific objects, since the names are more subjective than Leonard di Vinci’s “Mona Lisa” or more recent works of art. If I search “Statue of Woman” on the Met’s online collection, I get nearly 2,500 results without adding any additional filters or terms.

So what actually makes a digital collection a “generous space”? Despite my apparent bashing of the Met’s online collection above, it actually does a reasonable job at catering to both search-focused users and browsing-focused users. On the collection’s homepage, users are given the option to search the collection via a standardized search bar (1) or browse the collection in a variety of ways. The Met consolidated its highlights under the “Highlights” tag (2) and also gives the options to search for only images in the public domain (3) for artists and other users interested in using their images for reproduction or re-imagination. Moreover, users can browse by individual subject collection (4)—which for the Met groups objects by the room or wing of the building they are located in.

The Ackland’s eMuseum is less of a generous space than the Met’s, as it lacks a clear browsing feature beyond dumping the user into a “View All Works” spaces. For the Ackland, this directs users to more than 22,000 works of art that require additional filtering—an overwhelming experience for many casual browsers. Of course, the Ackland has a much smaller online collection than the Met (~22,000 works vs ~535,000 works) and fewer resources to work with to develop their digital platform. 

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With the previous online collections explored and critiqued, it is time for me to turn your attention to one of my favorite digital collections: the Beazley Archive. Run by the Classical Art Research Centre (CARC) at the University of Oxford, the Beazley Archive is an online database version of Sir John Beazley’s classifications of Greek vase painting, which were published as volumes in 1942³ and 1956⁴. The database started as a visual companion to Beazley’s volumes, since they originally contained no images. 

Today, the database holds more than 137,000 individual records of Greek vases which are accessible through a variety of search formats. The original search feature—dubbed “Traditional Search”—is an HTML-based search engine predominantly used by older academics. There is no room for casual browsing in this search feature, as the tool requires specific information to locate vases.

Beyond this feature, “Advanced Search” is more geared towards search-ability and “Basic Search” is geared towards browse-ability. “Advanced Search” provides more options for filters than “Basic Search” does, allowing those with more knowledge of the online collection’s holdings to navigate for specific objects. “Basic Search” presents the user with eight options for an initial filter, allowing them to narrow down the 137,000 options by a single metric rather than a series of them.

Once an initial filter is applied, the Beazley Archive returns a page of images, allowing the user to filter through them by visual marker rather than metadata information. Below is an example search for vases in the hydria shape using the Simple Search. In this case, “Shape” was selected as the category from the list of options (see above, left) and “hydria” was selected as the shape. There were 3,418 results for hydriai in the Beazley Archive.

If these search options seem like too much for a user, the Beazley Archive also has a “Show a sample vase” button that will randomly generate a record from their collection, giving users a taste of the collection’s holdings. This button can be pressed as many times as desired, generating a different vase each time.

1. Michael Whitelaw. “Generous Interfaces for Digital Cultural Collections.” Digital Humanities Quarterly, vol. 9, no. 1 (2015). ︎
2. Whitelaw, paragraph 46. ︎
3. John Beazley. Attic Red-Figure Vase-Painters. Clarendon Press. 1942. ︎
4. John Beazley. Attic Black-Figure Vase-Painters. Clarendon Press. 1956. ︎

Week Three, 9/2/2026

In class this week, we’re considering how artificial intelligence could aid or impact digital collections. To preface, I am generally skeptical of the utility of AI (particularly consumer-facing AI like Chat GPT), and am one of many who are concerned about the kind of future the technology might bring about. Even if you set aside the massive ecological impact that AI will have on our planet—which is a lot to set aside—the daily use of these technologies holds clear ethical issues. It is frequently implemented to devalue human labor, devalue learning, and to infringe upon artistic ownership. Nonetheless, the technology itself is one of many new digital tools, and in the right hands it can do really interesting things. When considering viable and meaningful implementations of AI, one that immediately comes to mind for me is archival work.

In one sense, digital archives (and data management in general) present an ideal use case for machine learning/AI. The job of a digital archivist is to sort large amounts of data and metadata, often with different media types linked to one object. One thing that machine learning is good at, even the consumer-facing large language models, is compiling huge amounts of data and making sense of it in a manner that a person can more easily digest. The other major task of an archivist is to identify what an object, artwork, or document actually is; of course, image recognition is another popular use of AI technologies.

However, the focus for this week was not on how AI might be able to aid the internal work of archivists, but rather, how it can aid us in creating more dynamic, accessible, user interfaces. In particular, two of the digital projects we read about each utilized AI to showcase the formal similarities between different images in a larger cluster of images. One project was Imgs.AI, which allows users to search pre-existing collections—like the Met or the Rijksmuseum—by choosing images that they’d like to see more similar objects to.¹ The other project, “Training the Archive,” utilized a similar technique, wherein machine learning models were trained to make visual associations between images before generating a map or a schematic, grouping similar images with one another. Both projects take a human’s ability to recognize similar images, and an art historian’s finely honed ability to do so, and automates it to the end of quickly generating a schematic of images. 

In the other AI digital collections project, “Training the Archive,” the machine learning model was trained from theories of the German art historian Aby Warburg (1866-1929). In order to train this model, project leader Dominik Bönisch notes that: “a procedure had to be implemented that would enable curators to connect digital collection objects with one another according to specific (…) criteria for context, aesthetics, iconography, and art historical references.”² (Bönisch, 26)

At the present moment, it seems that there is a distinct ceiling on what machine learning can contribute to digital archives, digitization, and user interfaces, and further, I believe that there will continue to be. As Dr. Bauer noted during class, each and every one of these projects still require human intervention, and I expect this will continue to be the case. At the very least, humans still need to be present as editors and fact-checkers. Though Bönisch ends his article by declaring that “AI is also suitable for the automated processing of the collections.” (Bönisch, 29), I am not so sure that this is currently the case. Further, digital collections managers and archivists have been creating dynamic and impactful user-interfaces without the use of AI for decades now.

Each of the impressive digital archiving projects referenced by Tim Sherratt in his 2011 article  “It’s all about the Stuff: Collections, Interfaces, Power and People,” were created prior to the popularization of artificial intelligence, and the expertise of curators and archivists come to the fore in each of these projects. 

Virginia Untold: The African American Narrative is one particularly effective example of how archivists can make records legible and accessible to audiences. By providing high-quality scans, grouping items together by theme or relevant historical event, and attaching explanatory texts to collections, archivists shaped legal documents and letters into an accessible narrative for general audiences and researchers alike. Users are also able to easily save certain documents to read for later by “pinning” them to their account.

As alluded to in my last posts, digitization is a laborious and often boring process. That being said, it is a process that is completed by interns, students, and volunteers, alongside professional archivists with library science degrees. I fear that what is at stake here is not the implementation of AI to make those laborers’ jobs easier and more impactful to the public, but rather, a proposition to replace them with machine labor as much as possible. Though a novel and potentially useful technology, the introduction of AI and machine learning will not solve the systemic issues that our field continues to face. Prior to introducing these new technologies, we ought to re-assess the technologies we already use, and give archivists the resources and training needed in order to be digitally literate. In my opinion, the systemic underfunding of our field is at the heart of this struggle to create exciting and accessible user interfaces.

1. Fabian Offert and Peter Bell, “Imgs.AI. A Multimodal Search Engine For Digital Art History,” International Journal for Digital Art History (vol. 9, 2024) ︎
2. Dominik Bönisch. “The Curator’s Machine: Clustering of Museum Collection Data Through Annotation of Hidden Connection Patterns Between Artworks.” Digital Art History Journal (May 4, 2021) ︎

Scanning this image from Vermis I: Lost Dungeons and Forbidden Woods by plastiboo¹ made me consider the layers of processing necessary to make a reproduction similar to the original. To get this image to come close to the original image in Vermis, I had to not only use a high-resolution scanner with the matching software, but to distort the original itself. I had to hold the book at an awkward angle, pressing it against the glass of the scanner enough to grab the image clearly without causing the spine to crack or the pages to be damaged (While this was with my personal copy of Vermis and I do not mind a cracked spine and other signs of wear, I wanted to practice as if it were not my own book). Using a paperback copy likely helped this process but I still would have had to take additional time if I had wanted the complete page, as parts of the full page were cut off or too shadowed. Even with the portion clearly scanned, I had to add a sepia photo filter to achieve the closest possible reproduction of the original in the time allotted as the scanner had dramatically brightened the image. I also had to add a Gaussian blur in Photoshop to smooth the honeycomb texture the scanner adds to books.

Emma Stanford in “A Field Guide to Digital Surrogates” explains the long lineage of reproductions, photographs, and other surrogates used in the study of art history.² Perhaps more importantly, Stanford argues that these surrogates often go unnoticed. They are such a necessary part of our study and pedagogical process that we no longer think of them as imperfect substitutions. If we do notice, we often do not think of just how distant our surrogates remain from the original artwork.

How far removed is my scan from the original image? Removing it from the book takes it out of context. It is also removed from the surrounding page graphics and faux signs of use that were cropped out. While that doesn’t make it useless for study, its use is not the same as the original image.

I can zoom in on the scanned image.

I can view it directly beside a comparison image.

But what happens when the reproduction is all that remains of a work or the only accessible version?

I have mixed feelings on video game emulators. I acknowledge that they are invaluable for making video games accessible and have amazing archival potential. Despite legal challenges, emulators may be the only cost-effective, practical way to preserve some games. Still, what is lost when we consider a video game as software alone? Hardware is an important part of video-game art, whether the game is played on a console or a computer. Compatible hardware may no longer exist for the original physical game, making emulation a practical means of preserving access. Yet an emulator is still a surrogate, not a complete replacement for the original. Treating the code or software as the game itself can overlook the role of hardware in shaping the experience.

When an exhibit uses the same generic controller and display for all the games presented, what changes? Are the awkward shape and biting corners of an NES controller part of an NES game? I don’t believe there is a blanket answer to every exhibit, game, or situation. Without asking the question, we don’t explore other options.

How deep should the layers of surrogacy go? If original hardware could not be sourced, STL files for 3D models of consoles and controllers could probably be found. Is a printed hardware replica helpful surrogate or deception? Nintendo attracted considerable criticism after visitors discovered that its official museum relied on PC emulation.³ Nintendo has a long history of holding their copyright with an iron fist, pursuing legal action against mods and emulators. But when faced with presenting its own history, Nintendo also had to rely on the same surrogates used by game researchers to access their back catalog. Instead of facing this paradox, they attempted to hide it, using system controllers fed into a wall with the screen embedded above.

Even when the layers of surrogacy are not deliberately hidden, thinking of emulation in the same space as a slide projector in an art class calls into question what is included and what is excluded from the experience. The Internet Archive hosts playable MS-DOS games in it’s Software Library (Sorry not sorry for ruining any plans you had this evening if you didn’t know about this resource already).⁴ When you click play on a game, after a brief modern download screen for the emulator, a super-speed version of the DOS process of opening a DOS game flashes by. Are there circumstances where you should still have to type in the path in the blinking white text of the black DOS box while you frantically try to find the scrap of paper you wrote your save extension on? Should this process be part of the emulation? Should original load times or run times be emulated? Would doing so bring something valuable to the experience of video games as art? Would this surrogacy of nuance of experience be valuable or deceptive since modern technology does not require these processes?

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1. Plastiboo, Vermis I : Lost Dungeons and Forbidden Woods : Official Guide, ed. Michele Nitri, with Marco Cirillo Pedri, Vermis 1 (2023; 11th printing, Hollow Press, 2026), Paperback (Regular Edition).︎

2. Emma Stanford, “A Field Guide to Digital Surrogates,” in The Routledge Companion to Digital Humanities and Art History, 1st ed., ed. Kathryn Brown (Routledge, 2020), https://doi.org/10.4324/9780429505188-19.︎

3. Andy Edser, “The Official Nintendo Museum Appears to Be Emulating SNES Games on a Windows PC, Which Is Slightly Embarrassing,” Hardware, PC Gamer, October 14, 2024, https://www.pcgamer.com/hardware/the-official-nintendo-museum-appears-to-be-emulating-snes-games-on-a-windows-pc-which-is-slightly-embarrassing/.︎

4. Internet Archive, “Software Library: MS-DOS Games,” Software Library: MS-DOS Games, accessed August 31, 2026, https://archive.org/details/softwarelibrary_msdos_games.︎

           

I decided to digitize a photograph of my dog, Jax, this past week in Digital Art History. In this educational exercise, I practiced how to properly scan, digitally adjust colors, and write alt text for this digital reproduction of Jax’s photograph. This experience gave me insight—albeit on a micro-scale—of the digitization protocols of museums, libraries, and cultural institutions.

Digitization is a crucial step forward for museums, libraries, and cultural institutions to broaden access to their collections. In the book chapter “A Field Guide to Digital Surrogates: Evaluating and Contextualizing a Rapidly Changing Resource” Emma Standford explains the history, best practices, challenges, and potential of digitization for museums and cultural institutions. Digitizing collections creates the potential for broader access to art, documents, and objects.

Digitization is inherently a surrogate for the original, whether it’s a digital copy of a painting or a digitized photograph of a living, breathing golden retriever. Surrogates are not new to the field of art history. As early as 1890, Herman Grim integrated a lantern slide projector into his lectures, using projected images as surrogates for works of art and architecture.[1] Digitization and digital photography allowed the transition from physical slides to digital projected images in the art history classroom. Even more advanced technology and software development allow for interactive methods of viewing objects or architectural spaces. It is impossible to digitally re-create the experience of viewing an object in-person, but the versatility of digital surrogates also grants viewers access to different methods of interaction with an object.

Digital-storytelling is a popular way to interact with the digital surrogate of an object. It primarily serves an educational purpose. In class we viewed an example of the collaborative software of the International Image Interoperability Framework (IIF), the Victoria and Albert Museum’s Compariscope that allows viewers to overlay The Night Watch by Rembrandt van Rijn over the artist’s original sketches. This tool encourages users to study the artist’s process and transition from a first sketch to the final painting. In a previous art history course, I also played with the publicly sponsored “interactive documentary” Jheronimus Bosch, the Garden of Earthly Delights, which creates an audio-visual experience for the user. [2] It pairs music with specific scenes in Bosch’s triptych, offers explanations for details in the painting, and allows the viewer to closely examine the work. These digital resources are not analytical in nature, but, as digital-storytelling tools, they do help share scholarly research in the classroom and the museum.

            Besides its educational advantages, digitization ultimately improves and broadens access to an institution’s collections. As a student with experience working in archives and special collections libraries, I have participated in digitization projects and witnessed their utility. For example, I scanned large, old, and fragile land survey maps for the Newport Historical Society while working in the Salve Regina University Archives. This project presented a few nuances to digitization that Stanford also elaborates upon in her chapter.

First, the necessity to update and improve the image quality of the digitized maps indicated institutions’ ongoing struggle to keep up with the most current technology. Stanford noted that even since the advent of digital photography, there are clear improvements in image quality from an object digitized twenty years ago and five years ago. [3] I learned that the Newport Historical Society had also already digitized the maps, but the University recently acquired a scanner that could capture significantly more depth per square inch. The Newport Historical Society’s decision to re-scan the maps demonstrated the necessity to maintain and update digital collections as technology improves.

Another factor influencing an institution’s digitization practices is access to the proper technology. In the case of the Newport Historical Society maps, it involved reaching out and collaborating with another institution, the Salve Regina University Archives. This may be an optimal solution for smaller, local institutions, but the wealth and resources available to an institution affects the quantity, quality, and type of objects in a collection that get digitized.

Stanford argues that determining what and how objects or documents are digitized is inherently subjective.[4] Although large institutions may have the financial autonomy to run their own digitization experiments, most non-profit institutions rely on private or corporate donors or grants. This ultimately affects what museums choose to digitize because access to essential funding may be at stake.

            Hans Haacke outlines the precarious position of museums between independence and accountability to donors in the chapter “Museums: Managers of Consciousness” in the book Grasping the World: The Idea of the Museum.[5] Haacke explains that museums are inevitably political institutions since they are accountable to those—either through public, government grants or private, corporate sponsorships—that control funding.[6] This makes the operational decisions of museums, like choosing what and how to digitize a collection, dependent on the source of funding for the project. In the case of corporate sponsorships, Haacke considers, museums may face even greater pressure to produce impressive, “box office” exhibitions.[7] This similar self-censorship is also true for digitization projects. Digitization projects, like exhibitions, are stuck between aiming to provide greater access to their collections while also molding projects to fit within a grant’s parameters or to appease a private donor or corporate sponsor.

            Despite digitization’s inherent subjectivity, responsiveness to new technology, and dependence on adequate funding and resources, it is clearly a significant benefit for museums, libraries, and cultural institutions that grew from the rapid technological advancement of the last twenty years. Digitization increases access to art, objects, and documents (and photographs to pets!) while also facilitating the creation of digital humanities projects. The challenges to digitization are great, but the potential for broadened access to collections for research, education, and even just general interest is worth the effort.

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[1] Alison Langmead, “Art and Architectural History and the Performative, Mindful Practice of the Digital Humanities,” Journal of Interactive Technology and Pedagogy, no. 12 (February 2018), 2.

[2] Pieter van Huystee Film, NTR, Jheronimus Bosch, the Garden of Earthly Delights (Pieter van Huystee Film, NTR, 2016), https://archief.ntr.nl/tuinderlusten/en.html#.

[3] Emma Standford, “A Field Guide to Digital Surrogates: Contextualizing a Rapidly Changing Resource,” in The Routledge Companion to Digital Humanities and Art History, ed. by Kathryn Brown (Routledge, 2020), 206.

[4] Standford, “A Field Guide to Digital Surrogates,” 205.

[5] Hans Haacke, “Museums: Managers of Consciousness,” in Grasping the World: The Idea of the Museum, eds. Donald Preziosi and Claire Farago (Routledge, 2020), 400-412.

[6] Haacke, “Museums: Managers of Consciousness,” 407-408.

[7] Haacke, “Museums: Managers of Consciousness,” 409.

30 August 2026

This week I have chosen to focus my blog post on Emma Stanford’s “A Field Guide to Digital Surrogates: Evaluating and Contextualizing a Rapidly Changing Resource” (2020) because of my own interest in and past use of digital surrogates in art history. The article briefly highlights the history of digital surrogates—especially through photography—and the inequalities in the materials available digitally to the public. 

Especially noteworthy is Stanford’s note on the materials chosen for digitization being influenced by the person or group funding the digitization project, such as the digital collections of the Bodleian Libraries at the University of Oxford being in-proportionately slanted towards Hebrew manuscripts due to significant funding by the Polonsky Foundation from 2012 to 2017¹ . While this is not inherently an issue since libraries and museums are often tight on funding for digital projects, external funding does prioritize certain objects over others for digitization, potentially feeding into the historic cycle of certain areas of art and history being prioritized over others. In particular, objects associated with non-Western histories and cultures have historically received the short end of the stick in digitization, as there are fewer external foundations to privately-fund projects. This being said, is some digitization—even if it is not proportional to an institution’s overall collection—still worth accepting external funding for as opposed to no digitization?

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I would like to turn the remainder of this blog post towards another topic discussed by author Emma Stanford: the the unique difficulties that arise when digitizing three-dimensional objects into a (mostly) two-dimensional digital format. Stanford alludes to this idea when she discusses the pitfalls of digital reproductions, writing “a two-dimensional digital surrogate of that object is frozen at a particular angle, under a particular light, and presented with a particular viewing experience in mind.”². Since three-dimensional objects are intended to be viewed from multiple angles, capturing a two-dimensional snapshot of the object only digitizes a single viewing angle. Details—both significant and minute—are lost in two-dimensional reproductions of three-dimensional objects. 

Take Bernini’s The Rape of Proserpina (1621-1622) for example. Now housed at the Galleria Borghese in Rome, the sculpture stands 116 inches (295 cm) in height and is displayed towards the center of a room, allowing visitors to walk around it and view the sculpture from all sides. From first glance, Bernini’s sculpture is an emotional, intricate depiction of the mythological tale, showcasing a terrified Proserpina as she is abducted by the god Pluto and dragged to the Underworld. She famously cries out as she is caught, the essence of which was rendered in her facial features by Bernini. Any viewer of this sculpture in-person would likely take the time to circle the work, identifying the minute features carved by Bernini that give insights into the emotions of the individuals portrayed.

center of the image, not Proserpina—Bernini’s sculpture when viewed from the back shifts the attention to Proserpina. From the back, she is the central figure with the highest range of motion and emotion, not Pluto. Proserpina is physically higher than Pluto is due to her outstretched arm, drawing the viewer’s eye towards her. Moreover, the intricate movements in the fabric of her clothing highlight the surprise she felt as she was suddenly abducted by Pluto, as she is clothed from the back but nude from the front—suggesting she was caught in a state of surprise. 

In reproducing only one vantage point of Bernini’s The Rape of Proserpina, Nicholas Dorigny’s engraving cuts out parts of the story told by Bernini—whether intentionally or unintentionally. Viewers are forced to see the story from a single perspective, mimicking the physical viewing experience relegated to a single perspective as well. Modern photographs still do the same thing. Photographs of Bernini’s work continue to exclude certain aspects of the three-dimensional sculpture. Many images taken from the same vantage point as Dorigny’s engraving completely exclude the inclusion of Cerberus beneath Proserpina, an important contextualization for the work’s story. The pressure with which Pluto grips Proserpina is also often missing from two-dimensional reproductions of the sculpture, as indicated by the strong grip he holds on her upper left thigh. 

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For the second part of my blog post I was tasked with uploaded scans completed earlier this week in class. We completed a digitization workshop in which each student scanned an image and a body of text of their choice. Adjustments were then made to the digitized files as needed in Photoshop, including cropping and minor color adjustments (for the image) and a very-unsuccessful attempt at OCR for the (handwritten) text. Apparently my handwriting is not legible to Adobe Acrobat.

Below is a scan of my reading notes from my museum studies seminar this semester. They come from an article assigned for reading: Carol Duncan and Alan Wallach, “The Museum of Modern Art as Late Capitalist Ritual,” in Preziosi and Farago, eds., Grasping the World, Part V, chapter 1.

I wouldn’t recommend you download them, unless you have a particular interest in Marxism and museum studies.

1. Emma Stanford, “A Field Guide to Digital Surrogates: Evaluating and Contextualizing a Rapidly Changing Resource,” Routledge Companion, pp. 205.  ︎
2. Stanford, pp.207. ︎
3. Rossi, Domenico de’, “Raccolta di statue antiche e moderne: data in luce sotto i gloriosi auspici della Santita di N.S. Papa Clemente XI.” Stamperia della Pace. Rome. 1704. Available online via Internet Archive. ︎

This week’s readings and activities were right up my alley- ever since beginning my career transition to cultural heritage four years ago as a volunteer cataloging and digitizing local history, the question of whether or not surrogates are effective has been a pressing question to me. As someone who also has a hefty background in more technical image processing as a compositor, the bits and bytes we use to represent ourselves, our stories, and our society have certainly framed a lot of the ways that I approach cultural heritage. To create, in one form or another, is to abstract. But how many layers of abstraction and how many copies of copies can exist before they become something different altogether? It’s quite a philosophical topic, and Emma Stanford’s article “A Field Guide to Digital Surrogates” did a fantastic job in laying out the points of interest in this discussion succinctly. 

Of course, no conversation about representation of an original is complete without at least acknowledging Walter Benjamin. The conversation of how accurate a surrogate could possibly be has its genesis in the advent of the publicly accessible camera; now that any person can capture an accurate image, what purpose does the original serve? Benjamin’s response (the concept of “aura”) points to the unique physicality of viewing originals, and nearly a hundred years later, we still unequivocally prefer to see the original, regardless of medium. Stanford, however, classifies this as a fundamental (if common) misunderstanding of what the purpose of a surrogate for an art object is. It is neither “a perfect substitute or […] a threat to the original’s authenticity”: It is a tool for delivering a singular perspective of a three-dimensional object, which comes with its own set of pros and cons. As we move beyond simple 2D recreations of objects and into the realm of more advanced digital surrogates (such as the parallax viewer tool created by the Victoria and Albert museum that we explored in class), these questions are pushed back to the forefront of the field. Whether or not more advanced surrogates will actually advance the study of art history seems to be the focus of exploration in this course.

Stanford also touches on something absolutely vital to the creation of advanced surrogates for long-term use: longevity. From an archival standpoint, we have been inundated since day one with the mantra “the archivist is not neutral,” and the same goes for collecting institutions of all kinds. What gets saved, acquired, processed, and made accessible is a slice of a slice of a slice of the overall experience of humanity. I’ve always appreciated Michelle Caswell’s quote, “Not all events ­are recorded; not all records ­are incorporated into archives; not all archives ­are used to tell stories; not all stories are used to write history. Power is implicated in each of these moments; which stories get told, which get for­got­ten, when, and by whom, is inextricably linked ­to the power to tell and to remain silent.” The introduction of power into the equation makes these choices of what and how to digitize that much more pressing and complex. When we take into account the resources necessary to maintain surrogates long-term, this problem further devolves into a case of the haves and have-nots. So, from step zero, there is a massive amount of push and pull from external sources that clouds our ability to answer the question of efficacy. Stafford also echoed a sentiment that anyone who has ever worked with digital objects of any kind has encountered; the tools are arbitrary, and it is the fundamental way of approaching a specific problem that ultimately determines how successful the result will be. 

In taking the time to explore what it takes to make a clean, high-quality, and accessible static digital image, we got to experience first-hand how some of these small decisions quickly shape the experience of the surrogate’s viewer. I brought in a book I purchased for an art history course nearly a decade ago titled The Downtown Book: The New York Art Scene 1974-1984 because I was kind of tickled by the idea of reproducing an image from an era focused on what it means to reproduce, re-contextualize, and re-appropriate an image. I scanned a page with one of Barbara Kruger’s untitled works from 1981 (Your gaze hits the side of my face) printed on it, and got to see firsthand what was lost in the interaction. For instance, when on exhibit, the work is placed in a frame painted bright red- her signature accent color for this era of her work. The frame’s vibrancy only partially made it into the image in the book, and when scanning the image in the book, the stark red border was only further diminished by my (somewhat rushed) cropping job. Frames are such a large part of presentation, and Stanford even describes them in the article as a context clue for the larger meaning of a work. Sure, it’s just a thin, red border, but red is such a prominent part of Kruger’s visual language and seeing it get smaller and smaller in this exercise made me a little sad! Some artifacting from the book’s printing was also included in the scan; there is an inherent graininess to the work, but this scan overly exaggerates its texture. I played around with frequency separation (a retouching method used often for skin in beauty photography) as a method of reducing texture, but ultimately found that separating the grain of the image from the grain of the book’s printing to be nearly impossible. 

I was, however, much more satisfied with the scans for two additional items that I brought in to compare how digitizing printed and original works differed. The postcard I brought, which was another printed material, had a similar result as far as added texture and graininess. In this case though, the artifacting present is much more in keeping with the nature of a cheaply printed souvenir photo postcard. I also know for a fact that many, many photos have been taken of this exact angle of downtown over the years (I’ve encountered many a Raleigh skyline postcard in my years with the City’s special collections), so the “aura” of the photo and of the original view feels less important in the digital reproduction from my perspective. I was also quite happy with how the scan of my linocut print (one of my very first) turned out. As a print, which is technically another type of “copy,” I feel like this surrogate comes pretty close to the original intent for the viewing of this work, and I felt a lot more confident being able to edit it myself to fit that view. I wonder if in today’s age, digital reproductions (from living artists, at least) are best obtained from the artist themselves? I think if artists were included in the determination of a “particular interpretation” of their work, as Stanford describes, it would be more accurate; the idea of digital surrogates suddenly becomes much more feasible for artists currently working.

Benjamin, Walter. “The Work of Art in the Age of Mechanical Reproduction.” In Illuminations, edited by Hannah Arendt, translated by Harry Zohn, 217–251. New York: Schocken Books, 1968.
Caswell, Michelle. “Archiving the unspeakable : Silence, memory, and the photographic record in Cambodia.” University of Wisconsin Press. 2014
Stanford, Emma. “A Field Guide to Digital Surrogates.” In The Routledge Companion to Digital Humanities and Art History, 1st ed., edited by Kathryn Brown. Routledge, 2020. https://doi.org/10.4324/9780429505188-19.