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Beyond the Heroic Age of Antarctic Exploration: Navigating the Past at the Polar Museum

Mohammad Abu Al Hasan reflects on Antarctic legacies in the museum landscape.

How can museums effectively mediate the human history and heritage in Antarctica? Which curatorial strategies may help to bridge the vast geographical distance and foster public connection with the Antarctic continent?

Wie können Museen die Geschichte und das Kulturerbe der Antarktis wirkungsvoll vermitteln? Welche kuratorischen Strategien können dabei helfen, die enorme geografische Entfernung zu überbrücken und eine Verbindung der Öffentlichkeit zum antarktischen Kontinent herzustellen?


The Polar Museum of Scott Polar Research Institute (SPRI), University of Cambridge.

As a recipient of the 2025 Cambridge-Leibniz Museum and Collection Fellowship, I arrived at the Scott Polar Research Institute (SPRI) in the University of Cambridge. My main project at the German Maritime Museum (DSM) focuses on Protecting and Managing Antarctic Heritage, so my fellowship research investigates how these far-reaching heritages are communicated in the museum space.

From the moment I walked into the Polar Museum of SPRI’s main building, I understood this was no ordinary institution. The grand entrance hall’s wall bears the final, poignant words of Captain Robert Falcon Scott: ‘Had we lived, I should have had a tale… These rough notes and our dead bodies must tell the tale…’. This is a profound act of affective curatorship. It acts as an immediate narrative plunge, utilizing the limited space of the museum to immerse the visitor in the context even before they reach the exhibition. It centers the museum’s narrative on tragic heroism, priming the visitor for a story of awe and admiration.

The Entrance and the famous quotation of Scott during his last days, providing the ground of the storytelling of the museum.

The community of the Scott Polar Research Institute truly comes to life every day at 10:30 a.m., when the original bell from Scott’s 1910 Terra Nova expedition ship is rung for tea. This ritual became a vital part of my time here, allowing me to meet other scientists and share our research. My task as a fellow was to understand how this powerful, memorial-centric narrative in the museum shapes our public understanding of Antarctica, especially in an age of urgent climate change.

Encountering the ‘Final Camp’: The Power of an Affective Past

My first week was a deep immersion. I spent days observing the museum objects and their labels, often having long discussions with Laura and Florence, two very dedicated members of the museum, who were always ready to help and discuss the exhibits.

The visitor’s path leads into the main event after the Arctic Exhibitions: the Antarctic gallery, unambiguously titled ‘Antarctic Exploration – the Heroic Age’. The title itself narrows the continent’s vast history to one mythologized period. Inside, the hierarchy is clear: the major portion of the space is for Robert Falcon Scott. A secondary focus is on Ernest Shackleton and a minor role is for Roald Amundsen, who appears mainly as the champion in the race to the pole, but Scott tragically became the ‘Second’.

The exhibition is a masterclass in narrative tension. The Scott display builds to the heartbreaking discovery of Amundsen’s tent, captured by Scott’s own despairing words: ‘Great God! This is an awful place…’.

The Display of Scott’s expedition to the South Pole.

The story culminates in the most affectively charged section, ‘The Final Camp’. This showcase functions as a secular shrine, displaying the intimate relics of the deceased men: a journal wallet, prayer books, and, in some pull-out drawers, their original, handwritten farewell letters. Opening those drawers is a transformative, private, and profoundly emotional encounter. This is a powerful storytelling tool: tangible relics of great men shaping a powerful national story.

The Present on the Periphery: The ‘Ice and Climate’ Gallery

After this immersive journey, the path concludes in the third and final gallery: ‘Ice and Climate: Exploration into Science’. This final, smallest gallery is positioned as a coda or epilogue to the main performance, tucked away by the exit. The atmosphere shifts from the dramatic and affective to the modern and moralistic. Clean, white blocks and digital screens feel more like a contemporary science center, signaling a move from storytelling to information.

This section highlights a core challenge of curating our current era, the Anthropocene. The contemporary story of climate change is abstract and lacks the narrative power of Scott’s letters. So how does the museum lend its authority? It powers the authenticity and historical weight of its most prized collections. To explain the Ozone Hole, the museum displays a telescope from the 1901 Discovery expedition. This is a deliberate strategy to leverage the museum collection by linking the historic era scientific observation with the present crisis. The implication is that the Heroic era objects are called upon as witnesses. The exhibition uses historic tools to ground climate data in a tangible lineage of polar observation.

A View from Bremerhaven: A Tale of Two Polar Narratives

My time at Cambridge went beyond just observing the objects; it involved engaging in critical dialogues with the scholars about the politics of Antarctic Heritage preservation. A dedicated discussion with the curator, Dr. David Waterhouse, offered essential insights into collection strategies, while Dr. Bryan Lintott’s guidance through the institutional archives reshaped my perspective on Antarctic Heritage Politics. These exchanges were crucial for my own research focus on how the value of the distant Antarctic Historic Sites and Monuments (HSM) can be mediated to the museum space to raise awareness and bridge the gap between the public and preservation efforts on that barren Antarctic landscape.    

Being from DSM and observing the museum exhibits of the Polar Museum gave the opportunity to do comparative analysis, which reveals two very different modes of polar curatorship. Cambridge exemplifies the memorial approach, using the affective power of relics to narrate a story of heroic sacrifice.

The Display of Sheckleton.

The German Maritime Museum (DSM) in Bremerhaven, by contrast, pioneers an experiential-scientific approach. Free from a foundational ‘Heroic Age’ legacy, its new exhibition axes the narrative squarely onto contemporary polar science, featuring an installation modeled on the modern research vessel Polarstern and using interactive media to make polar research an experience. This comparison is not about which model is better. It is about understanding how an institution’s identity shapes its narrative possibilities.

The Value of a Frozen Past

This brings me back to the core theme of the Leibniz Research Alliance: What is the ‘Value of the Past’ in our thawing, precarious present?

My time at the Polar Museum has left me reflecting on this very question. The ‘value’ here is not simple. It is also in the tensions the past reveals: the tension between a celebrated heroic narrative and an urgent climate crisis; a tension between the emotional relic in the museum and the real, threatened heritage site on the ice; and the tension between national memory and global responsibility.

The Decolonization attempt of the museum.

Addressing this, the Polar Museum in Cambridge has attempted to develop a dual strategy. The permanent gallery, with its powerful memorial focus, is not the whole story. It is complemented by a dynamic multi-platform strategy like temporary exhibitions, digital programming and educational outreach.

This seems to be the way forward: the permanent gallery fulfills the memorial duty, while the dynamic programming fulfills the contemporary one. The frozen past is not a roadblock; it is the foundation to build upon. The challenge, it seems, is not to discard these powerful, affective legacies, but to influence their power and critically connect them to the urgent, planetary responsibilities of the present.

The Display of the North-West Passage Expedition of Franklin.

Mohammad Abu Al Hasan is a Scientific Associate at the German Maritime Museum (DSM) – Leibniz Institute for Maritime History. Since April 2025, he is pursuing a PhD at the University of Bremen titled Protecting the Cultural and Scientific Heritage of Antarctica: Managing the Diversity, Ensuring Credibility for the Future.


Title picture: The Roof Painting illustrating the Arctic and the Antarctic.

All pictures in this blog post were taken by Mohammad Abu Al Hasan, 2025.

The fascination of old collections: Histology in the Museum of Zoology

In her contribution, Lucie Helfmann takes us to the histological collection of the Museum of Zoology, University of Cambridge, and shows us what more can be found there, beyond dusty slides.

For over a century, researchers at the University of Cambridge have used histology to reveal patterns of internal and soft-tissue anatomy, which would otherwise remain invisible. Over time, an extraordinary array of many thousands of histology slides has accumulated in Cambridge.

Seit über einem Jahrhundert nutzen Forscher:innen an der Universität Cambridge Histologie, um anatomische Eigenschaften von inneren Organen und Weichteilen zu untersuchen, die sonst verborgen blieben. Im Laufe der Zeit hat sich in Cambridge eine außergewöhnliche Sammlung von vielen Tausenden histologischen Präparaten angesammelt.


What is histology?

Histological examinations study the microscopic anatomy of tissue mounted on small glass slides, revealing properties that cannot be seen with the naked eye. The origins of histology date back to the 19th century, when CT and MRI scans did not yet exist.

Cross-section through the head of a ray (size about 1.5 cm). Photo: Lucie Helfmann, 2024.
How to create a histological slide. Lucie Helfmann, 2024.

To create a histological slide, a specimen is embedded in a supporting material, such as paraffin wax, and then cut into very thin slices (usually 5–15 µm). Bones and teeth have to be softened using a variety of acids and other reagents in order to be sliced. These slices are then transferred to glass slides in sequence and dyed using various chemicals, or “stains”, that differentially bind to soft tissues such as decalcified bone, teeth, muscles, and nerves. Which dye is used depends on the type of tissue you want to highlight. After staining, a cover slip is placed over the tissue on the slide to protect it. Now the slide is ready to be investigated under the microscope. In this way, the interior of specimen can be examined and even the finest tissue structures can be identified.

When I arrived in Cambridge, I found a room full of boxes, which were in turn filled with histological slides. In many cases, the origins of a given box was uncertain. The boxes had been moved several times over the decades, and some were quite old and worn.

Old box containing histological slides of sharks and rays. Scyllium canicula (today Scyliorhinus canicula ) is the small spotted catshark; Torpedo ocellata (today Torpedo torpedo ) is the common torpedo or eyed electric ray. ‘Trans’, ‘sagittal’ and ‘coronal’ refer to the directions in which the specimen was cut. Photo: Lucie Helfmann, 2024.

I examined each box, sorted its contents, and digitized all the available information about the slides. This work is crucial in order to make the collection more accessible for scientists all over the world. In the end, our goal is to construct a database where everyone can see what kind of specimens are housed in the Cambridge Museum of Zoology, and be able to determine if a given specimen might be useful for their research. Essential information might include the species, sample size, direction of cutting (e.g., horizontal or vertical), which stain was used, number of slices, anatomical region sampled, etc.

But during my work I found more than just slides. I found history dating to the foundation of the department itself. The oldest slides I found belonged to Francis Maitland Balfour, the first holder of the Chair of Animal Morphology in Cambridge in 1882 and regarded as Darwin’s successor. Tragically, Balfour died that very same year, just 30 years old, during a mountaineering accident in the Alps.

Francis Maitland Balfour, founder of the Department of Zoology in Cambridge (From: The Works of Francis Maitland Balfour).

His main research focused on elasmobranch fishes (sharks and rays) and their development. Despite his short life he left quite a legacy, consisting of thousands of slides. Some of them I could directly connect to Balfour’s work. Hence, the oldest slides are over 150 years old, and many remain in pristine condition! It’s impressive what was already possible at that time, to create such fine objects. Remember, the typewriter and the common light bulb had yet to be invented.

Balfour’s successor was Adam Sedgwick, a relative of the man after whom the museum is named. He took over Balfour’s instruction in animal morphology. Sedgwick also continued Balfour’s work on elasmobranchs and embryology. Because of their attention to detail and careful technical work, e.g. including precise places and dates of collection on many histological slides, it is easy to trace their work. For example, most of Sedgwick’s material is from the summer of 1890.

Example for a series of a shark’s head (Scyllium canicula). Each slide contains two slices of the specimen, Photo: Lucie Helfmann, 2024.

From the 1950s, Hans W. Lissmann was in charge of the histological collection. His main research topic were electric organs in fish like Gymnarchus niloticus (or the “aba”, a predatory fish from Central Africa). Together with Lissmann’s material, I found some notes and letters which, among other things, describe the story of a Mr. M. Omarkhan, who was also working on Gymnarchus. In one letter, Lissmann asked for the material of Omarkhan, which also turned out to be in one of the boxes I had organized. Further notes hinted that these might even be the slides R. Assheton wrote about in 1903. Again, there are publications that could be connected to these slides and these letters. With this material, we could open a window into how science worked at that time, without email, online databases, or Google Scholar.

A treasure box full of histological slides. You never know what you might find in there! Photo: Lucie Helfmann, 2024.

Today the method of creating histological slides remains widespread in hospitals and research universities, and it is still one of the best means to visualize internal and cellular anatomy. Although many aspects of the technique have changed, old material can still be used. Nowadays it is even possible to digitize histological slides and put them virtually back together to rebuild the old specimen and reconstruct parts thereof in three dimensions. Given that an animal must always be ‘sacrificed’ in order to create a histological series, it is desirable to reuse as much of the existing material as possible.

All of this shows how “old” material is often priceless, and how important it is to preserve the legacy of “old” collections, not only to save the material itself, but to reduce pressures on the animals and plants in living environments, and to preserve the remarkable history of the scientists on whose shoulders we stand today.


Literature

Alexander, R. M. (1996). Hans Werner Lissmann, 30 April 1909-21 April 1995. Biographical Memoirs of Fellows of the Royal Society, 42, 235-245.

Assheton, R. (1907). The development of Gymnarchus niloticus. Cambridge University Press.

Balfour, F. M. (1885). The Works of Francis Maitland Balfour. (Vol. 1 – 4). Macmillan and Company.

Hall, B. K. (2003). Francis Maitland Balfour (1851–1882): a founder of evolutionary embryology. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution299(1), 3-8.

Lissmann, H. W. (1958). On the function and evolution of electric organs in fish. Journal of experimental biology35(1), 156-191.

Omarkhan, M. (1949). The morphology of the chondrocranium of Gymnarchus niloticus. Zoological Journal of the Linnean Society, 41(281), 452-481.


Lucie Helfmann was awarded a Leibniz-Cambridge Museum & Collection Fellowship in Autumn 2024. At the University of Cambridge she curated the histological collection of the Museum of Zoology under the supervision of Dr. Robert Asher.


Title image: Four boxes containing histological slides of lizard tails. Photo: Lucie Helfmann, 2024.

Unlocking the Past with AI: Spectral Decomposition for Image Processing in Cultural Heritage

Marco Colombo reflects on Yury Korolev’s conference presentation and shares his own perspective and insights.

This blog post is part of a series on the conference “Artificial Intelligence in Archives and Collections” held on December 12-13, 2024, at the Herder Institute in Marburg and presents perspectives on the coference contribution by Yury Korolev, University of Bath – written by Marco Colombo.


Recent advancements in artificial intelligence and mathematical techniques are transforming the way we approach cultural heritage preservation. These technologies provide new ways to analyze and interpret digital data, particularly in the realm of historical documents and artifacts. By applying mathematical models to imaging data, researchers can uncover hidden details, restore ancient manuscripts, and better understand the history behind archaeological findings.

In the world of cultural heritage preservation, technology plays an increasingly vital role in uncovering and understanding historical artifacts. One of the most promising advancements in this field is mathematical imaging, which has revolutionized the way we analyze historical documents. This article delves into how spectral decomposition aids in processing images for cultural heritage applications, with a focus on analyzing handmade medieval paper. This topic was treated by Assistant Professor Yury Korolev in his oral presentation at the conference.

The Power of Spectral Decomposition in Image Processing

At its core, spectral decomposition involves breaking down an image or signal into simpler components that can be interpreted and manipulated independently. A well-known example is the Fourier transformation, which decomposes a signal into sine and cosine waves of different frequencies. This method has long been used in audio processing, where equalizers modify frequencies to emphasize or dampen specific sounds.

Applying this principle to image processing allows researchers to filter images by modifying their spectral components. Similar to how equalizers can adjust bass or treble in music, spectral decomposition enables the enhancement or suppression of specific image features, revealing details otherwise hidden in noise and distortions.

A musical manuscript (Pantokratoros monastery, code 214), 1433.

Challenges in Fourier-Based Image Processing

Traditional Fourier-based filtering presents certain challenges when applied to images. One primary issue is the handling of edges and sharp transitions within an image. The Fourier transform favors smooth variations and struggles with the abrupt changes often found in historical documents, where distinguishing between textual content, illustrations, and background textures is crucial for accurate analysis.

Additionally, artifacts such as noise and dirt often share high-frequency components with vital image details, making it difficult to distinguish between essential and extraneous elements. This limitation necessitates alternative approaches that can better separate meaningful structures from irrelevant noise.

Total Variation Spectral Decomposition: A More Effective Approach

A promising solution to these challenges is total variation (TV) spectral decomposition [1, 2, 3]. Unlike Fourier methods, TV decomposition is particularly effective in processing images with sharp edges and high contrast variations, such as handwritten medieval manuscripts. This approach decomposes images based on the scale and contrast of details, allowing for a more meaningful separation of image elements.

Using TV spectral decomposition, an image is analyzed at different levels of detail, isolating high-contrast features such as text and marks while preserving background textures like paper grain and chain lines. The ability to filter images in this way is invaluable for historians and archivists, as it allows them to extract key structural elements from historical documents with remarkable precision.

Grégoire de Tours, Histoire des Francs. Initial P in the form of a fish opening the book. Late 7th century.

Applications in Medieval Paper Analysis

One particularly compelling application of TV spectral decomposition is in the study of handmade medieval paper. This type of paper was created using molds made of metal wires, which left distinctive imprints known as chain lines (vertical lines) and laid lines (horizontal lines). Additionally, many papers featured watermarks that identified their origin, providing crucial insights into historical trade networks and manuscript provenance.

By applying spectral decomposition techniques, researchers can:

  • Digitally remove overlying text and stains from historical documents to better reveal the mold imprints.
  • Enhance faint chain lines and laid lines, allowing for accurate identification of the paper’s origin.
  • Segment different elements of an image to isolate and analyze individual components more effectively.

This methodology has been successfully employed on manuscripts from the Cambridge University Library, enabling historians to trace the origins and movements of medieval texts with better accuracy.

Beyond Cultural Heritage: Broader Implications

The benefits of TV spectral decomposition extend beyond historical paper analysis. This approach has demonstrated its effectiveness in several other imaging applications, including:

  • Image Denoising: Removing unwanted noise from photographs, particularly in low-light conditions.
  • Image Segmentation: Identifying and categorizing different elements within an image, useful in medical imaging and microscopy.
  • Image Fusion: Combining multiple imaging modalities to create a more comprehensive representation of an object, especially in medical diagnostics.

Moreover, machine learning is being integrated into these spectral decomposition processes, significantly improving computational efficiency. Researchers are developing AI-driven models to automate and optimize these transformations, making them more accessible and scalable for various imaging needs.

Gemini, from the medieval Georgian manuscript of an astrological treatise, 12th century.

Future Prospects and Challenges

While TV spectral decomposition has proven to be a powerful tool, it is not without its challenges. One notable limitation is its preference for detecting rounded or disk-like structures, which may not always align with the features of certain historical documents. Future research is focused on refining these methods to accommodate a wider variety of structural elements, making them even more effective for cultural heritage applications.

Additionally, computational efficiency remains a concern. Unlike standard Fourier filtering, TV-based decomposition requires solving complex optimization problems, making it computationally intensive. However, ongoing advancements in machine learning and algorithmic optimization are expected to mitigate these challenges, paving the way for faster and more efficient implementations.

Conclusion

Spectral decomposition, particularly through total variation methods, represents a powerful technique for cultural heritage applications. By enabling clearer and more detailed analysis of historical documents, this technology offers invaluable insights into the past while preserving artifacts for future generations. As AI and machine learning continue to enhance these techniques, the potential for further breakthroughs in digital humanities and archival science remains immense.

With continued research and innovation, spectral decomposition will undoubtedly play a crucial role in unlocking the hidden secrets of our cultural heritage, bridging the gap between history and technology.


References

[1] Gilboa, G., 2014. A total variation spectral framework for scale and texture analysis. SIAM journal on Imaging Sciences, 7(4), pp. 1937-1961.

[2] Grossmann, T.G., Schönlieb, C.B. and Da Rold, O., 2023. Extracting chain lines and laid lines from digital images of medieval paper using spectral total variation decomposition. Heritage Science, 11(1), p. 180.

[3] Grossmann, T.G., Dittmer, S., Korolev, Y. and Schönlieb, C.B., 2022. Unsupervised learning of the total variation flow. arXiv:2206.04406.


Marco Colombo is a PhD student in the Materials Analysis Group at the Darmstadt Technical University. He was a participant at the conference in Marburg and was particularly interested in Yury Korolev’s work, so he decided to write down his impression and perspectives on his presentation.

The original title of Yury Korolev‘s presentation at the conference was “Image filtering based on total variation spectral decompositions: an overview of the method and an application in medieval paper analysis”. For further information on the conference see the programme.


Title picture: Book of Hours — a prayer book written in Medieval Latin (c. 15th century).

All pictures: symbolic images, public domain via Wikimedia, see also here.

Current developments in AI and what they mean for everyday use in archives

Anja Link takes a closer look at various contributions from the panels and identifies three key findings from the conference.

Insights from the Conference “Artificial Intelligence in Archives and Collections”

This blog post is part of a series on the conference at the Herder Institute in Marburg on 12 and 13 December 2024 and will highlight three overall findings.


AI needs to be co-created by humans – to do its work but also to supervise its ethical conduct

Questions of finding the happy medium of human and machine action were touched on by many speakers. While the call co-creation may appear self-evident—after all, AI models are developed by humans — when taking a closer look at the modelling and training phase, the issue reveals to be more complex. The complexity begins with data selection and extends through the modelling and training phases to the actual implementation of AI systems. Furthermore, it touches ethical questions of (energy) resource efficiency, bias and power. Ensuring meaningful human involvement at every stage is therefore not just a technical necessity, but an ethical imperative.

Data Selection and AI

>>> Mo von Bychelberg’s overview on „Artificial Intelligence Technology’s Influence on the Authenticity of Digital Intangible Cultural Inheritance” explored how AI introduces new dimensions of power and bias into archival practices—dimensions that, in fact, build upon long-standing issues in the field. Traditional dimensions of power and bias in archives cover questions of what is worth being archived as well as who decides what is being archived. In the era of digitisation those dimensions extend to questions of what is worth being digitised and who decides on that. The emergence of AI technologies adds yet another layer: Which archives can afford to use or even create AI? Who has the human resources and expertise to work with off-the-shelf AI solutions? Will the staff be able to handle off-the-shelf AI? Can AI potentially address broader challenges, such as preserving the tacit knowledge of retiring archivists? Von Bychelberg argued that many of these issues—power, bias, access, and sustainability—converge in the context of AI. Before archives consider adopting AI technologies, these critical questions must be openly and thoroughly addressed.

Mo von Bychelberg, Uppsala University

AI model training phase

>>> In her presentation on “Dusting Off the Unlabelled Data: Graph Semi Supervised Learning for Large-Scale Datasets” Angelica I. Aviles-Rivero shared insights from her research on efficient image procession in training phases. Regardless of the model’s ultimate goal—be it image classification, recognition, or generation—every image-based AI system begins with object detection and data labelling. Since AI models have limited generalisation capabilities, acquiring large datasets with accurate annotations is costly in terms of time, financial resources, and the need for expert knowledge. Reducing those costs requires a well-balanced combination of human expertise and machine-based interpretation of image data.  Semi-supervised learning approaches that balance since its central task is replacing data by human knowledge and thus training with less data. Aviles-Rivero’s findings indicate that SSL can lead to improved model performance by replacing parts of the training data with human insight, thereby requiring fewer labelled examples.

>>> Nicole Graaf explored the temporal, gender-based, and cultural dimensions of bias in AI-generated image metadata in her presentation „Between ritual and relief – when the computer squints: analysis if AI-based indexing in the Image Archive of the ETH Library”. From an archivist’s persepective, Graaf presented the results of a qualitative analysis of automatically tagged images. The images were labelled using Clarifai’s general model and subsequently reviewed by subject experts—not only for semantic accuracy, but also for their potential to create or reinforce bias. As it turned out, automatic tagging works best with iconic, easily recognisable images that would likely be used to teach a child. In contrast, automatic tagging struggles significantly when it comes to abstract cultural or gender-related concepts. These findings underline two key points: a) AI-generated metadata must be critically evaluated by humans, and b) the ethical dimensions of AI output are fundamentally shaped by the data used during training. Graaf suggested that one possible technological approach to mitigating bias is to address the issue at its source—by regularly reprocessing digitised archival materials with updated AI models. Another long-term solution could lie in developing institution-specific AI systems tailored to the archival context.

>>> Christopher Kermovant also explored pre-trained AI-models’ capacities and limitations in interpreting historical image material. In his presentation on “How to use controlled vocabularies to describe early Japanese photographs using deep learning models” he shared his main findings for interpreting historical image material, particularly archive documents of non-Western origin. Kermovant’s findings highlighted two central issues: a) Pre-trained AI models (in this case: CLIP, Qwen2, and ChatGPT-4o) tend to perform best in languages with strong representation in their training data—namely English, French, and German. b) These models exhibit a significant bias toward Western perspectives when interpreting non-Western imagery, often leading to distorted or overly simplified classifications. His work also underscores the need for more culturally diverse training datasets and the careful use of controlled vocabularies when applying AI to global archival materials.

Reducing time, labour and energy intensity —while also addressing ethical concerns— reveals to be a major task in the field of object detection and labelling image and text documents. On the one hand there is the question to what extend co-creation is essential for bridging the gap between machine-classifiable content and the deeper semantics of images or texts. On the other hand, it must be critically assessed which tasks necessarily have to be executed by AI and which ones humans might be better at than resource-efficient AI could ever be.

The conference took place in a hybrid format. Questions were taken directly from the audience as well as via the chat.

Picture quality matters. But in a different way than we as humans might expect

Image quality plays a crucial role in both the preprocessing and processing stages of archival image and text documents. While preprocessing can be extremely time-consuming, it is highly relevant for enabling meaningful analysis. In archival contexts, preprocessing typically involves distinguishing between the medium (e.g., paper texture, handwriting, image artifacts) and the actual content. Only after this separation can the content be decomposed and relevant information extracted effectively.

>>> Contrary to what one might assume, in the case of object detection, higher resolution does not automatically yield better results in object detection tasks during AI training. The appropriate level of image detail depends on the specific analytical goal, as Karsten Tolle, Yury Korolev and Christopher Kermovant explained in their respective presentations „Potpourri of Computer Vision in Cultural Heritage“, “Image filtering based on total variation spectral decompositions: an overview of the method and an application in medieval paper analysis“ and “How to use controlled vocabularies to describe early Japanese photographs using deep learning models“. For certain features, reducing the resolution—or even intentionally blurring the images—can improve detection performance. This approach not only facilitates the filtering of relevant information but also helps eliminate insignificant visual elements, such as scratches or artifacts, which might otherwise be misinterpreted by the model as meaningful features.

>>> Mahsa Vafaie’s insights into „Separation of machine-printed and handwritten text in archival documents” illustrated many incremental steps required to extract semantically accurate information from digitised archival documents—steps that are essential for uncovering previously unknown historical knowledge. The process begins with removing traces of the documents’ physical characteristics, such as background noise, material textures, or the representation medium itself. It may also include the distinction between relevant elements and noise. When documents contain both machine-printed and handwritten text, further complexity arises. Text-type separation must be carried out using OCR (Optical Character Recognition) for print and HTR (Handwritten Text Recognition) for script. This involves handling heterogeneous layouts, processing both standard and non-standard fonts, recognising different handwriting styles, identifying stamps and annotations. However, Vafaie pointed out that the computational challenge does not stop at the complex procedure of accurately identifying information of every single document. Future research will have to address ways of connecting as well as embedding information into its historical context.

Mahsa Vafaie, FIZ Karlsruhe – Leibniz Institute for Information Infrastructure

Several contributions throughout the conference have underlined that AI forces us to examine analytical steps that the human brain implicitly takes and to adapt those steps to the technology’s requirements. Both the training of AI models and the analysis of archival material using AI are often shaped by trial-and-error processes that highly profit from creative ideas and fondness of experimenting.

Multimodal AI solutions are needed for AI to be applied across a broader range of archives

Despite growing technical capabilities, most current research projects still tend to focus on either image or text processing. The integration and simultaneous analysis of hybrid data—combining visual and textual elements—seems to remain the widest research gap.

As Erik Radisch concluded in his presentation on “A new Approach to Semi-Automated Annotations with Segment-Anything (Meta AI)” while numerous AI tools are already available, their full potential is only realised when they are combined —both to improve usability and to produce meaningful outcome. Radisch also emphasised the highly dynamic nature of the AI landscape: many models currently in use may soon be otperformed. The interim solution to that appears to lie in relying on pre-trained multimodal AI systems. When doing that, one has to bear in mind that pre-trained AI tends to fail at analysing phenomena that are not reflected in their training material for cultural or language differences or because they lack adequate historical training material.

Autor’s reflexion on the research findings and what they might mean for everyday use in archives

Practitioners attending the conference with high expectations for ready-to-use, one-size-fits-all AI solutions—comparable in performance and accessibility to chatbots like ChatGPT—may have left somewhat disappointed. At present, no such solution does exist. However, that does not mean that these ideas went unaddressed. As it is common for any conference the horizon of the panels was broadened by informal discussions during the coffee brakes where speculative ideas were explored. In this case the coffee brake discussions with practitioners from archives proved to be specifically insightful when it came to questions of integrating research findings into day-to-day archival work. While the conference contributors presented insights into the use of AI-models for different types of archival use it became even more apparent in the discussions that the path to their everyday applicability remains to be a long one. This path starts with the basic necessity of the existence of digitized material. Yet, particularly in small and understaffed archives, the proportion of digitised holdings is often very low. Ironically, these are the very institutions that could benefit most from AI-supported tools, given their limited financial and human resources. However, it is particularly that lack of resources that makes the use of AI tools unattractive at this point in time. Until AI tools can be seamlessly integrated into archival workflows in a significantly more resource-efficient manner, their use will likely remain out of reach for the average archive.

Among its many opportunities and challenges, AI has the potential to not only enhance biases. It also has the potential to widen gaps between well-resourced and under-resourced archives. Addressing these challenges requires more than just developing open-source, multimodal AI models. Equally important is ensuring maximum usability—through intuitive interfaces, cost-effectiveness, adequate server capacities, and robust data protection measures. Additionally, setting special focus on developing models in a modular system that can be used by a wide range of archives and adjoining institutions might be useful. AI might even constitute a new field of state action similar to already existing e-government or cloud infrastructures. Regardless of the specific perspective taken on AI in archives and collections in the near future, the field continues to offer ample food for thoughts, future research and discussions.


Anja Link has been working as a research assistant in the Department of Architectural Theory and Building History at Bremen University of Applied Sciences since 2019. By focussing her doctoral thesis on the history of architecture and urban planning, which is underpinned by an economic-historical perspective, her doctoral project brings together her previous research interests. She participated in the conference and is the author of this conference report.


Picture credit (all): Impressions from the conference, Claudia Junghänel, Herder Institute.

​Innovative Tools and Current Projects: Artificial Intelligence in Archives and Collections

In his article, Erdal Ayan presents a selection of AI tools for archives and collections as well as current projects that were presented at the Marburg AI Conference.

Key topics of the conference Artificial Intelligence in Archives and Collections: Practices, Potentials and Evidence Production in Dealing with Images and Multimodal Cultural Heritage included computer vision techniques, multi-modal large language models (MLLMs), semi-automated annotation, and innovative tools for search and discovery. Several new and ongoing projects showcased advancements in deep learning, text-image embedding, and graph-based learning.

This blog post is part of a series on the conference held on December 12-13, 2024, at the Herder Institute in Marburg and will present a number of selected tools and topics that have been discussed.

Opportunities and Challenges

The conference emphasized both the opportunities and challenges presented by AI-driven tools, including ethical concerns, explainability, and data bias, while promoting collaboration and knowledge exchange across disciplines. It focused on visual sources such as photographs, graphic collections, and mixed image-text archives, addressing both theoretical and practical challenges in automated indexing, cataloguing, and image processing. The growing role of AI and ML in multi-modal cultural heritage research was highlighted, particularly in semantic segmentation, object classification, and annotation. Key datasets discussed included coins, archaeological record cards, Buddhist murals, Soviet newsreels, and historical photographs, etc. This article will present a number of selected tools and topics that have been discussed.

​Image Archives and Image Processing

Image archiving and processing topics had an important place in the conference, and current studies on these topics attracted a lot of attention from the participants. The presentations at the conference demonstrated how AI and ML are revolutionizing the management and analysis of image archives.

Ralph Ewerth introduced iART, a computer vision-based search engine that enhances the accessibility of art and historical archives. It addresses cultural heritage images that integrate computer vision techniques for object recognition and cross-modal search. The dataset includes coin images, and the tool supports both scholarly research and public engagement. iART enables users to explore large image collections through features like object recognition, pose estimation, and natural language queries. Ewerth demonstrated how state-of-the-art computer vision techniques, combined with large language models, facilitate improved retrieval results and explanations for search outcomes.

Frank Puppe addressed the digital indexing of archaeological record cards, presenting a pipeline that processes scanned documents through Optical Character Recognition (OCR), semantic mapping, and multi-modal large language models like ChatGPT-4o. This pipeline enables the transformation of analogue archaeological records with images into searchable, structured formats such as JSON.

Home page of HikarIA, screenshot taken on 21 May 2025.

Christopher Kermorvant highlighted challenges in applying contemporary deep learning models to early Japanese photographs. He introduced HikarIA, which is a search engine designed for Japanese historical photographs, addressing issues of limited metadata and enabling discovery through advanced AI techniques. While convolutional neural networks and transformer models excel with modern datasets, historical images often present difficulties due to cultural and temporal differences. Kermorvant emphasized the need for tailored approaches to address these limitations.

Erik Radisch mentioned the Segment Anything, integrated with Annotorious for semi-automated image annotation. Segment Anything is a model developed by Meta AI for image segmentation, capable of prompt-based annotation without extensive retraining. And Annotorious is an open-source JavaScript solution for image annotation. This method significantly reduces the time required for detailed polygon-based annotations, making it ideal for large-scale archival projects. Segment Anything’s ability to adapt to new tasks without extensive retraining provides a powerful tool for researchers.

​New and Ongoing Projects in Image Archiving

At the conference, researchers talked in detail about their own work on image archiving and processing and shared their knowledge and experience on new and ongoing projects. The conference, therefore, showcased several innovative projects and tools that push the boundaries of AI-driven cultural heritage research. Among these were:

Celtic coin type “Divinka” from Slovakia. Foto: Marek Sobola, Wikimedia Commons.

ClaReNet (Karsten Tolle): A project utilizing object detection and classification to analyze coins. Tolle demonstrated the use of Orange Data Mining, a visual programming tool, to enable non-programmers to perform clustering and classification tasks. 

Wiedergutmachung (Harald Sack and Mahsa Vafaie): A collaboration with the Landesarchiv Baden-Württemberg that focuses on the classification and extraction of handwritten and machine-printed text in historical documents. Vafaie presented a pipeline for separating handwritten annotations from machine-printed text, resulting in a 26% improvement in OCR accuracy.

Kinokroonika (Mila Oiva): A project that explores clustering of images as graph data, leveraging graph-based methods for visual analysis.

Dight-Net (Mila Oiva): A collaborative research initiative utilizing tools like ResNet-50 to advance digital cultural heritage projects.

Orange: An open-source visual programming tool for clustering, classification, and image analytics, designed for non-programmers.

ResNet-50: A deep learning model architecture for image classification, compatible with Python libraries like Keras.

Collection Space Navigator (CSN): A tool for visualizing and exploring collections through vector encoding of images, built using Python (Flask) and React.

The sharing of these studies and experiences by experts at the conference provided an important impetus for knowledge transfer and the development of future collaborations.

Conclusion

The Artificial Intelligence in Archives and Collections conference underscored the transformative potential of AI and machine learning in managing, analyzing, and understanding cultural heritage data. Projects like iART and Wiedergutmachung demonstrated practical applications of computer vision and text recognition, while tools like Segment Anything and Orange highlighted the growing accessibility of AI technologies for non-experts.

Despite these advancements, the conference also addressed challenges such as data bias, explainability, and the limitations of current models when applied to historical datasets. Speakers emphasized the importance of interdisciplinary collaboration and the need for ethical considerations in the deployment of AI technologies.

Overall, the event successfully fostered dialogue between researchers, developers, and practitioners, paving the way for future innovations in AI-driven cultural heritage research.


Selected Reference List for the Projects Presented

Arnold, T. (2024). Explainable and Auditable Search and Discovery of Visual Cultural Heritage Collections.

Aviles-Rivero, A. I. (2024). Dusting Off the Unlabeled Data: Graph Semi-Supervised Learning for Large-Scale Datasets.

Evans, J. (2024). The Geometry of Culture: Analyzing Meaning through Embeddings of Text and Images.

Ewerth, R. (2024). Unlocking Cultural Heritage: Computer Vision for Art and History Archives.

Markus Huff, Nine Abele, Dominik Kimmel, Helen Fischer, Gerrit Anders, Tolgahan Aydin, Jürgen Bude. (2024). ArchiveGPT: Psychological and Technological Perspectives on the AI-Supported Archiving of Image Material.

Kermorvant, C. (2024). How Contemporary Deep Learning Models Describe Early Japanese Photographs?

Puppe, F., N. Fischer, D. Kimmel (2024). Pipeline for Digital Indexing of Archaeological Record Cards.

Radisch, E. (2024). A New Approach to Semi-Automated Annotations with Segment Anything.

Sack, H., & Vafaie, M., Waitelonis J. (2024). Separation of Machine-Printed and Handwritten Text in Archival Documents.

Tolle, K. (2024). Potpourri of Computer Vision in Cultural Heritage.

All of these projects were presented at the conference. The full programme and all abstracts can be found on the website of the Herder Insitute.


Erdal Ayan is a Software developer working at FIZ-Karlsruhe, Germany. As a young researcher and developer, he has been active in Digital Humanities for many years now. He is currently interested in software development in image processing and Computer Vision and has participated in the conference.


Title picture: An example of image processing. Original image, and resulting image after Laplacian and Sobel filters. Alaens, Wikimedia Commons.

Artificial Intelligence in Archives and Collections: Practices, Potentials and Evidence Production in Dealing with Images and Multimodal Cultural Heritage

In this report, the organizers look back on their conference and provide an outlook. Further summaries and reflections of the panels will be presented in a small blog series.

Report on a hybrid conference in Marburg, 12–13 December 2024


In the years to come, curatorial and archival processes in memory and heritage institutions (including key aspects of cataloguing such as description, classification and categorization) will be increasingly supported by automated systems and artificial intelligence. These practices attribute value to sources and link archival materials and collection objects to societal narratives. Collections and archives thus form an essential basis for memory-related discourses and shape our view of the past. New technologies have now reached the stage where they are potentially suitable for the requirements of cultural heritage institutions. There is substantial promise in the partially automated indexing and cataloguing of historical sources, particularly of digital images, the hermeneutics and meaning of images which in the past have only been accessible to the human eye and not the machine.

Images can now be automatically described semantically, making them easier to find. AI methods – and most recently multimodal AI processing – are opening new possibilities for automatic text extraction and layout recognition, automated image segmentation and annotation, as well as the analysis of visual sources and their contextualisation. At the same time, however, there is a lack of knowledge about how evidence – and subsequentially facts – are generated and how AI processes affect the attribution of authenticity to archival documents and photos. Currently, the humanities lack semantically high-quality, historically adequate and subject-appropriate training datasets. Similarly, there is hardly any agreement about what constitutes an acceptable outcome of computational classification processes, or what kind of benchmarks should be used to evaluate the results. We therefore need to develop best practices (that may tap into explainable Artificial Intelligence (XAI) methods), benchmarks and common goals. To increase the value that the information and knowledge held in our archives and collections have for future research, we need to deepen our understanding of processes and algorithms.

To deepen the discussion on these questions, the Research Lab ‘Digital Heuristics and Digital History’ of the Leibniz Research Alliance ‘Value of the Past’, in cooperation with NFDI4Memory, Task Area ‘Data Quality’ have organised a conference in Marburg on artificial intelligence in cultural heritage institutions, such as archives and collections, and how these new technologies are transforming archival institutional practices. Topics primarily focused on – but were not limited to – visual sources, such as photography and graphic collections or mixed image-text sources and multimodal information processing.

The conference provided a forum for researchers and practitioners from the humanities, as well as archives and collections to connect with researchers and engineers in the fields of artificial intelligence, computer science and the digital humanities, to discuss new findings, and to exchange experiences. The event was seeking to promote an interdisciplinary, cross-sectoral dialogue between research, development and practice.

The conference brought together curatorial and archiving knowledge and new AI-based methods but has also provided a forum for ethical reflection on the use of AI in academic and archival practices. Participants discussed how automated processing and AI methods require detailed epistemic reflection and methodological-technical control to ensure that no false or tainted evidence is generated. Thus, the conference reflected on the effects of these new technologies on the production of evidence, thereby contributing to the crucial question of how the digital transformation is changing knowledge creation in the humanities and what this means for scholarship in historical disciplines.

The call was met with a large response: Speakers from Austria, China, France, Germany, USA, UK and Sweden presented. More than 400 colleagues from 25 countries, most of them online, registered for the conference and followed the presentations or participated in the discussions. Papers covered topics such as Exploring and Analysing Collections from Textual and Multimodal Contexts, Computer Vision (Semantic Segmentation, Classification, Analysing and Understanding Images), The Effects of Computational Methods on Image Analytical Research and Visual Studies in Cultural Heritage, Opportunities and Challenges for the Automated Indexing and Cataloguing of Visual Sources in Archives and Collections.

As the organizers of the conference, we conclude from the high level of interest that – even though there are many possibilities in the various scientific communities to exchange upon new developments in AI – there is still a need for interdisciplinary and cross-sectoral exchange in the GLAM realm.  We would like to keep this interest alive and support networking on the topic also in the time to come – not limited to conference participants.

Participants – and any colleague who likes to join – will be informed about future activities and about possible publications. We will keep you updated about future publications resulting from the conference. Stay tuned! As a start, we will publish several short summaries and elaborations on selected conference topics on this blog, written by young researchers who participated in the conference. 


Programme and abstracts: https://www.herder-institut.de/event/conference-artificial-intelligence-in-archives-and-collections


Organizers:

Leibniz-Forschungsverbund „Wert der Vergangenheit“, Lab 1.3. Digitale Heuristik und Historik

Leibniz-Zentrum für Archäologie (LEIZA), Mainz

Herder-Institut für historische Ostmitteleuropaforschung – Institut der Leibniz-Gemeinschaft, Marburg

NFDI4Memory, Task Area Data Quality


This conference report was written by the organizing committee:

Elke Bauer, Herder-Institut

Simon Donig, Herder-Institut

Annette Frey, LEIZA

Dominik Kimmel, LEIZA


Further information on future activities on the topic: Interested parties can still use the conference registration tool to register for forthcoming information.

Contact: archivesai@herder-institut.dedominik.kimmel@leiza.de


Title picture: image detail of the conference flyer

Extinct but not forgotten: how museum collections help study the evolution of Hawaiian honeycreepers

In diesem Beitrag von Grigory Evtukh über Hawaiianische Kleidervögel lernen wir, wie naturkundliche Museumssammlungen etwas zum Schutz der Biodiversität beitragen können.

More than half of the Hawaiian honeycreeper species have disappeared, and the remaining ones are struggling to survive. How do museum collections help us study their past and prevent further losses?

Über die Hälfte der Hawaiianischen Kleidervögel-Arten sind ausgestorben, und die verbleibenden kämpfen ums Überleben. Wie helfen Museumssammlungen, ihre Vergangenheit zu erforschen und weitere Verluste zu verhindern?


I sit in the basement of the Cambridge Museum of Zoology, next to a humming ventilation system. The collections here are hidden from visitors, stored in metal cabinets filled with drawers of bird specimens. Today, the museum collections manager brought out one of specimens and carefully placed it on the table. I saw before me the only Hawaiʻi mamo (Drepanis pacifica) specimen in the Cambridge Museum collection. It was stored under a glass dome on a velvet-covered platform, giving it an almost ceremonial presence. This taxidermy specimen, collected in the mid-19th century, depicts the bird perched on a branch with its wings slightly spread. Its glass eyes look strikingly lifelike, even though no living representatives of this species remain in the world.

Surrounded by these silent witnesses of the past, I ask myself: what can we learn from these birds that are no longer seen in the wild? And more importantly, how can this knowledge help protect those that still survive?

A taxidermy specimen of the extinct Hawaiʻi mamo (Drepanis pacifica) from the Cambridge Museum of Zoology. The specimen is mounted on a wooden perch with original collection tags attached. [Image credit: Grigory Evtukh]

What are Hawaiian honeycreepers and why are they disappearing?

Hawaiian honeycreepers (Drepanidinae) are a group of birds within the finch family (Fringillidae) that evolved in isolation on the Hawaiian Islands. Due to the absence of competitors and predators, they occupied a variety of ecological niches, evolving into dozens of species with unique adaptations: long, curved beaks for nectar feeding, powerful beaks for cracking seeds, and even specialized beaks for extracting larvae from under tree bark.

However, with the arrival of humans, the situation changed drastically. Introduced animals like cats, rats and pigs, diseases such as avian malaria, and deforestation led to the extinction of at least 34 species of Hawaiian honeycreepers, with 14 disappearing after the arrival of Polynesians and another 20 following European colonization. The most significant losses occurred in the 20th century, as honeycreeper populations began to decline rapidly due to the spread of mosquitoes carrying avian malaria. Some of the remaining species are now on the brink of extinction. This group of birds historically included at least 57 species, yet today, fewer than half of Hawaii’s once-thriving honeycreeper species still exist. Birds that once thrived in the montane forests of Hawaii have now become symbols of the region’s ecological crisis.

Museum collections as a source of knowledge

Collections like those in Cambridge allow scientists to study both extinct and surviving species. The museum holds dozens of honeycreeper specimens, including type specimens described as early as the 19th century. Each specimen represents a frozen moment in evolutionary history. Museum collections offer the opportunity to study morphology, examine anatomical changes, and even reconstruct past ecosystems.

In my research, I use standardized photography and microCT scanning methods. These technologies allow for a detailed analysis of beak shape, skull structure, and other morphological features. For example, I compare honeycreeper beaks of different lengths and curvatures. In combination with phylogeny this data will help me to understand how fast these birds change their morphological features and evolve.

A traditional Hawaiian feather cloak (ʻahuʻula) made from olona fiber netting and feathers of the ʻiʻiwi (Drepanis coccinea), ʻōʻō (Moho spp.), and mamo (Drepanis pacifica). Creating a single cloak required the feathers of hundreds, sometimes thousands, of birds, many of which were captured and killed specifically for this purpose, contributing to the decline of several species, including the now-extinct Hawaiʻi mamo. In German, Hawaiian honeycreepers are referred to as “Kleidervögel” (clothing birds) due to their historical use in featherwork. [Image credit: © The Trustees of the British Museum, CC BY-NC-SA 4.0]

Hawaiʻi mamo as an example of a lost species

Hawaiʻi mamo is one of the most well-known honeycreeper species that disappeared due to hunting and habitat destruction. These birds fed on the nectar of native trees such as ʻōhiʻa lehua (Metrosideros polymorpha), which played a crucial role in the Hawaiian ecosystem. Their bright yellow feathers were used in the creation of traditional royal cloaks (ʻahuʻula) and helmets (mahiole) worn by Hawaiian chiefs and kings during ceremonies and warfare. These cloaks were crafted from thousands of individual feathers and hundreds of individual birds such as ʻōʻō (Moho) and mamo (Drepanis), symbolizing power and divine protection. The arrival of Europeans played a decisive role in the extinction of this species.

The study of museum specimens helps in the conservation of remaining species. For example, analyzing beak structure and dietary preferences helps in designing habitat restoration programs. Museum collection data are used in conservation initiatives such as the Kauaʻi Forest Bird Recovery Project and the Hawaiian Forest Bird Recovery Project, which focus on restoring local ecosystems, controlling invasive species, and protecting vulnerable bird populations.

A vibrant ʻIʻiwi (Drepanis coccinea) perched on a branch. This species, once widespread across the Hawaiian Islands, is now facing habitat loss and the threat of avian malaria but remains one of the most recognizable honeycreepers. [Image credit: Cricket Raspet / CC BY 4.0]

Scientists use museum specimens to analyze the genetic diversity of historical and modern populations, allowing them to identify species at the highest risk of extinction and develop conservation strategies. DNA analysis of extinct honeycreepers provides insights into how their gene pools differed from surviving species, helping assess the genetic resilience of remaining populations.

Additionally, data on extinct species are used to model ecological changes. Studies show that the disappearance of one species can trigger cascading effects on the ecosystem, making museum-based models crucial for predicting potential threats and adapting conservation measures. Such knowledge is important not only for Hawaii but also for preserving other island ecosystems. For example, in the Galápagos, active programs are working to restore endemic species affected by invasive animals, while in Madagascar, conservation efforts are intensifying to protect unique forest ecosystems. Human impact on these regions has led to significant biodiversity loss, and research based on museum data helps develop more effective conservation strategies.

How museum research helps in the real world

Many conservation projects rely on museum research. Historical data help scientists understand how species’ ranges have shifted over time and how they responded to environmental changes. These insights allow researchers to model how remaining populations will react to modern ecological challenges.

Recent studies suggest that some extinct species, such as the Poʻo-uli (Melamprosops phaeosoma), might have had a chance of survival if more aggressive conservation measures had been taken earlier. These lessons from the past help avoid similar mistakes in the future.

In addition to field research, museums facilitate international collaboration. Through digitization, researchers from different countries can study digital specimens and share data. This is especially crucial for species whose populations are critically endangered.

A Poʻouli (Melamprosops phaeosoma) being handled by researchers during conservation efforts. This extinct Hawaiian honeycreeper was discovered in 1973 and rapidly declined due to habitat loss, disease, and the fragmentation of its small population. The last confirmed sighting of a Poʻouli was in 2004. [Image credit: Paul E. Baker / U.S. Fish and Wildlife Service]

Conclusion

Museum collections play a crucial role in preserving biological heritage. Studying specimens like Hawaiʻi mamo allows us not only to explore the past but also to develop tools for protecting biodiversity in the future. Research based on these data helps determine the necessary steps for conserving vulnerable species and ecosystems.

Biodiversity conservation is not just about protecting individual species but about restoring ecosystems and preventing the repetition of past mistakes. Museum specimens give scientists the ability to understand the factors that led to species’ extinction and use this knowledge to develop effective conservation strategies.

Today, digitization of collections, international collaboration, and genetic research allow us to extract invaluable information even from long-extinct organisms. These data help not only analyze the past but also design programs for conserving surviving species, such as habitat restoration, invasive species control, and disease management.

Now, sitting in the quiet basement of the museum, I realize that these birds are not truly gone —their history lives on in science, in conservation initiatives, and in our ongoing efforts to prevent further losses.


[Image credit: private]

Grigory Evtukh is currently pursuing his PhD at the Leibniz Institute for the Analysis of Biodiversity Change (LIB) in Germany.


Title picture: A vibrant ʻIʻiwi (Drepanis coccinea) perched on a branch. This species, once widespread across the Hawaiian Islands, is now facing habitat loss and the threat of avian malaria but remains one of the most recognizable honeycreepers. [Image credit: Cricket Raspet / CC BY 4.0]

Vergessen – Stillgelegte Objekte in musealen Sammlungen

In diesem Beitrag begibt sich Anna-Magdalena Heide auf die Suche nach dem Kontext einer Reihe vergessener Kinderzeichnungen im Deutschen Bergbau-Museum Bochum.

Museen leben von ihren Objekten und den Geschichten, die sich mit ihnen erzählen lassen. Am Beispiel von Kinderzeichnungen wird veranschaulicht, dass Museen ihr kulturelles Erbe stilllegen, wenn sie die Entstehungs- und Nutzungskontexte ihrer Objekte nicht überliefern.

Museums depend on objects and the stories that can be told with them. The example of children’s drawings demonstrates that museums can suppress their own cultural heritage by neglecting the contexts in which their objects were originally created and used.


Die Vorstellung, dass in Museen die Schätze der Welt verwahrt werden, hält sich hartnäckig. Was es in die Depots dieser Gedächtniseinrichtungen geschafft hat, so scheint sich dies bisweilen nach außen darzustellen, ist durch einen kritischen Bewertungsprozess gegangen und hat sich als ‚relevantes‘ und ‚bedeutsames‘ Kulturerbe behauptet. Dass die Aufnahme von Objekten in museale Sammlungen aber auch von Zufälligkeiten, pragmatischen Entscheidungen, strategischen Zwängen oder der Affinität von Sammlungsmitarbeitenden für ihre Arbeit bestimmt wird, liegt in der Regel außerhalb des Wahrnehmungshorizonts. Dies führt in der intellektuellen Auseinandersetzung mit materieller Kultur schnell dazu, dass Objekten fast zwanghaft irgendetwas ‚Besonderes‘, ‚Interessantes‘ oder wenigstens ein diffuses ‚Bedeutungspotential‘ abgerungen wird.

Kohlezeichnung eines Bochumer Kindes, montan.dok 030002040007

Ganz Wichtiges, weniger Wichtiges und Unwichtiges in musealen Sammlungen

Am Beispiel von zwei Konvoluten an Kinderzeichnungen im Deutschen Bergbau-Museum Bochum (DBM) lässt sich aufzeigen, dass die Realität im Arbeitsalltag musealer Sammlungen auch eine andere sein kann. Natürlich gibt es in jeder Sammlung die Publikumsrenner, die gerne für Ausstellungen genutzt werden, weil sie die größten, schönsten, seltensten, berühmtesten ihrer Art sind oder irgendeinen anderen Superlativ für sich verbuchen können, der ihnen ihre Berechtigung in den musealen Sammlungen sichert. Es gibt auch Objekte, die solchen Legitimationslogiken nicht folgen, aber anlassbezogen Interesse auf sich ziehen. Und dann gibt es einen nicht unerheblichen Teil an Objekten, mit denen man überhaupt nichts anzufangen weiß, weil sie von irgendwem, irgendwann, von irgendwoher mitgebracht, dann aber sang- und klanglos in einem Schrank oder einer Schublade versenkt worden sind.

Ein solches Beispiel sind 22 Kindermalereien bzw. -zeichnungen, die nicht so recht in das Sammlungsprofil des Deutschen Bergbau-Museums Bochum passen wollen, sich aber seit sieben Jahrzehnten physisch im Haus befinden. Seit drei Jahrzehnten sind sie offiziell Teil der Musealen Sammlungen des Montanhistorischen Dokumentationszentrums (montan.dok) im DBM. Ihre Existenz ist im Laufe der Jahre aber augenscheinlich mehrfach in Vergessenheit geraten.

Aquarellmalerei eines Kindes, montan.dok 030002040009

Zufallsfunde in den Sammlungen

Aufgetaucht waren diese Werke aus Kinderhand bei Erschließungsarbeiten im Rahmen des noch laufenden Projekts „Digitale Infrastrukturen im Deutschen Bergbau-Museum Bochum und virtuelle Zugänglichkeit zum Bergbauerbe“ im montan.dok des DBM, in dem Zeichnungen, Druckgrafiken und Malereien aus den Musealen Sammlungen des Hauses standardisiert dokumentiert und digitalisiert werden. Eine vergleichsweise hohe Beachtung – gemessen an der für sie verwandten Zeit bei der Dokumentation – erhielten die Objekte in erster Linie deshalb, weil aufgrund fehlender Informationen keine normierte Erfassung erfolgen konnte.

Über die Objekte selbst und die Sammlungsdokumentation war zunächst festzustellen, dass die Malereien und Zeichnungen in den frühen 1990er-Jahren Sammlungsmitarbeitenden in die Hände gefallen waren. Das erste Konvolut mit neun Werken ist 1990 als Schenkung des Fördervereins des Bochumer Bergbau-Museums aufgenommen worden, das zweite, mit 13 Einzelblättern, ist drei Jahre später aus Objekten des „nicht inventarisierten Altbestands“ gebildet worden. Außerdem ist den analogen Dokumentationsmedien zu entnehmen, dass es sich um Werke von zehn- bis vierzehnjährigen Gymnasiast:innen aus dem Ruhrgebiet und Münster handelt, die – irgendwann – in den 1950er-Jahren in Ausstellungen des Fördervereins zu sehen waren. Erst durch Zeitungs- und Zeitschriftenbeiträge, Fotografien, Vortragsmanuskripte und Korrespondenzen ließen sich die anfänglich völlig anonymen Objekte erfolgreich in ihre Entstehungskontexte einordnen. Dass es sich hierbei keineswegs um die freie künstlerische Auseinandersetzung mit dem Thema „Bergbau“ handelt, offenbart ein Vortragsskript des stellvertretenden Museumsdirektors aus dem Jahr 1955:

„Wir haben gelegentlich in einer höheren Schule außerhalb des Reviers im Zeichenunterricht die Aufgabe stellen lassen, in einer Zeichnung wiederzugeben, was sich die Kinder – es handelte sich dabei um Mädchen der Mittelschule eines Lyzeums – unter einer Zeche vorstellen. Das Ergebnis war erschütternd. Ein erschreckend großer Teil […] zeichnete ein großes Tor und dahinter eine Menge hoher Gebäude. Über einen Platz oder hinter dem Tor liefen Menschen, die Verunglückte auf Bahren trugen oder fuhren Krankenwagen usw. Wenn bei dieser am häufigsten wiederkehrenden Darstellung viele der Mädchen auch durch ihre Nachbarn beeinflußt waren, läßt sich doch die Tatsache nicht von der Hand weisen, daß viele dieser Kinder den Bergbau ohne weiteres sofort mit einem Unglück verbinden. Zweifellos ist das nicht nur bei Kindern der Fall. Diese Auffassung hat dem Bergbau in den letzten Jahrzehnten ungeheuer geschadet und schadet ihm heute noch. […] Hier aufklärend einzugreifen, ist eine der wichtigsten Aufgaben des Bergbau-Museums.“[1]

Legte die lückenhafte Objektdokumentation zunächst nahe, dass es sich hier um einigermaßen belanglose Versuche von Schüler:innen handelte, Vorstellungen vom Bergbau auf das Papier zu bringen, stellte die Kontextualisierung des Materials die Kinderzeichnungen hingegen in den Zusammenhang von PR-Analyse, Wahrnehmungskontrolle und Nachwuchswerbung der um Arbeitskräfte ringenden Bergbaubranche in den 1950er-Jahren.

Tuschestiftzeichnung einer Vierzehnjährigen aus Münster, montan.dok 030002040003

Objekte als “Quellen zweiter Klasse”

Paradoxerweise führte die Anreicherung der Objektinformationen mit den archivischen Quellen immer weiter von den eigentlichen Objekten weg. So habe ich zwar meinen Blogbeitrag mit Beispielen aus den Konvoluten illustrativ bebildert. Gegenstand meiner Analyse sind aber nicht die Motive. Denn der Umfang des Materials erlaubt keinen bilddiskursanalytischen Zugriff. Für einen kulturwissenschaftlichen Ansatz, der sich im Wesentlichen für die Wechselbeziehung zwischen Ding und Mensch interessiert, fehlt wiederum die Perspektive der Urheber:innen. Letztlich dienten und dienen diese Kindermalereien – so hat Silke Göttsch es in den frühen 1990er-Jahren pointiert formuliert – als „Quellen zweiter Klasse“ und damit lediglich als Illustration von Erkenntnissen, die aus Schriftquellen gewonnen worden sind. Im vorliegenden Beispiel sind sie die Türöffner für ein abstrakteres Thema – nämlich die Kulturpolitik im Ruhrgebiet der 1950er-Jahre.

Aquarellmalerei eines Zehnjährigen aus Essen, montan.dok 030002789004

Stilllegung kulturellen Erbes durch mangelnde Kontextualisierung

Was bedeutet dies für den Erbestatus dieser Objekte? In den 1950er-Jahren sahen die Vertreter des Bergbau-Museums weder eine Veranlassung, diese Objekte den Sammlungen einzuverleiben noch sie zu entsorgen. Man schrieb ihnen offenbar vielmehr eine latente, nicht ganz greifbare, Bedeutsamkeit zu. Dass ihre physische Präsenz später einmal das jahrzehntelang gepflegte Narrativ vom Bergbau-Museum als fördernde Institution einer Kultur „von unten“ ins Wanken bringen würde, war dabei wohl kaum intendiert. So lässt die inhaltlich zurückhaltende Sammlungsdokumentation der 1990er-Jahre begründet vermuten, dass die Adelung zum „Kulturerbe“ – über den bloßen Akt der Inventarnummernvergabe – ohne Kenntnisse der Zusammenhänge erfolgte, die schlicht in Vergessenheit geraten waren. Damit betrug die Latenzzeit 72 Jahre, ehe die ursprünglichen Bedeutungshorizonte als solche erkennbar wurden.

Haben die Kindermalereien nun endgültig ausgedient und sind „stillgelegt“, weil ihre Entstehungszusammenhänge aufgedeckt sind und die einzelnen Motive durch die mangelnde, kontextualisierende Dokumentation nicht produktiv für die Forschung genutzt werden können? Ikonografische Vergleiche mit Werken aus der bildenden Kunst, eine Ausstellung der Kinderzeichnungen – ggf. ergänzt durch Werke anderer Museen – oder materialanalytische Zugänge zum Farbauftrag wären Beispiele, um das latente Forschungs- und Bedeutungspotential der Quellen hervorzuheben. Was in den 1950er-Jahren unschlüssig beiseitegelegt und in den 1990er-Jahren beiläufig inventarisiert wurde, könnte also im Zuge seiner Befragung eine Statusaufwertung und Bedeutungsverschiebung erfahren. Als empirisch arbeitende Kulturwissenschaftlerin und Museumspraktikerin argumentiere ich allerdings, dass keine dieser Kindermalereien für sich genommen einen Alters-, Erinnerungs-, Kunst-, Denkmal- oder Symbolwert geltend machen kann.[2] Gemessen an anderen Objekten sind sie mit etwas über 70 Jahren nicht besonders alt. Ihre Motive sind weder ungewöhnlich noch bedeutungsschwanger oder symbolträchtig. Auch eine besondere Raffinesse in der Umsetzung fällt nicht ins Auge. Hinzu kommt, dass Kinderzeichnungen und -malereien in der Kunstsammlung des Deutschen Bergbau-Museums eine absolute Ausnahme sind. Wer von ihrer Existenz also nicht ohnehin schon weiß, wird bei Recherchen allerhöchstens zufällig auf sie stoßen. Meines Erachtens sind diese zwei Konvolute deshalb nach einer kurzen Phase des anlassbezogenen Erinnerns auf dem Weg in die Vergessenheit.

Hans-Peter Hahn warnt im Zusammenhang mit Alltagsdingen davor, Dinge zu funktionalisieren beziehungsweise ihnen eindeutige Bedeutungen zuweisen oder absprechen zu wollen. Was bedeutet dieses „in der Schwebehalten“ aber für das kulturelle Erbe in Gedächtniseinrichtungen, wenn die ursprünglichen Bedeutungszusammenhänge nur noch als Fußnoten mitgeführt oder irrelevant werden? Was bedeutet es am Ende für Sammlungsprofile, wenn jedes Ding potentiell ein bedeutsames Zeichen werden kann? Der Erbestatus der Kinderzeichnungen und -malereien ließe sich meines Erachtens lediglich aufwerten, wenn sich die Urheber:innen zu ihren Werken noch einmal befragen ließen. Letztlich zeigt dieses Beispiel einmal mehr, welchen Stellenwert Infrastrukturaufgaben in Museen haben müssen, damit Objekte nicht als stumme Zeugen einer unbestimmten Vergangenheit in den Depots verstauben.

Aquarellmalerei eines Elfjährigen aus Essen, montan.dok 030002789009


[1] Maschinenschriftliches Vortragsskript „Das Bergbau-Museum“ von Julius Raub, 08.09.1955, in: montan.dok/BBA 112/2215.

[2] Vgl. Samida, Stefanie: Kulturerbe als Herausforderung. Reflexionen zum ›Heritage-Boom‹ aus fachübergreifender Perspektive. In: WERKSTATTGESCHICHTE / Heft 64 (2013), S. 111-127. Online einsehbar: https://werkstattgeschichte.de/wp-content/uploads/2014/11/WG64_111-127_SAMIDA_KULTURERBE.pdf (29.02.2024).


Literatur

Göttsch, Silke: Universität und Museum – mögliche Begegnungen?, in: Abel, Susanne (Hrsg.): Rekonstruktion von Wirklichkeit im Museum. Tagungsbeiträge der Arbeitsgruppe „Kulturhistorische Museen“ in der deutschen Gesellschaft für Volkskunde. Hildesheim, 3. – 5. Oktober 1990, Hildesheim 1992, S. 46-52.

Hahn, Hans-Peter: Die geringen Dinge des Alltags. Kritische Anmerkungen zu einigen aktuellen Trends der Material Culture Studies, in: Braun, Karl/Dieterich, Claus-Marco/Treiber, Angela (Hrsg.): Materialisierung von Kultur. Diskurse, Dinge, Praktiken, Würzburg 2015, S. 28-42.

Hahn, Hans-Peter: How Close are Things to us? On the Relation between the Incidental and the Valuable, in: Cambridge Archaeological Journal, 30 (2020) H. 1, S. 168-172.

König, Gudrun: Auf dem Rücken der Dinge. Materielle Kultur und Kulturwissenschaft, in: Maase, Kaspar/Bausinger, Hermann/Warneken, Bernd (Hrsg.): Unterwelten der Kultur. Themen und Theorien der volkskundlichen Kulturwissenschaft, Köln/Weimar/Wien 2003, S. 95-118.

Samida, Stefanie: Kulturerbe als Herausforderung. Reflexionen zum ›Heritage-Boom‹ aus fachübergreifender Perspektive, in: WERKSTATTGESCHICHTE (2013) H. 64, S. 111-127. Online einsehbar: https://werkstattgeschichte.de/wp-content/uploads/2014/11/WG64_111-127_SAMIDA_KULTURERBE.pdf (29.02.2024).

Samida, Stefanie: Materielle Kultur und dann? Kulturwissenschaftliche Anmerkungen zu einem aktuellen Trend in der Zeitgeschichtsforschung, in: Zeithistorische Forschungen/Studies in Contemporary History 13 (2016) H. 3, S. 506-514. Online einsehbar: https://doi.org/10.14765/zzf.dok-1393 (29.02.2024).


Anna-Magdalena Heide ist wissenschaftliche Mitarbeiterin am Deutschen Bergbau-Museum Bochum, Leibniz-Forschungsmuseum für Georessourcen in Bochum.


Titelbild: Aquarellmalerei eines Zehnjährigen aus Essen, montan.dok 030002789001

Quellen: Montanhistorisches Dokumentationszentrum (montan.dok) beim Deutschen Bergbau-Museum Bochum/Bergbau-Archiv Bochum (BBA) 112/2215.