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Integrated in prometheus is the Image database ‘Architecture Museum’ of the Technical University of Berlin since 2008. A lot has happened and developed over the years, not only in the digitization of further drawings, prints and photographs or the link to the The Integrated Authority File (GND) of the German National Library.

It was definitely time for an update. Instead of 26,636, there are now 161,680 data records available for your research in the field of architectural history. Many of the works and digital copies are in the public domain and the TU Berlin is happy to receive an image credit.

We hope you enjoy your research.




In prometheus you can currently access more than 3.5 million images for your research work, papers and presentations as well as for your teaching. Nevertheless, the images you need for your specific topics are often missing. Or you have just been traveling and want to add your own current images of cultural objects. You know that you can upload all these images to your own image database with a personal account at prometheus and use them in the same way as the 126 image databases included, right? On our help pages you can read how the Upload into your own image database works.
Your uploads will then be directly available for your own image collections. After editorial review for quality assurance purposes by the prometheus office, you can also make the images accessible to others in the image archive and, since last year, the images also appear in the search results if you do not switch off this function.

Would you like to use your own image database in prometheus as an institute, school or project? Please get in touch with us and we will set up an institute database for you, such as the „BaSaar Image Archive“ of Art History at Saarland University. The first 32 data records are indexed and accessible for general searches.




We mentioned it briefly in the last newsletter: the realization of a new design in the image archive is currently our “biggest” project. We work together on the open source design and prototyping platform Penpot from Kaleidos, discuss individual drafts in weekly Zoom sessions, for example for the list view of the search results or about the upload workflow and make overarching decisions about functionality and design. Here is a view of the complex workflow at Penpot for the individual areas at prometheus from “search” to “administration”.

To be continued …




April 1st was our birthday again. It wasn’t a big one, but a birthday is a birthday, and it’s an opportunity for us to take a quick look back, update the figures, take the next steps and discuss new plans.
It all started 2001 with a meeting in Berlin and a year later we recruited partners on quite a few occasions. For this purpose, we have posted on Instagram and will continue to comb through our hard drives in the next few days to publish pictures from the past few years there.

We publish current figures from the image archive every two weeks in the newsletter, but once a year we update them on Facebook in the project information section. This time we were able to add six image databases and almost 300,000 images. We will inform you here about the next steps, new plans and ideas over the next few months. This includes, among other things, further integration of image databases, but above all the implementation of the new design in the image archive.




Within the consortium NFDI4Culture, whose goal is to build a needs-oriented infrastructure for research data on material and intangible cultural assets in the National Research Data Infrastructure, the networking of the Culture Knowledge Graph advanced. This creates a connection between all research data in the subject areas from architecture, art and music to theater, dance, film and media studies.
prometheus is already integrated as a resource and the 26 Open -Access image databases accessed via the API, so that these will soon be integrated into the Culture Knowledge Graph.
Via the Interface (API) everyone has the opportunity to speak directly to pandora, the software from prometheus, the digital image archive, and perform the following actions: search, retrieve metadata and images, explore image collections, and upload images. Statistical queries are also possible.

An example of the query of metadata for individual images: „Aaron goes to meet Moses (Rieter window)“




The Heidelberg University Library’s new image database, which has been integrated into prometheus for a few days now, comprises 2,343 data records. The aim of this HeidICON pool „UB Anatomische Illustrationen “ is the complete formal and content-related indexing of the illustrations of selected 19th century anatomical plates from the library’s holdings. They originate from the Cooperation with the Institute of Anatomy and Cell Biology of the University of Heidelberg. The selected textbooks, illustrations and records reflect the content of the former teaching and learning collection and document the contemporary focus of research.




Today we would like to take another look at the image similarity search integrated in prometheus, which creates image vectors based on the SwAV (Swapping Assignments between Views) self-supervised learning algorithm. They are limited to 80 dimensions sufficient for the result, which relate, for example, to color properties or the brightness of pixels as well as to the structural image composition. These created image vectors are pre-calculated for the images in the image archive and stored in the index so that the search engine queries are reduced to calculating the distance between these vectors stored in the index. They have not yet been created and indexed for all images in prometheus, but this is done at regular intervals. If images are deleted from the original databases and are therefore “not available”, they will remain in the index until the next update.

We occasionally receive feedback on the image similarity search from users who are not convinced by the results because, for example, one of our examples, a winter landscape by Witsen, shows many summer landscapes or „Asparagus“ by Edouard Manet in the results.

What do you think? Are the images similar or not similar?

We see the similarity in the images, between snow and sand, which we do not evaluate based on the metadata associated with the image. And yes, there are some surprising, astonishing and sometimes inexplicable results that we find in this way, especially when the calculated distance is greater in the results listed below.

But there are also fascinating results, as in the case of the „Madonna and Child“ by Giovanni Bellini.

Most of the time, however, we don’t do exploratory searches, but rather targeted searches to get less unexpected results and then we search for winter landscape or the keywords winter landscape, winter, landscape in the title using the Advanced Search.

Have you already tried the image similarity search?




Inspired by the graphic „Dependency“, today we briefly present the most important facts about the development process for the prometheus software.
In the current main development stack we have ruby on rails 7.1, ruby 3.2, elasticsearch 8.7, mariadb 10.11 and apache 2.4 alongside the other components imagemagick for processing images, ffmpeg for processing videos and nokogiri for processing most metadata imports. First, we test all changes and new features on our test suite, which consists of two parts. On the one hand, we maintain a unit test suite with Minitest to test important components of our application in isolation, such as the authorization model and image processing. Secondly, our e2e suite with selenium-webdriver simulates real users launching a browser and using the Prometheus application. No code is ever deployed to our servers without passing all tests first.
To ensure that we can easily onboard new team members while maintaining a consistent coding style, we use rubocop during our test runs to enforce a few rules. Similarly, we perform security audits with tools like Brakeman. During development, we use a number of debuggers and profilers to isolate bottlenecks and fix hard-to-find bugs.
We operate the image archive on three servers with a total of 12 CPUs and 48G RAM. Recently, these and our other servers were migrated to Debian 12, the basis for many popular Linux distributions such as Ubuntu or Mint.




Every week the top image bar on the homepage of prometheus changes and gives a first visual impression of the image series of the week. The topics are mostly inspired by current exhibitions, for example this week’s „Anna Oppermann. A Retro Perspective“ in the Bundeskunsthalle in Bonn. We often take an aspect of the exhibition or the artist’s work, such as Anna Oppermann’s “Ensembles” in this case, and look for suitable images in the prometheus image archive. We cannot always rely on a research database and 2,191 data sets on the artist’s work.
However, there is always a public image collection at prometheus that you can click on directly (see Fig. “1.”) and where you can find more material on the topic. As of today, you can also click on the thumbnails directly (see Fig. “2.”) and the associated data record will be displayed in the image archive.

We would be happy to accept your topics for a #pictureSeriesOfTheWeek, for an exhibition, but also for projects or campaigns. Get in touch with us and see how it can be implemented.




This year we will once again begin our information section in the picture archive with a look at the annual list of the artists you most frequently searched for last year.
Paula Modersohn-Becker made it to the top in 2022 but this year she came in 9th place.
She was replaced at the top by Pablo Picasso, followed by Vincent van Gogh and Max Ernst. The most wanted artist in 2023 is Hannah Höch behind this trio. With her there are seven other artists in the top 20.

All top 20 in 2023:

1. Pablo Picasso
2. Vincent van Gogh
3. Max Ernst
4. Hannah Höch
5. René Magritte
6. Claude Monet
7. Gabriele Münter
8. Caspar David Friedrich
9. Paula Modersohn-Becker
10. Hilma af Klint
11. Caravaggio
12. Albrecht Dürer
13. Otto Dix
14. Frida Kahlo
15. Nan Goldin
16. Henri Matisse
17. Gerhard Richter
18. Kandinsky
19. Rebecca Horn
20. Cindy Sherman

A lot has also changed in the list of the ten living artists who aroused the most interest on Google and which internet service providers identified for Monopol magazine compared to last year. Last year’s number 1 Banksy is no longer in the top 10, just like Jeff Koons, Cindy Sherman, Damien Hirst and Wolfgang Tillmanns.

1. Gerhard Richter
2. Yoko Ono
3. Marina Abramović
4. Anselm Kiefer
5. Leon Löwentraut
6. David Hockney
7. Yayoi Kusama
8. Isa Genzken
9. Kaws
10. Georg Baselitz