The course has a double orientation: theoretical exchange and critical discussions will be combined with practical sessions (lab-based sessions) through which participants will work collaboratively on common projects. Each participant can only join one of the tracks. During your application, you should select the tracks in your preferred order. Take into consideration that participants cannot switch tracks once they are registered in the summer school.
August 29th – September 3rd, 2022
The course is organized around five tracks.
Track A: Digital Display Spaces. Greg Niemeyer (UC Berkeley), will work with participants in configuring digital spaces for exhibitions on virtual platforms such as newart.city and modzilla hub. Techniques include basic modeling and animation, .fbx or .glb file format, spatial strategies for virtual engagement, data visualization and local sound synchronization in virtual spaces. Track A participants will create content and curate content produced in the other Tracks to cumulate in an online virtual exhibit about DAHSS 2021.
Cultural data–well used, managed and analysed–is of immense value for the understanding of art history and its impact on society. Open data is an opportunity to engage the public with cultural heritage, foster diversity and create knowledge. In this track, led by Harald Klinke (LMU Munich), we will investigate open data sources, learn the fundamentals of cultural data analysis, and use simple but powerful computational tools. No prior experience is necessary. Bring your own data. You can find more information at: http://dahss22.harald-klinke.de/
This track led by Justin Underhill (Visualization Lab for Digital Art History, UC Berkeley) will explore 3D data acquisition techniques, such as photogrammetry and laser scanning, and their use in VR and related virtual environments. We will experiment with different ways of exploring virtual space, and will see how we might use augmented and virtual reality to practice Digital Art History. We will also ask ourselves how to best design visualizations and historical reconstructions for these environments.
Track D, led by Leonardo Impett (University of Cambridge), will think about applications of AI and computer vision to the history of art and visual studies. Thinking about ‘the visual’ is a major difference between digital art history and ‘digital humanities on art history’. We will look at the long history of the computer analysis of images from the late 1980s to today, as well as thinking about the implicit theories of vision that underpin computer vision systems today. We’ll learn to use some basic image processing tools and more sophisticated AI and machine learning algorithms to search within, organise, or study large image sets. Using tools like Scikit-Image, Tensorflow, and ImageGraph (a visual AI tool which we wrote specifically for DAHSS), we will build systems that deal with genuinely big image datasets. For the first time, we will also look at AI systems that generate images like DALL·E, and ask how we might use them as art historians.
Track E led by Yadira Lizama Mué (CulturePlex Lab, Western Ontario University) will explore the applications of NLP to understand what textual big data can tell us about art. By combining the power of linguistics and computer science, NLP considers the guidelines and structure of language and creates intelligent systems that comprehend, break down, and separate meaning from text and speech. We will explore a wide range of NLP topics relevant to the context of Digital Art History, starting with the basics like word tokenization & tagging, semantic similarity, named-entity recognition, topic modelling, and leading to deep learning applications to sentiment analysis, text classification, and human-like text generation. We will gain practical experience using tools such as Spacy, and TensorFlow while exploring collections of art-related texts in H.W. Wilson’s Art Full Text database, Project Muse, Wikipedia, and social media platforms. You are welcome to bring your own data and ask questions about the applications of NLP to your own research.
No matter what track you pick, you will also see what students do in other tracks in our daily plenary session. In the plenary sessions, notable alumni of the DAHSS program will also share feedback and observations about how DAHSS helped them in their work.
Each day, we will have lighting talks from DAHSS alumni, to promote their projects, research and networking between the current students and the alumni. Over the years, we have settled a strong DAHSS alumni network and community. We also organize online coffee talks during the whole year to continue promoting and building a Digital Art History community.