The Distant Viewing Lab uses and develops computational techniques to analyze visual culture on a large scale. We develop tools, methods, and datasets that can be re-used by other researchers. The lab engages closely with critical cultural and data studies, aiming to make explicit the interpretive act of algorithmic logic. The Lab is directed by Taylor Arnold and Lauren Tilton. For the theoretical basis of the lab, please see our book Distant Viewing (MIT, 2023).

• Arnold, T. and Tilton, L. (2024) In: Jaillant, L., Warwick, C., Gooding, P., Aske, K., Layne-Worthey, G. and Downie, J. S. (Eds.) Navigating Artificial Intelligence for Cultural Heritage Organisations. University College London (UCL) Press.
• Van der Heijden, T., Arnold, T. and Tilton, L. (2025) "Distant Viewing the Amateur Film Platform." In: Dang, S., van der Heijden, T., and Olesen, C.G. (Eds.) Doing Digital Film History: Concepts, Tools, Practices. De Gruyter Oldenbourg. [pdf]
• Arnold, T., Wigard, J. and Tilton, L. (2023) "Understanding Peanuts and Schulzian Symmetry: Panel Detection, Caption Detection, and Gag Panels in 17,897 Comic Strips Through Distant Viewing." Cultural Analytics, 8(3): 1--31. [pdf]
• T. Arnold and L. Tilton. (2023) Distant Viewing: Computational Exploration of Digital Images. MIT Press. [book] [data]
• T. Arnold, L. Tilton and J. Wigard. (2022) "Automatic Identification and Classification of Portraits in a Corpus of Historical Photographs." CEUR Workshop Proceedings. [pdf]
• T. Arnold and L. Tilton. (2022) "Analysing Audio/Visual Data in the Digital Humanities." In: J. O'Sullivan, (Ed.) Bloomsbury Handbook of Digital Humanities. Bloomsbury Press. [pdf]
• T. Arnold, J. v. Gorp, S. Scagliola and L. Tilton. (2021) "Special Issue: AudioVisual Data in DH." Digital Humanities Quarterly, 15.1. [link]
• T. Arnold and L. Tilton. (2021) "Depth in Deep Learning: Knowledgeable, Layered, and Impenetrable." In: Redrobe, K. and Scheible, J. (Eds.) Deep Mediations. University of Minnesota Press. [pdf]
• T. Arnold and L. Tilton. (2020) "Distant Viewing Toolkit: A Python Package for the Analysis of Visual Culture." Journal of Open Source Software. [pdf]
• T. Arnold, L. Tilton., and A. Berke. (2019) "Visual Style in Two Network Era Sitcoms." Cultural Analytics. [pdf]
• T. Arnold and L. Tilton. (2019) "Distant Viewing: Analyzing Large Visual Corpora." Digital Scholarship in the Humanities. [pdf]

• Photogrammar: A web-based visualization platform for exploring the 170,000 photographs taken by the FSA and OWI agencies of the U.S. Federal Government between 1935 and 1943. [link]
• ADDI (Access & Discovery of Documentary Images) was designed to adapt and apply computer vision algorithms to aid in the discovery and use of digital collections, specifically documentary photography collections held by the Library of Congress [link]

• Distant Viewing Toolkit for the Analysis of Visual Culture is a Python package that facilitates the computational analysis of still and moving images. [link]
• PGVis is a digital public humanities software for visualizing image collections. It is currently under development.

The lab offers in-person and virtual workshops at various levels, ranging from a few hours to a few weeks, related to the content of this text. Workshops have been offered at a number of institutions and events, including Yale, Harvard, Carnegie Mellon University, Université Paris Diderot, UseR!, the European Summer University, NYU Abu Dhabi, and the Université de Rennes. Please contact us for more information.

The lab and its projects have received generous funding from the National Endowement for the Humanities, the Mellon Foundation, and the University of Richmond.