By Thunnis van Oort


The last Salon of the season was dedicated to Digital Art History. Not the history of digital art, but on various uses of digital methods and data for studying art history. One overarching element in this broad topic was that all speakers are interested in linking and connecting art historical and cultural data.


Linking historical data is the mission of the afternoon’s first speaker, Menno den Engelse, free-lance programmer and ‘data maker’, active in a variety of digital humanities projects, including Amsterdam Time Machine and Adamlink. He summed up four reasons to build an authoritative list of exhibitions in the Netherlands: it would (1) help us better understand the cultural landscapes of the past, (2) ‘liberate’ existing datasets, which are not yet (publically) available or linked, (3) help make connections between cultural heritage objects to each other and to their contexts, and (4) facilitate researchers and heritage professionals in their study of art and artists. To make a start, Menno suggested a practical modus operandi: first collect some data, model it, publish and use it, and only then obtain more and higher quality data. As an example, he showcased his work on the exhibitions in the 19th century Amsterdam landmark venue Paleis voor Volksvlijt, catalogued at


Secondly, Rachel Esner (Department of Art History, UvA) presented her work on documenting curatorial practices in Dutch art museums in the post-war era. Together with Fieke Konijn, emeritus of VU University Amsterdam, Rachel completed a pilot project, funded with a KIEM grant from NWO. Aim of the project was to take stock of the of archival material of a sample of four exhibitions held at Boijmans Van Beuningen in Rotterdam between 1970 and 2013, and to determine its use for analyzing curatorial practice. Even if the pilot demonstrated the archival material’s limitations, especially for the older exhibitions, to generate knowledge about the curatorial practice, one of the outcomes of the project is the interest stated by several Dutch museums in creating a historical database of art exhibitions.


The third speaker was Matthia Sabatelli, a PhD candidate in Machine Learning at the Montefiore Institute (University of Liège). He offered some of the first results of his work in the INSIGHT project that aims at the development of Computer Vision technology for analyzing images of art works, specifically working with digital assets of two museum clusters in Brussels: Royal Museums of Fine Arts of Belgium and Royal Museums of Art and History. Matthia is involved in efforts to build a new generation of machine learning based tools that can enrich such heritage collections. One of the challenges discussed, was how to modify algorithms for recognizing natural images to work for images of art works, because the latter deviate from ‘real world’ depictions.