A New Program for Art Historians in the Digital Age

NYU’s Claudio Silva & Juliana Freire, both Professors of Computer Science, Engineering and Data Science, develop ARIES (ARt Image Exploration Space) with a multidisciplinary team of researchers

An art historian’s job typically requires a detailed comparison of two or more works of art. Before the digital age, the conventional method involved examining and arranging physical prints, photographs, or slides on tables or light boxes.

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Now art historians rely almost entirely on digital images from their own databases, special collections, or the web. Yet, no integrated software program is attuned to the needs of art historians. Instead, they rely on a hodgepodge of incompatible programs for separate tasks including grouping images, saving and sharing work, making annotations, and performing detailed analysis. Spreading different tasks across incompatible programs complicates an art historian’s job and makes research unnecessarily laborious.

But a multidisciplinary team of researchers, including CDS faculty members Claudio T. Silva and Juliana Freire, have a solution. They have designed a unique program specifically for art historians called ARIES (ARt Image Exploration Space), funded partly by a seed grant from the Moore-Sloan Data Science Environment at CDS. ARIES is an intuitive web-based interface that supports exploration, manipulation, annotation, grouping, and sharing of art images within a single digital environment.

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ARIES equips art historians with a virtual toolkit that enables meaningful interactions with digital images. Its main component is a lightbox canvas that allows dynamic overlays, arrangements, juxtapositions, zoom features, filters, annotations, lenses, and selection tools. Art historians can easily save and share their work within ARIES so another expert can seamlessly continue.

Beyond the lightbox canvas, however, ARIES also helps art historians identify differences between artworks by generating a pixel heat map. The pixel heat map can be useful for tracking an artist’s progression over time, evaluating the quality of reproductions, or spotting forgeries.

ARIES also incorporates metadata associated with images (i.e. artist, date, geography, and relative size). Based on stored metadata, ARIES users can search from a database to sort images and arrange them by timeline, map them on a Geochart, or display them side-by-side according to relative size. The relative size feature is especially useful for museum curators to visually plan exhibitions.

The ARIES development team plans to improve the program by adding support for real time collaboration and additional ways to input and leverage metadata. While ARIES was crafted specifically for art historians, the program can help other academics and professionals who interact with a high volume of digital images such as designers, photographers, artists, scientists, and digital humanists.

By Paul Oliver

NYU Center for Data Science

Written by

Official account of the Center for Data Science at NYU, home of the Master’s and Ph.D. in Data Science.

Center for Data Science

This is the official research blog of the NYU Center for Data Science (CDS). Established in 2013, we are a leading data science training and research facility, offering a MS in Data Science and, as of 2017, one of the nation’s first universities to offer a Ph.D. in Data Science.

NYU Center for Data Science

Written by

Official account of the Center for Data Science at NYU, home of the Master’s and Ph.D. in Data Science.

Center for Data Science

This is the official research blog of the NYU Center for Data Science (CDS). Established in 2013, we are a leading data science training and research facility, offering a MS in Data Science and, as of 2017, one of the nation’s first universities to offer a Ph.D. in Data Science.

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