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Uncovering Latent Metadata in the FSA-OWI Photographic Archive CC BY-NC-ND

Large digitized archives allow for the quantitative analysis of artefacts in a similar fashion as the distant reading methods popularized in literary analysis. Digital research in the humanities is so strongly tied to this paradigm it may appear that computational methods are singularly useful when analyzing a collection as an aggregation of its constituent parts. In constrast to this view, we argue that computational and statistical methods also have the potential to serve a significant role in traditional humanities research; digitial methods are often able to expose useful latent metadata about individual records, assisting in the close reading of even a small set of archival records. We demonstrate this point by showing specific examples where latent information can be learnt by digital methods through a case study of the FSA-OWI Photographic Archive, a collection of over 170,000 photographs taken by the US Government between 1935 and 1945. A wealth of additional contextual information surrounding each photograph, from the perspective of both the photographers as well as the government archivists, is brought to the fore through a variety of digital methods.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.