References of "Viola, Lorella 50039079"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailFrom Digitized Sources to Digital Data, Behind the Scenes of (Critically) Enriching a Digital Heritage Collection
Viola, Lorella UL; Fiscarelli, Antonio Maria

in Weber, Andreas; Heerlien, Maarten; Gassó Miracle, Eulàlia (Eds.) et al Proceedings of the International Conference Collect and Connect: Archives and Collections in a Digital Age (2020)

Digitally available repositories are becoming not only more and more widespread but also larger and larger. Although there are both digitally-born collections and digitised material, the digital heritage ... [more ▼]

Digitally available repositories are becoming not only more and more widespread but also larger and larger. Although there are both digitally-born collections and digitised material, the digital heritage scholar is typically confronted with the latter. This immediately presents new challenges, one of the most urgent being how to find the meaningful elements that are hidden underneath such unprecedented mass of digital data. One way to respond to this challenge is to contextually enrich the digital material, for example through deep learning. Using the enrichment of the digital heritage collection ChroniclItaly 3.0 [10] as a concrete example, this article discusses the complexities of this process. Specifically, combining statistical and critical evaluation, it describes the gains and losses resulting from the decisions made by the researcher at each step and it shows how in the passage from digitised sources to enriched material, most is gained (e.g., preservation, wider and enhanced access, more material) but some is also lost (e.g., original layout and composition, loss of information due to pre-processing steps). The article concludes that it is only through a critical approach that the digital heritage scholar can successfully meet the interpretive challenges presented by the digital and the digital heritage sector fulfil the second most important purpose of digitisation, that is to enhance access. [less ▲]

Detailed reference viewed: 18 (0 UL)
Full Text
Peer Reviewed
See detailMachine Learning to Geographically Enrich Understudied Sources: A Conceptual Approach
Viola, Lorella UL; Verheul, Jaap

in Rocha, Ana; Steels, Luc; van den Herik, Jaap (Eds.) Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ARTIDIGH (2020)

This paper discusses the added value of applying machine learning (ML) to contextually enrich digital collections. In this study, we employed ML as a method to geographically enrich historical datasets ... [more ▼]

This paper discusses the added value of applying machine learning (ML) to contextually enrich digital collections. In this study, we employed ML as a method to geographically enrich historical datasets. Specifically, we used a sequence tagging tool (Riedl and Padó 2018) which implements TensorFlow to perform NER on a corpus of historical immigrant newspapers. Afterwards, the entities were extracted and geocoded. The aim was to prepare large quantities of unstructured data for a conceptual historical analysis of geographical references. The intention was to develop a method that would assist researchers working in spatial humanities, a recently emerged interdisciplinary field focused on geographic and conceptual space. Here we describe the ML methodology and the geocoding phase of the project, focussing on the advantages and challenges of this approach, particularly for humanities scholars. We also argue that, by choosing to use largely neglected sources such as immigrant newspapers (a lso known as ethnic newspapers), this study contributes to the debate about diversity representation and archival biases in digital practices. [less ▲]

Detailed reference viewed: 139 (7 UL)