Published February 6, 2023 | Version v1
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Computational Approaches to Digitised Historical Newspapers (Dagstuhl Seminar 22292)

  • 1. EPFL
  • 2. C2DH
  • 3. SBB (Staatsbibliothek zu Berlin - Preußischer Kulturbesitz)
  • 4. La Rochelle University

Description

Historical newspapers are mirrors of past societies, keeping track of the small and great history and reflecting the political, moral, and economic environments in which they were produced. Highly valued as primary sources by historians and humanities scholars, newspaper archives have been massively digitised in libraries, resulting in large collections of machine-readable documents and, over the past half-decade, in numerous academic research initiatives on their automatic processing. The Dagstuhl Seminar 22292 "Computational Approaches to Digitised Historical Newspaper" gathered researchers and practitioners with backgrounds in natural language processing, computer vision, digital history and digital library involved in computational approaches to historical newspapers with the objectives to share experiences, analyse successes and shortcomings, deepen our understanding of the interplay between computational aspects and digital scholarship, and discuss future challenges. This report documents the program and the outcomes of the seminar.

BibTeX - Entry

@Article{ehrmann_et_al:DagRep.12.7.112,
  author =	{Ehrmann, Maud and D\"{u}ring, Marten and Neudecker, Clemens and Doucet, Antoine},
  title =	{{Computational Approaches to Digitised Historical Newspapers (Dagstuhl Seminar 22292)}},
  pages =	{112--179},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{12},
  number =	{7},
  editor =	{Ehrmann, Maud and D\"{u}ring, Marten and Neudecker, Clemens and Doucet, Antoine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/17614},
  URN =		{urn:nbn:de:0030-drops-176141},
  doi =		{10.4230/DagRep.12.7.112},
  annote =	{Keywords: historical document processing, document structure and layout analysis, natural language processing, information extraction, natural language processing, digital history, digital scholarship}
}

 

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Additional details

Funding

Media Monitoring of the Past CRSII5_173719
Swiss National Science Foundation