{"id":6845,"date":"2024-06-10T06:27:24","date_gmt":"2024-06-10T04:27:24","guid":{"rendered":"https:\/\/www.uni.lu\/c2dh-en\/articles\/opportunities-challenges-and-next-steps-a-look-back-at-the-first-impresso-workshop-with-partners\/"},"modified":"2025-05-08T12:10:49","modified_gmt":"2025-05-08T10:10:49","slug":"opportunities-challenges-and-next-steps-a-look-back-at-the-first-impresso-workshop-with-partners","status":"publish","type":"articles","link":"https:\/\/www.uni.lu\/c2dh-en\/articles\/opportunities-challenges-and-next-steps-a-look-back-at-the-first-impresso-workshop-with-partners\/","title":{"rendered":"Opportunities, challenges and next steps: A look back at the first Impresso workshop with partners"},"content":{"rendered":"\n
\n

What exactly does the Impresso project want to achieve with its research objectives in Natural language processing, design and history? What are the technical, conceptual and methodological challenges we face? How can we facilitate secure access to data with respect to copyright restrictions? These questions stood at the core of the first on-site Impresso workshop with partners which took place on 25 and 26 April 2024 at EPFL Lausanne.<\/strong><\/p>\n\n\n\n

The workshop began with a look back at the first Impresso project<\/a> (2017-2020) by Maud Ehrmann<\/a> on major challenges, achievements and Impresso\u2019s modus operandi. The main challenges of Impresso 1 also remain in the second project: Cultural heritage data is stored in digital silos and maintained by separate institutions, there are large amounts of messy and noisy textual data encoded in various standards which requires significant transformation to effectively support visualisation and exploration to enable the conduct of historically meaningful scholarship based on data and interfaces. A short demo by Marten D\u00fcring<\/a> gave an insight into the interplay of the different interface components and illustrated the intended usage of the Impresso app whilst also serving as a sneak preview of a gentle design update reserved for an upcoming release.<\/p>\n\n\n

<\/div>\n\n\n

\nWe intend to make impresso the tool of reference for the exploration of interconnected media sources.<\/h2>\n\n\n\n

A recap of Impresso 2\u2019s main research objectives<\/a> and its overall ambition to become \u201cthe tool of reference for the exploration of interconnected media sources\u201d across languages, time, and countries followed. For the realisation of this ambitious goal, Impresso can build on recent advances in NLP, digital humanities research practices and a shift in research objectives in media history. Still, a number of challenges remain on the level of system architecture, data representation and legal access to data.<\/p>\n\n\n

\n \n\"\"\n

\n Main objectives of Impresso2 as presentend in the workshop <\/p>\n <\/figure>\n\n\n

\nEnriching and connecting historical media collections<\/h2>\n\n\n\n

Impresso\u2019s NLP team presented the ongoing work to achieve one of the project\u2019s biggest goals, to \u201cdevelop mono- and multilingual NLP and image processing components that consolidate, process, enrich, index, link and connect historical sources and external knowledge bases.\u201d This session began with a short report on efforts by University of Zurich to integrate BNL\u2019s pipeline Nautilus for the re-OCRisation of Impresso data formats and continued with a report on preliminary mixed results obtained during post-correction of ASR using LLMs. Shifting to named entities, Maud Ehrmann<\/a> and Emanuela Boros<\/a> presented past and future HIPE evaluation campaigns for the detection of named entities in historical texts as well as efforts to improve named entity processing in Impresso2 together with earlier efforts to detect press agencies in historical newspaper text.<\/p>\n\n\n\n

For NLP, dense vector representations enable the effective linking of different types of documents (newspaper articles, manuscripts, tapuscripts, speech-to-text transcripts, images, programming information, \u2026) across languages. Juri Opitz<\/a> introduced the topic and gave real-world examples to illustrate the potential inherent in different types of embeddings.<\/p>\n\n\n\n

A first case study presented by Andrianos Michail<\/a> and Simon Clematide<\/a> demonstrated how cross-lingual embeddings can already effectively link semantically related articles. Using the example of the failed project to build a nuclear plant in Kaiseraugst (CH), they were able to effectively link closely related articles in German and French-language.<\/p>\n\n\n\n

\n
\n \n
\n
\n
\n