Semantic Deep Mapping in the Amsterdam Time Machine: Viewing Late 19th- and Early 20th-Century Theatre and Cinema Culture Through the Lens of Language Use and Socio-Economic Status
| Autor: | Noordegraaf, Julia, van Erp, Marieke, Zijdeman, Richard, Raat, Mark, van Oort, Thunnis, Zandhuis, Ivo, Vermaut, Thomas, Mol, Hans, van der Sijs, Nicoline, Doreleijers, Kristel, Baptist, Vincent, Vrielink, Charlotte, Assendelft, Brenda, Rasterhoff, Claartje, Kisjes, Ivan, Niebling, F., Münster, S., Messemer, H. |
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| Přispěvatelé: | RS: FASoS AMC, Literature & Art, Department of History, Rapid Social and Cultural Transformation: Online & Offline |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Research and Education in Urban History in the Age of Digital Libraries: UHDL 2019, 191-212 STARTPAGE=191;ENDPAGE=212;TITLE=Research and Education in Urban History in the Age of Digital Libraries Research and Education in Urban History in the Age of Digital Libraries, 191-212 Niebling, F.; Münster, S.; Messemer, H. (ed.), Research and Education in Urban History in the Age of Digital Libraries. UHDL 2019, 191-212. Cham : Springer STARTPAGE=191;ENDPAGE=212;TITLE=Niebling, F.; Münster, S.; Messemer, H. (ed.), Research and Education in Urban History in the Age of Digital Libraries. UHDL 2019 Research and Education in Urban History in the Age of Digital Libraries-2nd International Workshop, UHDL 2019, Revised Selected Papers, 1501, 191-212 Communications in Computer and Information Science ISBN: 9783030931858 |
| Popis: | In this paper, we present our work on semantic deep mapping at scale by combining information from various sources and disciplines to study historical Amsterdam. We model our data according to semantic web standards and ground them in space and time such that we can investigate what happened at a particular time and place from a linguistics, socio-economic and urban historical perspective. In a small use case we test the spatio-temporal infrastructure for research on entertainment culture in Amsterdam around the turn of the 20th century. We explain the bottlenecks we encountered for integrating information from different disciplines and sources and how we resolved or worked around them. Finally, we present a set of recommendations and best practices for adapting semantic deep mapping to other settings. |
| Databáze: | OpenAIRE |
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