{"id":8401,"date":"2022-04-01T08:12:24","date_gmt":"2022-04-01T08:12:24","guid":{"rendered":"https:\/\/website.prod.unilu.spikeseed.cloud\/en\/news\/d4h-data-science-meets-digital-history\/"},"modified":"2022-04-01T08:12:24","modified_gmt":"2022-04-01T08:12:24","slug":"d4h-data-science-meets-digital-history","status":"publish","type":"news","link":"https:\/\/www.uni.lu\/en\/news\/d4h-data-science-meets-digital-history\/","title":{"rendered":"D4H: Data Science meets Digital History"},"content":{"rendered":"<section class=\"wp-block-unilux-blocks-free-section section\"><div class=\"container xl:max-w-screen-xl\"><p>The mass digitisation of historical sources and the exponential growth native digital online sources have catapulted the discipline of history from an \u201cage of scarcity\u201d to an \u201cage of abundance\u201d. Making sense of the \u201cbig data of the past\u201d requires new approaches to data management, data mining, visualisation and interpretation of data.<\/p><p>In the future, the study of massive migration flows, climatic changes, or public opinion formation on social media platforms will both necessitate a critical digital literacy by historians and humanist approach to data analytics.\u00a0<\/p><p>\u201cDeep Data Science of Digital History\u201d (D4H) is a new Doctoral Training Unit funded through the FNR\u2019s PRIDE programme, that will launch in autumn 2022. This interdisciplinary DTU focuses on multiple challenges at the intersection between the disciplines of history and data science and builds on the epistemological and methodological learnings of the interdisciplinary DTU \u201c<a href=\"https:\/\/dhh.uni.lu\/\" target=\"_blank\" title=\"\" rel=\"noopener\">Digital History and Hermeneutics<\/a>\u201d.<\/p><p>Its main aims and ambitions are:<\/p><ul class=\"ulux-list\"><li class=\"ulux-list-item\">To bridge research in humanities and sciences by creating an interdisciplinary \u201ctrading zone\u201d building on the concept of \u201cdigital hermeneutics\u201d;<\/li><li class=\"ulux-list-item\">To train a new generation of digitally literate PhD students to deal with \u201cbig data of the past\u201d in a critical and competent way, combining the epistemic tradition of close reading with machine-based methods of distant reading (\u201cscalable reading\u201d);<\/li><li class=\"ulux-list-item\">To develop a shared understanding of the human\/machine nexus in collecting, curating, managing, analysing, interpreting, and visualising historical data;<\/li><\/ul><p>D4H involves the University of <a href=\"https:\/\/wwwen.uni.lu\/c2dh\" target=\"_self\" title=\"\" rel=\"noopener\">Luxembourg&#8217;s\u00a0Centre for Contemporary and Digital History<\/a>\u00a0(C\u00b2DH), the\u00a0<a href=\"https:\/\/wwwen.uni.lu\/fstm\" target=\"_self\" title=\"\" rel=\"noopener\">Faculty of Science, Technology and Medicine<\/a>\u00a0(FSTM), the\u00a0<a href=\"https:\/\/wwwen.uni.lu\/fhse\" target=\"_self\" title=\"\" rel=\"noopener\">Faculty of Humanities, Education and Social Sciences<\/a>\u00a0(FHSE), together with the Luxembourg Institute of Science and Technology (LIST) and the Institute of Socio-Economic Research (LISER). The DTU will include a total of 18 PhD positions. It will be led by\u00a0<a href=\"https:\/\/wwwen.uni.lu\/c2dh\/people\/andreas_fickers\" target=\"_blank\" title=\"\" rel=\"noopener\">Andreas Fickers<\/a>, Director of the Luxembourg Centre for Contemporary and Digital History (C2DH).<\/p><p>The new Doctoral Training Unit proposes to deepen the interdisciplinary collaboration between digital history and computer science by exploring the concepts of deep history and deep data science. D4H will focus on three thematic and methodological pillars:<\/p><p>1) deep data and knowledge<\/p><p>2) deep analytics and learning<\/p><p>3) deep visualisation and interpretation<\/p><p>The concept of \u201cDeep data and knowledge\u201d addresses the challenges of creating digital datasets which, in the field of history, are often characterised by their heterogeneity of data and their unstable or fluid nature in terms of volume and integrity. Doctoral students will be trained in the analysis of characteristics, formats, histories, and infrastructures of historical data and train our PhD students in historical data criticism and traceable data management. Deep analytics and learning engage with state-of-the-art approaches in machine learning technologies and the use of artificial intelligence for analysing large historical datasets. Deep visualisation and interpretation enter epistemological discussions about how visualisation techniques and dynamic interfaces transform historical imagination and interpretation. Based on recent trends in explainable artificial intelligence, information visualisation, and human-computer interaction, the aim is to promote critical debates about how historical arguments can be turned into \u201cgraphic arguments\u201d, and how new techniques of representing big historical datasets can be turned into explorative modes for the temporal and spatial sampling of historical information.<\/p><p>For more information about the Doctoral Training Unit, please contact the Project Leader:\u00a0<a href=\"mailto:andreas.fickers@uni.lu\" target=\"_self\" title=\"\" rel=\"noopener\">andreas.fickers@uni.lu<\/a><\/p><\/div><\/section>","protected":false},"excerpt":{"rendered":"<p>The mass digitisation of historical sources and the exponential growth native digital online sources have catapulted the discipline of history from an \u201cage of scarcity\u201d to an \u201cage of abundance\u201d. Making sense of the \u201cbig data of the past\u201d requires new approaches to data management, data mining, visualisation and interpretation of data.<\/p>\n","protected":false},"author":0,"featured_media":8402,"template":"","format":"standard","meta":{"featured_image_focal_point":[],"show_featured_caption":false,"ulux_newsletter_groups":"","uluxPostTitle":"","uluxPrePostTitle":"","_trash_the_other_posts":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false},"news-category":[11,10],"news-topic":[24],"organisation":[154,32,228,233],"authorship":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.3 (Yoast SEO v22.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>D4H: Data Science meets Digital History - University of Luxembourg<\/title>\n<meta name=\"description\" content=\"The mass digitisation of historical sources and the exponential growth native digital online sources have catapulted the discipline of history from an \u201cage of scarcity\u201d to an \u201cage of abundance\u201d. 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