Thematic Approaches to the Study of Science Drift 27, Rm. 032 Contributed Papers
25 Jul 2019 01:30 PM - 03:30 PM(Europe/Amsterdam)
20190725T1330 20190725T1530 Europe/Amsterdam Digital Humanities and the History of Science Drift 27, Rm. 032 History of Science Society 2019 meeting@hssonline.org
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The Modeling of Alchemical Decknamen: On the Potential of Digital Representation for Deepening Understanding in the HumanitiesView Abstract
Contributed PaperTools for Historians of Science 01:30 PM - 02:00 PM (Europe/Amsterdam) 2019/07/25 11:30:00 UTC - 2019/07/25 12:00:00 UTC
Alchemical language is an example of scientia poetica, its Decknamen are coded, ornate and instable. But alchemical language shouldn’t remain ultimate riddle it has come to represent. Couldn’t a computer bring clarity into the poetics of alchemy? After all, poetry is a system and systems can be modeled. Alchemical language is full of ambiguity but modern Digital Humanities tools allow to model exactly this uncertainty. Computational methods like Natural Language Processing (NLP), Named Entity Recognition (NER) and knowledge representation technologies, for example using thesauri of the terms of alchemy in SKOS-standard-conformant XML, allow to handle the typical ambiguity of alchemical data. We can make implicit instances of knowledge explicit in a digital thesaurus while the linking between the concrete word (a string or label) in a text to the thesaurus remains loose enough to allow for imprecise poetic language. Modeling is the iterative process of systematic representation of certain aspects of reality. In order to model, we need make knowledge explicit. Once a model is created for the purpose of study, the failings of the model teach us new insights: Computational models are “temporary states in a process of coming to know”, in which computers are not “knowledge jukeboxes” but “representation machines” (McCarty 2004, 255). They create an systematic approximation of reality and from its shortcomings we learn about the reality we aimed to model. This paper aims to show uses of modeling alchemical terms in a digital thesaurus using the example of Michael Maier’s (1568-1622) writings.
Presenters Sarah Lang
Centre For Information Modelling (ZIM) Of Karl-Franzens-Universität Graz
Text Mining and the Conceptual History of the "Republic of Letters"View Abstract
Contributed PaperAspects of Scientific Practice/Organization 02:00 PM - 02:30 PM (Europe/Amsterdam) 2019/07/25 12:00:00 UTC - 2019/07/25 12:30:00 UTC
All that we know about the early modern Republic of Letters, from the heterogeneity of its membership to its continued significance in the learned world of the sixteenth, seventeenth, and eighteenth centuries, is based on traditional historical research: the close-reading of historical documents. Yet, as the number of primary sources shared online keeps growing, it is time to discover how computational approaches can advance our understanding of this complex community. In my paper, part of my research for the SKILLNET project, I will explore the use of digital text mining in the study of the conceptual history of the ‘Republic of Letters’, investigating if and how the distant reading of a large corpus of letters can trace key concepts that relate to a sense of commonality and to the ideal of sharing knowledge. Looking at the frequency and spread of words, I am mapping the main ethical notions which held this learned community together. Did these notions change over time or differ according to, for example, region, language, or religion? Can they tell us if this knowledge society represented a utopian idea, detached from religious and political concerns, or if we should explain its long-term significance in relation to its pragmatic value, allowing scholars to share their thoughts and texts with each other? Exploring these questions, my paper will touch upon the construction of my principal dataset, comprising of more than 80,000 early modern letters, and discuss the complexities of conducting experiments with a historical and multilingual corpus.
Presenters
KH
Karen Hollewand
Utrecht University
Text-Mining Early Modern Collective Lives of Scholars for Scholarly VirtuesView Abstract
Contributed PaperAspects of Scientific Practice/Organization 02:30 PM - 03:00 PM (Europe/Amsterdam) 2019/07/25 12:30:00 UTC - 2019/07/25 13:00:00 UTC
The respublica litteraria, the imagined community of scholars in the early modern period, was kept together beyond confessional borders through collective ideals. These ideals were celebrated and embodied by exemplary scholars – most notably Erasmus – who served as role models for virtue and participation in the learned community. By presenting an overview of the virtues ascribed to exceptional and exemplary learned men we gain insight into the development of the transconfessional respublica litteraria in the sixteenth and seventeenth centuries. Early modern collective scholarly life-writing often referred to as "vitae" or "elogia" offered an overview to early modern readers of the most eminent scholars, their deeds and virtues. This paper will present the results of a text-mining analysis of a variety of collective scholarly life-writings. Vitae and elogia from both sides of the confessional divide will be taken into consideration and compared against each other. Do Italian or Dutch compendia of scholars include the same scholars? And, more importantly, were scholars ascribed the same virtues throughout Europe? All in all, this paper addresses the scholarly virtues expressed in collective scholarly life-writing in the early modern period.
Presenters
KS
Koen Scholten
PhD Candidate, Utrecht University
Centre for Information Modelling (ZIM) of Karl-Franzens-Universität Graz
Utrecht University
PhD candidate, Utrecht University
Johns Hopkins University
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