The Hitchhiker’s Guide to Data in the History of Science

Abstract

Every project in digital and computational history of science starts with the collection of data. Depending on the research project, the subject of study, and other factors, data can comprise a variety of different types, including full texts, images, audio, video, and bibliographic metadata. Publications and project reports generally describe their results and the methods and algorithms employed, but few discuss the challenges of the initial data collection process or how it fits into the overall research data life cycle. This essay discusses a concrete research data life cycle and takes a look at the difficulties it involves. It also explores the strategies and challenges of data collection and the question of the comparability of datasets. Don't panic.-Douglas Adams, The Hitchhiker's Guide to the Galaxy E very project in the history of science relies on data. Collecting data by visiting archives, deciphering manuscripts, or describing artifacts was always essential in the daily work of the historian; digital methods are changing the amount of data that can be processed, and, more important, complex algorithms can be applied to analyze these data. In order for these methods to be applied, data has to be made available digitally. The focus of this essay is on how to work with data in this sense, although we are fully aware that digitizing sources is still one of the main challenges in the life cycle we will describe. 1 For a detailed discussion of this topic see, for example, Stéphane Nicolas, Thierry Paquet, and Laurent Heutte's essay "Digitizing Cultural Heritage Julia Damerow is a scientific software engineer at Arizona State University with a degree in computer science and a Ph.D. in computational history and philosophy of science. Her interests are the application of computation to the field of history and philosophy of science, software development in the field of digital humanities, and how these can be combined with digital humanities education. She is Head of Development and Cofounder of the Digital Innovation Group at

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“…In other words, the division of scientific data (data) and contextual data (meta-data) of a different nature (cultural, social, political, economic) can be flexibly set by the analysts once all different kinds of data are structured in a formal (interlinked) way. A proposal for standardized data taking based on the Linked-data framework has, e.g., recently been proposed in the emerging field of computational history of science (Damerow and Wintergrün, 2019;Wintergrün, 2019). In addition, internationally standardized tools for meta-data description of bibliographical and cultural itemssuch as the CIDOC Conceptual Reference Model (Doerr, 2003)are increasingly shifting toward the adoption of the Linked-Data canon (Schilling, 2012).…”

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“…Particularly because, to work with such corpora the historian needs to be able to manipulate digitised "originals" in order to use them in a more consistent manner. Damerow and Wintergrün have put forward that historians always need full control of a corpus as even within "a digital framework, historical research relies on trust in its sources" (Damerow and Wintergrün 2019). This trust in sources is a precarious balancing act for the historian.…”