Abstract
This curated collection examines “data” through the lens of digital humanities and literary studies, exploring its multifaceted definitions and implications. Contemporary understandings of data vary widely across fields, from science to philosophy. Contributors to this collection critically evaluate the complex relationship between data and information, and how digital formats influence data interpretation, addressing key questions around data preparation, interpretation, provenance, and neutrality.
For this curated collection, we’ve selected the term “data” (the plural of datum, Latin dare ‘to give’). Although the use of the term dates back to ancient times, its contemporary usage has been in circulation since the late eighteenth and early nineteenth centuries Full reference in Zotero Library. In scientific fields, anything observed or measured is documented as data. Yet, “data” is likely as nebulous a concept as “literature”, as can be read in the curated collection ‘Critical Modelling’. The challenge in defining data lies in its broad scope, prompting us to ask: what doesn’t qualify as data? Various theories and disciplines offer differing definitions of data, leading to the quick dismissal of notions such as “data science” due to the disparate assumptions surrounding data Full reference in Zotero Library.
At times, “data” and “information” are used interchangeably. In addition to disciplines like information science and mathematics, philosophy also contemplates the essence of data. Presently, when we use this term, we often envision digital formats. However, at its core, a datum represents information in any conceivable form—information stemming from data. Thus, data require analysis, interpretation, or contextualisation before yielding information.
The RA5 ‘Building Digital Communities’ team and invited colleagues, comprising the contributors to this curated collection, engage with data from the perspective of digital humanities. Digital humanities methods, reliant on (digital) data such as research data, big data, and linked data, necessitate the use of databases, data processing tools, visualisation, filtering, and management, as well as the semantic web.
Contributors to this curated collection delve into the human element concerning digital data and literary studies. We aim to report on our quasi-daily work with data by presenting a variety of perspectives from diverse projects, showcasing both the extensive range of data and the different approaches to handling them. Instead of extensively explaining what data are, we primarily aim to show what types of data we encounter in literary studies, how we work with them, and the challenges we face in doing so.
The questions that we specifically addressed in this collection include: How should researchers prepare data for scientific inquiry? How do researchers interpret data within literary contexts? To what extent must humans consider data provenance to meet scientific rigour? What “truths” can be expressed through certain data? Are there truly neutral datasets? What mistakes do we encounter dealing with data in our research field? The collection fosters a conversation around data in literary studies, emphasising the importance of data literacy in the digital age and the need for individuals to develop the skills and knowledge necessary to evaluate and interpret data critically. Working with data always means working with “gaps” in the dataset; how do you deal with incomplete data, and which cases are particularly noteworthy?
Insights
The digital is still rather unusual in a literary archive. One reason for this may be that an author’s estate usually only reaches the archive after his death or at least when he is at an advanced age. In other words, the archive reflects our present with a time lag. But born-digital estates require fast…
When thinking about the use of data, we always have to think about workflows and data management, too. Therefore, the aim of this contribution is to show how Articulations handles bibliographic data through Zotero to manage and implement references to the platform—the advantages this has brought and the difficulties encountered in the implementation process.