Call for Papers: Engaging with Big and Small Historical Data

Interested scholars are invited to submit proposals for one or more chapters in the edited Volume titled ‘Engaging with Big and Small Historical Data’, as part of the Routledges ‘Engaging with…’ series. The deadline for proposals is October 15, 2023.

The material that historical research – and humanities scholarship in general – is based on traditionally carries names like ‘archival’ or ‘primary sources’. The ongoing disciplinary movement towards digitization and datafication forces us to engage with our material in new ways: it becomes data. The aim of the volume Engaging with Big and Small Historical Data, under contract with Routledge as a part of their Engaging with… series, is to provide a guide for the scholarly community of historians to reflect on the consequences of these current developments. We invite historians and other scholars with an interest in this topic to contribute to the volume.

Contributions are asked to relate to one or more of these questions concerning datafication, which provide the structure of the volume:

1)   Where are data to be found? Data is not always stored in the archives and libraries that we know how to work with. Preconditions for access to data are changing. Historians have to cope with paywalls, versioning, permissions, and formats. They have to learn about OCR, image recognition, and other techniques. Most of all, they are usually not in control of what material is or can be turned into data. This raises crucial questions about what material can be worked with as data in the first place, and what material is being left out, excluded, overseen, or forgotten.

2)   How do we engage with data? Working with data impacts the epistemological preconditions of historical scholarship, if only because its methodologies usually originate from other fields of research. Does working with data necessitate a (new) quantitative turn in historical scholarship, or can it be integrated into hermeneutic traditions? How do current developments in artificial intelligence and machine learning, which have a huge potential for historical research, impact traditional views on methodological reflection and source criticism?

3)   What can we find in data? Tools and techniques for computational analyses of data are advancing with great speed, and historians and other scholars have been using them in a large variety of ways to study history. These techniques allow for new research questions, as well as new perspectives on familiar questions.

The title of this volume aims to capture the often intertwining trends that are hidden under these questions. It refers to the various dimensions of scholarship that come with digitization and born digital data. In addition, the juxtaposition of big and small also evokes two widely discussed approaches to using data in a humanities context – which are all but mutually exclusive. A more elaborate introduction to the volume’s aims and design can be found at http://tinyurl.com/BigandSmallData.

The volume primarily aims to target the field of history. However, even if based on historical examples, the contributions to this volume are to have relevance for other fields of humanities research. After all, the historical data that is being digitized is used in a wide range of fields, from cultural studies to philosophy and from media studies to linguistics. Therefore, scholars from adjacent fields working with historical data are also warmly invited to contribute.

Proposals and deadline

Contributions are ca. 7000 words long (excl. bibliography) and, ideally, relate to a combination of concepts, key terms/methodologies and case studies. Due date for the first draft of contributors’ chapters is June 1, 2024. Revised chapters after peer review are due in the Spring of 2025. Expected publication of the volume is the Fall of 2025.

Interested scholars are asked to send proposals of max. 300 words for one or more chapters (for a list, see http://tinyurl.com/BigandSmallData) no later than October 15, 2023 to volume editor Pim Huijnen at p.huijnen@uu.nl, who you may also contact with any questions.