Edited volume on ‘Data Science and History: Practicing and Theorizing Data-Driven Inquiries into the Past’
In the last decade historians have witnessed a proliferation of digitized and born-digital data sets. Examples include digitized correspondences, oral history interviews, photos, and maps. A growing number of cultural institutions such as archives, museums, and libraries, have made parts of their digital assets available in raw data formats. Some institutions launched pilot projects experimenting with data releases. Historical data sets encourage data-driven inquiries into the past, as well as the integration of data science methods into historical research. Best practice, and illustrative examples in the application of data science methods in historical research remain scarce, however. Similarly, the epistemological and theoretical underpinning of historical research applying data science methods needs to be developed. This collection of papers will offer a panorama of the current state of the art in the application of data science methods in historical research; it will be submitted to the Digital Humanities Quarterly (DHQ) as a special issue.
We specifically invite contributions that analyze data sets and integrate complex models of data science into historical inquiry. We also seek contributions that discuss the development of new data sets and research softwares. In brief, we aim to publish papers with three foci:
analysis of historical data sets with data science methods software development for the application of data science methods in history preparation of historical data sets to be studied with data science methods
Prospective authors are asked to reflect on know-how, best practice, and epistemology, as well as how newly developed data and software will contribute to existing knowledge and scholarship. Authors are also encouraged to include deeper methodological reflections and to highlight how data science methods can further our understanding of the past and open new directions for future research. More generally, we seek fresh and original perspectives that problematize both data and data-centric approaches, as well as the synergies between theory and practice.
We encourage contributions between 5000 and 8000 words, though shorter papers (3000 - 5000) will also be considered.
- 15 July 2023: Submit an abstract of your paper (max. 500 words) through the following link: https://tinyurl.com/mr24cecv
- 15 August 2023: Notification of acceptance and submission of accepted abstracts to DHQ
- 10 December 2023: Submit your complete paper (submission link TBA)
We aim to publish the special issue in the summer of 2024.
For further information, please contact Gabor Mihaly Toth: email@example.com (please use the subject header “DHQ Special Issue”).
We are looking forward to receiving your abstract and reading your contribution.
- Gabor Mihaly Toth
- Caitlin Burge
- Christoph Purschke
- Marten Düring