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Tom Elliott

I see there's a nice shout-out for the community in Farina, Andrea, Paola Marongiu, Mathilde Bru, and Daniele Borkowski. “When Data Meets the Past: Data Collection, Sharing, and Reuse in Ancient World Studies.” Open Information Science 9, no. 1 (January 1, 2025). doi.org/10.1515/opis-2025-0014.

"Academic working groups such as that of Pleiades for ancient geographical data (NYU’s Institute for the Study of the AW ...) are vital for advancing shared standards in data set creation and interoperability. Participating in collaborative efforts – such as contributing to repositories or establishing discipline-specific metadata standards – can empower scholars to make their data sets more widely usable and integrated with larger research projects. As these collaborations grow, they create a feedback loop, where best practices evolve and become embedded within the discipline, ultimately broadening the impact of data-driven approaches in AW studies."

De Gruyter Brill · When Data Meets the Past: Data Collection, Sharing, and Reuse in Ancient World StudiesThis article explores the challenges and opportunities of adopting data-driven approaches in Ancient World (AW) studies, focusing on the complexities of data collection, curation, and analysis in the field. We address issues such as defining data for AW studies, as well as data fragmentation, standardization, and interoperability. We propose solutions to enhance data accessibility, collaboration, and reuse, demonstrating that adopting standardized formats and adhering to FAIR principles can improve data sharing and enable large-scale, interdisciplinary research. Importantly, we highlight how qualitative and quantitative approaches can coexist, enriching the field. We also review different past and ongoing initiatives supporting data-driven methodologies in AW studies and advocate for their continued expansion. Lastly, we discuss the rise of data papers as a transformative tool for bridging traditional scholarship and digital methodologies, emphasizing the importance of data sets and their potential for reuse in advancing the field.
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Jun 02, 2025, 19:57 · · Web · 1 · 1
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