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Data management and reproducible workflows

This research theme focuses on the development and implementation of robust data management practices and reproducible computational workflows in archaeology. Emphasizing the importance of clean, well-documented pipelines, I advocate for the adoption of FAIR (Findable, Accessible, Interoperable, Reusable) principles to ensure that archaeological data and analyses are transparent, reproducible, and easily shareable within the research community.

I develop and promote best practices for data organization, version control, and workflow automation using tools such as Git, Jupyter Notebooks, and workflow management systems. By creating modular and reusable code, I aim to facilitate collaboration and enable other researchers to build upon existing work with ease.

I also focus on the documentation of computational methods and data processing steps, ensuring that analyses can be understood and replicated by others. This includes the use of literate programming techniques, comprehensive metadata standards, and clear reporting of results.

Overall, this research theme seeks to advance the field of computational archaeology by fostering a culture of reproducibility and open science, ultimately contributing to more reliable and impactful research outcomes.