Research Data Management in the Field

Gathering, curating and storing research data during field work is not a trivial task. In fact, it can quickly get messy. Archaeologists often have to deal with less-than ideal working conditions and heterogeneous research methods and diverse documentation requirements. On top of that, projects often involve specialists from different disciplines, such as the natural sciences, who bring their own requirements and practices to the table.

This often leads to data silos that have to be subsequently integrated. At the same time, the demands on research data management and data quality have continuously risen in recent years. Institutions that fund research expect professional data management. Compliance with the FAIR principles is a mandatory requirement. This increases time and effort required by researchers and, in some cases, demands new technical skills that are not reflected in today's educational curricula.

Against this backdrop, many research projects have developed their own workflows and best practices to enable high-quality documentation with minimised effort. Initiatives such as the National Research Data Infrastructure for Objects (NFDI4O) in Germany are trying to bring the community together to transfer these project-specific specifications into commonly accepted standards and best practices.

In our session we aim to discuss these workflows and best practices developed in projects to improve our understanding of practical research data management in the context of field research. We invite contributions that deal with the entire documentation process or specific aspects. These include, but are not limited to:

– Workflows & Tools: from data collection in the field to FAIR data
– Best Practices: data formats and standards you use
– AI / Machine learning for data processing and/or quality management
– Working with silos: transformation and publication of data
– Reuse Open Data: from BigData to ML/AI Application
– Projekt specific excavation manuels and data models