The general data workflow outlines how bioarchaeological data is managed from its generation through various usage and up to structured archival. The diagram below visualizes the core progression, showing data infrastructure, in this case based on SharePoint worksheets and ARHUT data management system and emphasizing feedback loops in data management:
Sampling is based on research design and must follow consistent documentation practices. Each sample is given a unique identifier, with metadata covering excavation context, coordinates, object type, collection date, sampler, analysis method etc. Documentation begins in field or lab notebooks and is later transcribed into SharePoint worksheets.
Instrument outputs—such as LC-MS, GC-MS, NGS, or microscopy data—are collected in vendor-specific raw formats (e.g., RAW, FASTQ). This raw data is then referenced and linked in SharePoint worksheets that record initial metadata, sampling context, and lab-specific identifiers. These worksheets are used for early-stage review and validation.
Raw entries are transformed into structured research datasets by cleaning, standardising terminology, and checking for consistency. This step includes:
These structured datasets form the basis for computational analysis and are maintained within SharePoint for collaborative editing. Access permissions are set to control changes and ensure data provenance.
Once structured, datasets can be processed using computational tools tailored to specific research questions and data types. This includes statistical modelling, pattern recognition, and visualisation. Analyses are typically performed in environments like R, Python, or specialised software, such as OxCal, IsoReader, or MaxQuant.
Analytical outputs must be reproducible and versioned, with all scripts and parameter settings documented and stored alongside the dataset, either in SharePoint or linked repositories (e.g., GitHub).
Structured datasets are subjected to both planned and unplanned quality checks. Users can verify data completeness, coherence, and consistency with raw entries during a formal review process, but often various problems are noticed while working with data. In some cases, those require contextual knowledge, and it is thus not possible to catch all of those during any formal review. Feedback is communicated via SharePoint comments, tracked changes, or ARHUT comments/tasks. Datasets may cycle through multiple revisions before finalisation. This feedback mechanism is essential for maintaining data quality and for correcting inconsistencies before deposition.
Finalised datasets are transferred to the ARHUT data platform, where they are archived with:
These datasets become part of the long-term record and are linked to both internal systems (e.g., SharePoint, Archemy, Department of Archaeology) and external repositories (e.g., Dryad, BIAD ,etc).
Each phase of the workflow is supported by designated platforms:
Finalised and curated datasets archived in ARHUT are made available through their dissemination. ARHUT's web interface (https://arh.ut.ee/) allows for structured querying and access to project-specific datasets, enriched with contextual metadata and persistent identifiers. Paleomix Open Archaeological Database (O.A.D.) builds on the ARHUT infrastructure, offering public-facing access to selected datasets from Paleomix and related projects. This system enables transparent sharing of research outputs, supports interdisciplinary collaboration, and fosters broader reuse by both academic and public audiences.
Reiter, Samantha S., Staniuk, Robert, Kolář, Jan, Bulatović, Jelena, Rose, Helene Agerskov, Ryabogina, Natalia E., Speciale, Claudia, Schjerven, Nicoline, Paulsson, Bettina Schulz, Lee, Victor Yan Kin, Canteri, Elisabetta, Revill, Alice, Dahlberg, Fredrik, Sabatini, Serena, Frei, Karin M., Racimo, Fernando, Ivanova-Bieg, Maria, Traylor, Wolfgang, Kate, Emily J., Derenne, Eve, Frank, Lea, Woodbridge, Jessie, Fyfe, Ralph, Shennan, Stephen, Kristiansen, Kristian, Thomas, Mark G. and Timpson, Adrian. "The BIAD Standards: Recommendations for Archaeological Data Publication and Insights From the Big Interdisciplinary Archaeological Database" Open Archaeology, vol. 10, no. 1, 2024, pp. 20240015. https://doi.org/10.1515/opar-2024-0015