This dataset was created within the framework of the
Digital Roofs project (2020–2025), a research initiative of the German
Archaeological Institute (DAI). The project focuses on the development
and evaluation of methods and technologies for the high-quality digital
documentation and publication of large quantities of archaeological roof
tile finds.
Ancient roof tiles, particularly from Greek and Roman contexts,
represent a challenging category of material due to their size, weight,
and the large number of fragments typically recovered during excavations
and surveys. Despite their research potential, especially unornamented
tiles are often insufficiently documented and rarely published in a form
suitable for comparative analysis.
Within the project, standardized workflows were developed that
integrate database structures, documentation methodologies, and digital
recording techniques. These workflows aim to ensure consistent,
efficient, and high-quality documentation, facilitating reuse,
comparability, and publication.
The data were recorded using a customized configuration of iDAI.field
developed within the Digital Roofs project. The development of this
configuration formed a central part of the project’s methodological
work, with Annalize Rheeder playing a key role in its design and
implementation. This configuration, which reflects the project’s
approach to structuring and documenting roof tile assemblages, is
provided as part of the dataset for reuse in other projects.
The configuration was created prior to the introduction of the
dedicated “Find collection” category in iDAI.field; consequently, some
structural elements represent earlier strategies for handling large
groups of finds. Parts of the configuration can nevertheless be reused
and imported into newer iDAI.field projects.
The dataset further includes accompanying documentation in the form
of methodological guidelines and manuals, provided in English and
German, each in both high- and low-resolution PDF versions. These
materials document the workflows and technologies applied and support
the reuse and adaptation of the dataset.
00106, Upload: 19.08.2019
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