2C Supporting researchers in the use and reuse of archaeological data: following the ARIADNE thread

Julian Richards, Franco Niccolucci, Kate Fernie, Holly Wright

Ever-increasing amounts of data are available within data repositories in individual institutions, national infrastructures and international services.  The EC Infrastructures funded ARIADNE project is working to bring together archaeological research data from across Europe, for use and reuse in new research. There are challenges, such as raising awareness about the available data, integrating datasets produced by very different projects using differing methodologies and various technologies.  There are GIS, databases, 3D data, scientific datasets and more, all produced in a variety of languages.  ARIADNE is building vital infrastructure to bring together, manage and provide access to these datasets.  The project is embracing Linked Open Data, Natural Language Processing, deploying Web Services and new tools to provide enhanced access to researchers. ARIADNE is also offering training and opportunities for archaeologists to access the research infrastructure, and to share knowledge and expertise.

The aim of this session is to stimulate discussion between researchers and data specialists, and to:

  • Showcase best practices and relevant work supporting access and use of digital archaeology from ARIADNE and other services
  • Present case studies demonstrating innovative reuse of archaeological datasets
  • Develop an understanding of the challenges in providing access to research data and the opportunities offered by ARIADNE and other services
  • Discuss how these challenges can be addressed and how the opportunities can be maximized
  • Generate ideas for future training, access and research

Session themes

The focus is on access, discovery and research reuse of archaeological datasets, and contributions are invited on the following (and related) topics:

  • 3D and Visualization
  • Remote Sensing and Spatial Data
  • Excavation and Monument Data
  • Scientific Datasets
  • Grey Literature
  • Linked Data
  • Design of Archaeological Datasets
  • Conversion of Legacy Datasets

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