The overall aim is to investigate the potential of linked data for integrating datasets related to classical antiquity, in particular addressing the particular challenges raised by our material – its incompleteness, uncertainty and fuzziness. We will achieve this by developing mechanisms for breaking data out of silos and exposing it as linked data, using standard ontologies, and in particular the Europeana Data Model, as the semantic “glue” for linking data into a wider network of knowledge. The ultimate objective will be to create a common corpus or “RDF warehouse” of linked Classics data that can be explored, searched and enhanced by further annotations.

SPQR: supporting productive queries for research

Overview

Classics researchers have produced a variety of separate digital outputs that nevertheless overlap in terms of content and would be much more useful if they could be explored as an integrated whole. Earlier work by the team, in the LaQuAT Project, concluded that such access requires a deep understanding of the data’s implicit semantics at a fine-grained level, which is complicated by the variety of representations used and the uncertain and interpretative nature of the data. Linked data approaches have great potential for addressing these issues, providing a flexible means of formalising and exploring the connections between resources, which are the key to integration.

Aims and Objectives

The overall aim is to investigate the potential of linked data for integrating datasets related to classical antiquity, in particular addressing the particular challenges raised by our material – its incompleteness, uncertainty and fuzziness. We will achieve this by developing mechanisms for breaking data out of silos and exposing it as linked data, using standard ontologies, and in particular the Europeana Data Model, as the semantic “glue” for linking data into a wider network of knowledge. The ultimate objective will be to create a common corpus or “RDF warehouse” of linked Classics data that can be explored, searched and enhanced by further annotations.

Project Methodology

Our approach has three broad, overlapping phases:

  1. A researcher-focused baseline review, which includes identifying available datasets, identifying existing ontologies and vocabularies, and describing the research activities and processes that use the datasets.
  2. An implementation phase, comprising several iterations of linked data tool evaluation, development and testing. Successive iterations will incorporate increased functionality, additional datasets, and/or a more developed ontology.
  3. An evaluation phase, during which the (near-)final version of the prototype is evaluated formally with researchers.

Anticipated Outputs and Outcomes

Specific deliverables include:

  • A corpus of linked data related to the Classics and ancient documents.
  • A baseline review of current research processes and community needs in this domain.
  • A comparative review of linked data tools.
  • Online tutorials proving practical guidance on adopting our approach.
  • A case study addressing project outcomes

More generally,

·       The datasets are "hand-crafted", with implicit semantics that are difficult to deal with – such characteristics are encountered in other disciplines, to which our results may be transferable.

Using the Europeana Data Model will provide interoperability with, and facilitate future publication into, Europeana.

Technologies and Standards

RDF, RDFa, OWL, SKOS, EDM

Project Staff

Project Director

Mark Hedges, King’s College London, Centre for e-Research, mark.hedges@kcl.ac.uk

Project Manager

Tobias Blanke, King's College London, Centre for e-Research, tobias.blanke@kcl.ac.uk

Project Team, at King's College

Stuart Dunn (stuart.dunn@kcl.ac.uk) and Gabriel Bodard (gabriel.bodard@kcl.ac.uk): domain expertise in Classics and Archaeology

Anna Ashton (anna.ashton@kcl.ac.uk): dissemination and administration

Project Team, at EPCC, University of Edinburgh:

Mike Jackson (michaelj@epcc.ed.ac.uk): manager of activities at EPCC

Bartosz Dobrzelecki (bartosz@epcc.ed.ac.uk): analysis and development of demonstrator

Project Team, at Humboldt University Berlin:

Stefan Gradmann (stefan.gradmann@ibi.hu-berlin.de)

Steffen Hennicke (steffen.hennicke@ibi.hu-berlin.de)

Marlies Olensky (marlies.olensky@ibi.hu-berlin.de)


 

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Summary
Start date
1 August 2010
End date
31 July 2011
Funding programme
Managing Research Data (JISCMRD)
Strand
Citing, linking, integrating and publishing research data (CLIP)
Project website
Lead institutions

King’s College London http://www.kcl.ac.uk/

Partner institutions
University of Edinburgh (EPCC) http://www.epcc.ed.ac.uk/
Humboldt University Berlin http://www.hu-berlin.de/
Committees
  • JISC Support of Research committee