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A Lockpick's Guide to dataARC: Designing Infrastructures and Building Communities to Enable Transdisciplinary ResearchOpen Materials

Rachel Opitz, Colleen Strawhacker, Philip Buckland, Jackson Cothren, Tom Dawson, Andrew Dugmore, George Hambrecht, Willem Koster, Emily Lethbridge, Ingrid Mainland, Tom McGovern, Anthony Newton, Gisli Palsson, Tom Ryan, Richard Streeter, Elisabeth Stade, Vicki Szabo, Polly Thompson

Cite this as: Opitz, R. and Strawhacker, C. et al. 2021 A Lockpick’s Guide to dataARC: Designing Infrastructures and Building Communities to Enable Transdisciplinary Research, Internet Archaeology 56.


The North Atlantic Biocultural Organization (NABO) community initiated dataARC to develop digital research infrastructures to support their work on long-term human-ecodynamics in the North Atlantic. These infrastructures were designed to address the challenges of sharing research data, the connections between those data and high-level interpretations, and the interpretations themselves. In parallel, they were also designed to support the reuse of diverse data that underpin transdisciplinary synthesis research and to contextualise materials disseminated widely to the public more firmly in their evidence base. This article outlines the research infrastructure produced by the project and reflects on its design and development. We outline the core motivations for dataARC's work and introduce the tools, platforms and (meta)data products developed. We then undertake a critical review of the project's workflow. This review focuses on our understanding of the needs of stakeholder groups, the principles that guided the design of the infrastructure, and the extent to which these principles are successfully promoted in the current implementation. Drawing on this assessment, we consider how the infrastructure, in whole or in part, might be reused by other transdisciplinary research communities. Finally, we highlight key socio-technical gaps that may emerge as structural barriers to transdisciplinary, engaged, and open research if left unaddressed.

Corresponding author: Rachel OpitzORCID logo
University of Glasgow

Colleen StrawhackerORCID logo
National Science Foundation

Philip BucklandORCID logo
Umea University

Jackson Cothren
CAST, University of Arkansas

Tom DawsonORCID logo
University of St Andrews

Andrew DugmoreORCID logo
School of Geosciences, University of Edinburgh

George HambrechtORCID logo

Willem KosterORCID logo
University of St Andrews

Emily Lethbridge
Stofnun Árna Magnússonar Í Íslenskum Fræðum

Ingrid MainlandORCID logo
University of Highlands and Islands

Tom McGovernORCID logo
City University of New York

Anthony Newton
School of Geosciences, University of Edinburgh

Gisli PalssonORCID logo
Umea University

Tom Ryan
City University of New York

Richard StreeterORCID logo
University of St Andrews

Elisabeth Stade
Computer Science, University of Colorado Boulder

Vicki Szabo
Western Carolina University

Polly ThompsonORCID logo
School of Geosciences, University of Edinburgh

Full text

Figure 1: The dataARC infrastructure, whose main components are shown here, builds on the CIDOC CRM and leverages tools and platforms including GitHub, Jupyter notebooks, and the OpenAPI Specification.

Figure 2: Concepts are linked to the results of queries on individual datasets via well-described mappings, referred to as 'combinators' within the dataARC infrastructure. (2a) A conceptual illustration of how combinators provide data to concept links (2b).

Figure 3: An illustration of how the results returned by the dataARC search tool are organised. They are grouped into 'matched', 'related' and 'contextual' results and further organised into 'archaeological', 'environmental' and 'textual' types, and then by data source.

Figure 4: The 'Why' section of the search tool exposes the connections between concepts used in a search, data returned, and combinators, providing an explanation to an end user of how their search results were generated and why the data are considered relevant.

Figure 5: A subsection of the concept map illustrates the diverse connections between related and contextual concepts, which are used to generate search results.

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