Conceptualizing a National Approach to Data Curation Services in Canada

Clary, Erin; Brodeur, Jason; Wilson, Lee; Moon, Jeff; Khair, Shahira

doi:10.5281/zenodo.3894935

Cited by 2 publications

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“…Library professionals, who have traditionally played a large role in supporting researchers' data management efforts, are now providing an increasing amount of support for data curation (Steeves 2017). Data curation is the active management of research data as it is created, maintained, used or reused, and archived for long-term storage (Clary et al 2020), and it ensures research data are FAIR, or Findable, Accessible, Interoperable, and Reusable (Johnston et al 2017;Wilkinson et al 2016). While repositories and data management plans help to make data findable and accessible, data sharing does not guarantee ease of use.…”

Section: Introductionmentioning

confidence: 99%

Computational Reproducibility: A Practical Framework for Data Curators

Sawchuk

Khair

2021

JeSLIB

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Introduction: This paper presents concrete and actionable steps to guide researchers, data curators, and data managers in improving their understanding and practice of computational reproducibility. Objectives: Focusing on incremental progress rather than prescriptive rules, researchers and curators can build their knowledge and skills as the need arises. This paper presents a framework of incremental curation for reproducibility to support open science objectives. Methods: A computational reproducibility framework developed for the Canadian Data Curation Forum serves as the model for this approach. This framework combines learning about reproducibility with recommended steps to improving reproducibility. Conclusion: Computational reproducibility leads to more transparent and accurate research. The authors warn that fear of a crisis and focus on perfection should not prevent curation that may be ‘good enough.’

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Section: Introductionmentioning

confidence: 99%

Computational Reproducibility: A Practical Framework for Data Curators

Sawchuk

Khair

2021

JeSLIB

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“…At the time of writing, 58 Canadian institutions participate in Scholars Portal Dataverse (Portage Network 2020a) and many academic institutions in Canada today have RDM staff. However, in this buildup of infrastructure, staff, and programming, a gap between the improved facility to house properly curated data and the local institution's knowledge and capacity to conduct data curation itself became apparent (Clary et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Creating Guidance for Canadian Dataverse Curators: Portage Network’s Dataverse Curation Guide

Cooper

Steeleworthy

Paquette-Bigras

et al. 2021

JeSLIB

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Purpose: This paper introduces the Portage Network’s Dataverse Curation Guide and the new bilingual curation framework developed to support it. Brief Description: Canadian academic institutions and national organizations have been building infrastructure, staffing, and programming to support research data management. Amidst this work, a notable gap emerged between requirements for data curation in general repositories like Dataverse and the requisite workflows and guidance materials needed by curators to meet them. In response, Portage, a national network of data experts, organized a working group to develop a Dataverse curation guide built upon the Data Curation Network’s CURATED workflow. To create a bilingual resource, the original CURATE(D) acronym was modified to CURATION—which has the same meaning in both French and English—and steps were augmented with Dataverse-specific guidance and mapped to three conceptualized levels of curation to assist curators in prioritizing curation actions. Methods: An environmental scan of relevant deposit and curation guidance materials from Canadian and international institutions identified the need for a comprehensive Dataverse Curation Guide, as most existing resources were either depositor-focused or contained only partial workflows. The resulting Guide synthesized these guidance materials into the CURATION steps and mapped actions to various theoretical levels of data repository services and levels of curation. Resources: The following documents are supplemental to the Dataverse Curation Guide: the Portage Dataverse North Metadata Best Practices Guide, the Scholars Portal Dataverse Guide, and the Data Curation Network CURATED Workflow and Data Curation Primers.

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Conceptualizing a National Approach to Data Curation Services in Canada

Cited by 2 publications

References 0 publications

Computational Reproducibility: A Practical Framework for Data Curators

Computational Reproducibility: A Practical Framework for Data Curators

Creating Guidance for Canadian Dataverse Curators: Portage Network’s Dataverse Curation Guide

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