Hands-On Data Publishing with Researchers: Five Experiments with Metadata in Multiple Domains

Rodrigues, Joana; Castro, João Aguiar; Silva, João Rocha da; Ribeiro, Cristina

doi:10.1007/978-3-030-11226-4_22

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…The joint development of data-specific templates for metadata creation, following a researcher-curator collaborative approach, has been very successful. This is consistent with the findings of Rodrigues et al (2019) who showed that researchers working on familiar datasets can contribute efficiently to the definition of metadata models, in particular to overcome the common problem of data descriptors lacking specificity. & The launch of the Central Storage, providing simple lowlevel data storage and exchange options, at an early stage of the project (Fig.…”

Section: Metadata Creationsupporting

confidence: 90%

“…Research data management is a complex issue involving multiple activities carried out by various actors addressing a range of drivers and influenced by a large set of factors (Pinfield et al 2014). An ongoing debate addresses the roles and responsibilities of these actors, and how they are best allocated for the diverse tasks and activities of research data management (White 2014;Latham 2017;Chunpir 2018;Rodrigues et al 2019).…”

Section: Introductionmentioning

confidence: 99%

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Managing collaborative research data for integrated, interdisciplinary environmental research

et al. 2020

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The consistent management of research data is crucial for the success of long-term and large-scale collaborative research. Research data management is the basis for efficiency, continuity, and quality of the research, as well as for maximum impact and outreach, including the long-term publication of data and their accessibility. Both funding agencies and publishers increasingly require this long term and open access to research data. Joint environmental studies typically take place in a fragmented research landscape of diverse disciplines; researchers involved typically show a variety of attitudes towards and previous experiences with common data policies, and the extensive variety of data types in interdisciplinary research poses particular challenges for collaborative data management. In this paper, we present organizational measures, data and metadata management concepts, and technical solutions to form a flexible research data management framework that allows for efficiently sharing the full range of data and metadata among all researchers of the project, and smooth publishing of selected data and data streams to publicly accessible sites. The concept is built upon data type-specific and hierarchical metadata using a common taxonomy agreed upon by all researchers of the project. The framework's concept has been developed along the needs and demands of the scientists involved, and aims to minimize their effort in data management, which we illustrate from the researchers' perspective describing their typical workflow from the generation and preparation of data and metadata to the long-term preservation of data including their metadata.

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Section: Metadata Creationsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Managing collaborative research data for integrated, interdisciplinary environmental research

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Data description is necessary for information experts to develop adequate insights into the prior research. For this reason, researchers inclined to share their data have need to make it available via easy-to-use platforms [13,14]. Understanding how data is input into such platforms is also important.…”

Section: Data Sharing and Reusing In Absence Of Methods Sharingmentioning

confidence: 99%

Evaluating QualiCO: an ontology to facilitate qualitative methods sharing to support open science

Hocker

Bipat

McDonald

et al. 2021

J Internet Serv Appl

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Qualitative science methods have largely been omitted from discussions of open science. Platforms focused on qualitative science that support open science data and method sharing are rare. Sharing and exchanging coding schemas has great potential for supporting traceability in qualitative research as well as for facilitating the reuse of coding schemas. In this study, we present and evaluate QualiCO, an ontology to describe qualitative coding schemas. Twenty qualitative researchers used QualiCO to complete two coding tasks. In our findings, we present task performance and interview data that focus participants’ attention on the ontology. Participants used QualiCO to complete the coding tasks, decreasing time on task, while improving accuracy, signifying that QualiCO enabled the reuse of qualitative coding schemas. Our discussion elaborates some issues that participants had and highlights how conceptual and prior practice frames their interpretation of how QualiCO can be used.

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“…Data description is necessary for information experts to develop adequate insights into the prior research. For this reason, researchers inclined to share their data have need to make it available via easy-touse platforms [13,14]. Understanding how data is input into such platforms is also important.…”

Section: Data Sharing and Reusing In Absence Of Methods Sharingmentioning

confidence: 99%

Evaluating QualiCO: An Ontology to Facilitate Qualitative Methods Sharing to Support Open Science

Hocker

Bipat

McDonald

et al. 2021

Preprint

View full text Add to dashboard Cite

Qualitative science methods have largely been omitted from discussions of open science. Platforms focused on qualitative science that support open science data and method sharing are rare. Sharing and exchanging coding schemas has great potential for supporting traceability in qualitative research as well as for facilitating the re-use of coding schemas. In this study, we describe and evaluate QualiCO, an ontology for qualitative coding schemas. QualiCO is designed to describe a wide range of qualitative coding schemas. Twenty qualitative researchers used QualiCO to complete two coding tasks. In our findings, we present task performance and interview data that focus participants’ attention on the ontology. Participants used QualiCO to complete the coding tasks, decreasing time on task, while improving accuracy, signifying that QualiCO enabled the reuse of qualitative coding schemas. Our discussion elaborates some issues that participants had and highlights how conceptual and prior practice frames their interpretation of how QualiCo can be used.

show abstract

Hands-On Data Publishing with Researchers: Five Experiments with Metadata in Multiple Domains

Cited by 7 publications

References 17 publications

Managing collaborative research data for integrated, interdisciplinary environmental research

Managing collaborative research data for integrated, interdisciplinary environmental research

Evaluating QualiCO: an ontology to facilitate qualitative methods sharing to support open science

Evaluating QualiCO: An Ontology to Facilitate Qualitative Methods Sharing to Support Open Science

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