Giving Datasets Context: a Comparison Study of Institutional Repositories that Apply Varying Degrees of Curation

Koshoffer, Amy; Neeser, Amy; Newman, Linda; Johnston, Lisa

doi:10.2218/ijdc.v13i1.632

Cited by 7 publications

(6 citation statements)

References 1 publication

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“…To learn about the impact of review and curation services, we conduct an analysis of previously collected data [26], that captures the presence of the following characteristics [27] in the Harvard Dataverse datasets:…”

Section: Encourage Use Of Curation Features and Pre-submission Dataset Reviewmentioning

confidence: 99%

Repository Approaches to Improving the Quality of Shared Data and Code

Trisovic

Mika

Boyd

et al. 2021

Data

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Sharing data and code for reuse have become increasingly important in scientific work over the past decade. However, in practice, shared data and code may be unusable, or published results obtained from them may be irreproducible. Data repository features and services contribute significantly to the quality, longevity, and reusability of datasets. This paper presents a combination of original and secondary data analysis studies focusing on computational reproducibility, data curation, and gamified design elements that can be employed to indicate and improve the quality of shared data and code. The findings of these studies are sorted into three approaches that can be valuable to data repositories, archives, and other research dissemination platforms.

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Section: Encourage Use Of Curation Features and Pre-submission Dataset Reviewmentioning

confidence: 99%

Repository Approaches to Improving the Quality of Shared Data and Code

Trisovic

Mika

Boyd

et al. 2021

Data

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“…Otherwise, nuances that may help future users, including themselves, understand the data may be lost. When submitting data to repositories, researchers are less likely to provide suitable documentation unless they are required to [ 20 , 23 ]. While academic journal standards still vary, some require reproducibility verification, where researchers must provide their materials (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Understanding the value of curation: A survey of researcher perspectives of data curation services from six US institutions

Marsolek,

Wright,

Luong

et al. 2023

PLoS ONE

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Data curation encompasses a range of actions undertaken to ensure that research data are fit for purpose and available for discovery and reuse, and can help to improve the likelihood that data is more FAIR (Findable, Accessible, Interoperable, and Reusable). The Data Curation Network (DCN) has taken a collaborative approach to data curation, sharing curation expertise across a network of partner institutions and data repositories, and enabling those member institutions to provide expert curation for a wide variety of data types and discipline-specific datasets. This study sought to assess the satisfaction of researchers who had received data curation services, and to learn more about what curation actions were most valued by researchers. By surveying researchers who had deposited data into one of six academic generalist data repositories between 2019–2021, this study set out to collect feedback on the value of curation from the researchers themselves. A total of 568 researchers were surveyed; 42% (238) responded. Respondents were positive in their evaluation of the importance and value of curation, indicating that the participants not only value curation services, but are largely satisfied with the services provided. An overwhelming majority 97% of researchers agreed that data curation adds value to the data sharing process, 96% agreed it was worth the effort, and 90% felt more confident sharing their data due to the curation process. We share these results to provide insights into researchers’ perceptions and experience of data curation, and to contribute evidence of the positive impact of curation on repository depositors. From the perspective of researchers we surveyed, curation is worth the effort, increases their comfort with data sharing, and makes data more findable, accessible, interoperable, and reusable.

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“…Some adopt a self-deposit model, where most responsibilities for quality assurance lie with the data depositor (Austin et al 2016), whereas others take on a more active role. The level of data curation performed at repositories and, as a result, the quality of metadata varies (Koshoffer et al 2018).…”

Section: Data Quality Assurance and Repositoriesmentioning

confidence: 99%

Data Quality Assurance at Research Data Repositories

Kindling

Strecker

2022

Data Science Journal

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This paper presents findings from a survey on the status quo of data quality assurance practices at research data repositories.The personalised online survey was conducted among repositories indexed in re3data in 2021. It covered the scope of the repository, types of data quality assessment, quality criteria, responsibilities, details of the review process, and data quality information and yielded 332 complete responses.The results demonstrate that most repositories perform data quality assurance measures, and overall, research data repositories significantly contribute to data quality. Quality assurance at research data repositories is multifaceted and nonlinear, and although there are some common patterns, individual approaches to ensuring data quality are diverse. The survey showed that data quality assurance sets high expectations for repositories and requires a lot of resources. Several challenges were discovered: for example, the adequate recognition of the contribution of data reviewers and repositories, the path dependence of data review on review processes for text publications, and the lack of data quality information. The study could not confirm that the certification status of a repository is a clear indicator of whether a repository conducts in-depth quality assurance.

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Giving Datasets Context: a Comparison Study of Institutional Repositories that Apply Varying Degrees of Curation

Cited by 7 publications

References 1 publication

Repository Approaches to Improving the Quality of Shared Data and Code

Repository Approaches to Improving the Quality of Shared Data and Code

Understanding the value of curation: A survey of researcher perspectives of data curation services from six US institutions

Data Quality Assurance at Research Data Repositories

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