Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution

Roche, Dominique G.; Berberi, Ilias; Dhane, Fares; lauzon, Félix; Soeharjono, Sandrine; Dakin, Roslyn; Binning, Sandra A.

doi:10.32942/osf.io/d63js

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…Although data sharing and reuse have become integral to advancing knowledge in environmental science, data stewardship and enabling such reuse are still in the early stages of socio‐technical inventions (Michener, 2015). However, it is recognized that data publishing improves the scientific enterprise (McKiernan et al, 2016) by increasing transparency and reproducibility of published results (Borghi & Van Gulick, 2021; Roche et al, 2015, 2021) and encouraging new collaborations (Boland et al, 2017; Walter et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…Environmental Data Initiative is a data repository and data management support organization providing the environmental research community with a stable platform of well-documented and, hence, reusable data. As the open data landscape is changing toward data publishing requirements to increase transparency and reproducibility of scientific results (Roche et al, 2021), EDI provides tools and support to streamline publication workflows and review processes (Fox et al, 2021). The current rapid and dramatic environmental changes in particular, increasingly prompt researchers to publish and seek historic observations for comparison and context in EDI.…”

Section: Con Clus Ionmentioning

confidence: 99%

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The Environmental Data Initiative: Connecting the past to the future through data reuse

Gries

Hanson

O'Brien

et al. 2023

Ecology and Evolution

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Domain-specific data repositories provide services that directly support certain communities of practice or disciplines. They often cater to the needs of that community by archiving and making available data that are of interest, in formats that are usable, and through interfaces that are accessible to the community. A National Science Board refers to these services as "essential, community-proxy functions" (National Science Board, 2005). In turn, the community supports and builds trust in the repository and its content and relies upon it to publish data and as a source of data repurposed to answer new scientific questions, either in its original form or combined into a synthetic product or meta-analysis. Data published in a trustworthy and accessible repository provide significant benefits to scientific progress (Hampton et al., 2013), society in general, and the careers and research of individual scientists (Eisenstein, 2022). Evaluating the connection between metadata quality and data reuse will help inform the role of data repositories in the future of ecological science.The Environmental Data Initiative (EDI) operates a domainspecific data repository designed for and with input from the

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Section: Discussionmentioning

confidence: 99%

Section: Con Clus Ionmentioning

confidence: 99%

The Environmental Data Initiative: Connecting the past to the future through data reuse

Gries

Hanson

O'Brien

et al. 2023

Ecology and Evolution

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“…The anonymized data and the analysis script to reproduce our results are available on the Open Science Framework () and were shared with the editors and reviewers upon submission. Electronic supplementary material is available online [47].…”

Section: Data Accessibilitymentioning

confidence: 99%

Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution

et al. 2022

Self Cite

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Many leading journals in ecology and evolution now mandate open data upon publication. Yet, there is very little oversight to ensure the completeness and reusability of archived datasets, and we currently have a poor understanding of the factors associated with high-quality data sharing. We assessed 362 open datasets linked to first- or senior-authored papers published by 100 principal investigators (PIs) in the fields of ecology and evolution over a period of 7 years to identify predictors of data completeness and reusability (data archiving quality). Datasets scored low on these metrics: 56.4% were complete and 45.9% were reusable. Data reusability, but not completeness, was slightly higher for more recently archived datasets and PIs with less seniority. Journal open data policy, PI gender and PI corresponding author status were unrelated to data archiving quality. However, PI identity explained a large proportion of the variance in data completeness (27.8%) and reusability (22.0%), indicating consistent inter-individual differences in data sharing practices by PIs across time and contexts. Several PIs consistently shared data of either high or low archiving quality, but most PIs were inconsistent in how well they shared. One explanation for the high intra-individual variation we observed is that PIs often conduct research through students and postdoctoral researchers, who may be responsible for the data collection, curation and archiving. Levels of data literacy vary among trainees and PIs may not regularly perform quality control over archived files. Our findings suggest that research data management training and culture within a PI's group are likely to be more important determinants of data archiving quality than other factors such as a journal's open data policy. Greater incentives and training for individual researchers at all career stages could improve data sharing practices and enhance data transparency and reusability.

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“…In addition, researchers interested in building upon existing research often find it difficult to retrieve the data associated with published articles (Goodman et al, 2014). Even when they are available, the data may not be usable in their current state, a problem which has been documented in a number of other fields, including ecology and evolution (Roche et al, 2015, 2021), psychology (Towse et al, 2020) and cognition research (Hardwicke et al, 2018). Water researchers in academia, especially those at the early stage of their career, face many competing demands and pressures.…”

Section: Introductionmentioning

confidence: 99%

Ten best practices to strengthen stewardship and sharing of water science data in Canada

Persaud

Dukacz²,

Saha

et al. 2021

Hydrological Processes

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Water science data are a valuable asset that both underpins the original research project and bolsters new research questions, particularly in view of the increasingly complex water issues facing Canada and the world. Whilst there is general support for making data more broadly accessible, and a number of water science journals and funding agencies have adopted policies that require researchers to share data in accordance with the findable, accessible, interoperable, reusable (FAIR) principles, there are still questions about effective management of data to protect their usefulness over time. Incorporating data management practices and standards at the outset of a water science research project will enable researchers to efficiently locate, analyse and use data throughout the project lifecycle, and will ensure the data maintain their value after the project has ended. Here, some common misconceptions about data management are highlighted, along with insights and practical advice to assist established and early career water science researchers as they integrate data management best practices and tools into their research. Freely available tools and training opportunities made available in Canada through Global Water Futures, The Gordon Foundation DataStream, the Digital Research Alliance of Canada Portage Network, Compute Canada, and university libraries, among others are compiled. These include webinars, training videos, and individual support for the water science community that together enable researchers to protect their data assets and meet the expectations of journals and funders. The perspectives shared here have been developed as part of the Global Water Futures programme's efforts to improve data management and promote the use of common data practices and standards in the context of water science in Canada. Ten best practices are proposed that may be broadly applicable to other disciplines in the natural sciences and can be adopted and adapted globally.

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Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution

Cited by 6 publications

References 24 publications

The Environmental Data Initiative: Connecting the past to the future through data reuse

The Environmental Data Initiative: Connecting the past to the future through data reuse

Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution

Ten best practices to strengthen stewardship and sharing of water science data in Canada

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