The benefits and reasons for making data discoverable are:
There are instances where data cannot be shared or may first need to be de-identified:
Sharing data on a platform like the Research Repository (formerly Figshare) also increases your citations and broadens the impact of your research, as proven by a recent article published in the Public Library of Open Science. In this below quotation DAS stands for "Data Availability Statement" - the author's statement about where the data supporting an article's findings can be accessed, with 3 being the most open and easily available. As the paper states:
"The results of citation prediction clearly associates a citation advantage, of up to 25.36%, with articles that have a category 3 DAS—those including a link to a repository via a URL or other permanent identifier, consistent with the results of previous smaller, more focused studies [...] Sharing data also gives more credibility to an article’s results, as it supports reproducibility. Finally, data sharing encourages re-use, which further contributes to citation counts."
Reference
Colavizza, G., Hrynaszkiewicz, I., Staden, I., Whitaker, K., & McGillivray, B. (2020). The citation advantage of linking publications to research data. PLoS ONE,15(4): e0230416. https://doi.org/10.1371/journal.pone.0230416
Stories that show research data impact
The #dataimpact eBook brings together 16 of the stories collected during the #dataimpact campaign.
The stories showcase the real-life impact of Australian research data.
The Research Repository is RMIT University's open access publications and data repository and uses the Figshare platform. RMIT researchers can use the Research Repository to share and promote research data and other research output types to the global community.
Most file types can be hosted, and research data records entered using the Dataset item type, are automatically minted a DOI (Digital Object Identifier) for citing and promotion.
Dataset from Dr. Andrew Martin, Dept. of Physics
DOI: http://dx.doi.org/10.25439/rmt.12253310
See the Research Repository home page for access and further information.
Contact the Research Repository team at: repository@rmit.edu.au
For information on citing or referencing data see the following guide:
Figshare's annual State of Open Data 2024, in collaboration with Digital Science and Springer Nature, has been released. You can find the full report at this link: https://www.digital-science.com/state-of-open-data-report-2024/.
This report reveals links between the numbers of peer reviewed published research and data sets being made available open access. Data sources for this report include Dimensions, Springer Nature Data Availability Statements (DAS), and the Make Data Count and DataCite Data Citation Corpus.
This report aims to understand and uncover strategies to bridge the gap between policy and practice in making research data available openly accessible.
Reproducibility is crucial in consideration of research data, and it should maintain its initial richness. If possible, data should have a clear machine-readable licence and provenance information on how the data was formed. It should also have discipline-specific data and metadata standards to give it rich contextual information that will allow for reuse.
The Australian Research Data Commons (ARDC) outlines the importance of data provenance metadata explaining that "data provenance . . . is the documentation of why and how the data was produced, where, when and by whom the data is collected" (ARDC, 2022, para 1).
It is essential to capture data provenance metadata as it provides details of how the primary data was collected, methodologies and processes used to extract data, and how the data was analysed. Having data provenance metadata ensure that when the data is published that it is credible and for those reusing the data it establishes trustworthiness in the data.
For more information on the definitions and concepts on reproducibility consider the chapter 'Understanding Reproducibility and Replicability' from the National Academies and Sciences' Reproducibility and replicability in science consensus study report.
Reproducibility and replicability in scienceARDC. 2022. Data provenance metadata: Builds trust, credibility and reproducibility https://ardc.edu.au/article/data-provenance-metadata-builds-trust-credibility-and-reproducibility/
National Academies of Sciences, Engineering, and Medicine. (2019). Reproducibility and replicability in science National Academic Press. https://doi.org/10.17226/25303