RESUMEN
Advances in sequencing technologies and declining costs are increasing the accessibility of large-scale biodiversity genomic datasets. To maximize the impact of these data, a careful, considered approach to data management is essential. However, challenges associated with the management of such datasets remain, exacerbated by uncertainty among the research community as to what constitutes best practices. As an interdisciplinary team with diverse data management experience, we recognize the growing need for guidance on comprehensive data management practices that minimize the risks of data loss, maximize efficiency for stand-alone projects, enhance opportunities for data reuse, facilitate Indigenous data sovereignty and uphold the FAIR and CARE Guiding Principles. Here, we describe four fictional personas reflecting differing user experiences with data management to identify data management challenges across the biodiversity genomics research ecosystem. We then use these personas to demonstrate realistic considerations, compromises and actions for biodiversity genomic data management. We also launch the Biodiversity Genomics Data Management Hub (https://genomicsaotearoa.github.io/data-management-resources/), containing tips, tricks and resources to support biodiversity genomics researchers, especially those new to data management, in their journey towards best practice. The Hub also provides an opportunity for those biodiversity researchers whose expertise lies beyond genomics and are keen to advance their data management journey. We aim to support the biodiversity genomics community in embedding data management throughout the research lifecycle to maximize research impact and outcomes.
RESUMEN
We studied journal articles published by researchers at all eight New Zealand universities in 2017 to determine how many were freely accessible on the web. We wrote software code to harvest data from multiple sources, code that we now share to enable others to reproduce our work on their own sample set. In May 2019, we ran our code to determine which of the 2017 articles were open at that time and by what method; where those articles would have incurred an Article Processing Charge (APC) we calculated the cost if those charges had been paid. Where articles were not freely available we determined whether the policies of publishers in each case would have allowed deposit in a non-commercial repository (Green open access). We also examined citation rates for different types of access. We found that, of our 2017 sample set, about two out of every five articles were freely accessible without payment or subscription (41%). Where research was explicitly said to be funded by New Zealand's major research funding agencies, the proportion was slightly higher at 45%. Where open articles would have incurred an APC we estimated an average cost per article of USD1,682 (for publications where all articles require an APC, that is, Gold open access) and USD2,558 (where APC payment is optional, Hybrid open access) at a total estimated cost of USD1.45m. Of the paid options, Gold is by far more common for New Zealand researchers (82% Gold, 18% Hybrid). In terms of citations, our analysis aligned with previous studies that suggest a correlation between publications being freely accessible and, on balance, slightly higher rates of citation. This is not seen across all types of open access, however, with Diamond OA achieving the lowest rates. Where articles were not freely accessible we found that a very large majority of them (88% or 3089 publications) could have been legally deposited in an institutional repository. Similarly, only in a very small number of cases had a version deposited in the repository of a New Zealand university made the difference between the publication being freely accessible or not (125 publications). Given that most New Zealand researchers support research being open, there is clearly a large gap between belief and practice in New Zealand's research ecosystem.