Challenges of open data in aquatic sciences: issues faced by data users and data providers

Jorrit P. Mesman, Carolina C. Barbosa, Abigail S.L. Lewis, Freya Olsson, Stacy Calhoun-Grosch, Hans Peter Grossart, Robert Ladwig, R. Sofia La Fuente, Karla Münzner, Lipa G.T. Nkwalale, Rachel M. Pilla, Keerthana Suresh, Danielle J. Wain

Research output: Contribution to journalArticlepeer-review

Abstract

Free use and redistribution of data (i.e., Open Data) increases the reproducibility, transparency, and pace of aquatic sciences research. However, barriers to both data users and data providers may limit the adoption of Open Data practices. Here, we describe common Open Data challenges faced by data users and data providers within the aquatic sciences community (i.e., oceanography, limnology, hydrology, and others). These challenges were synthesized from literature, authors’ experiences, and a broad survey of 174 data users and data providers across academia, government agencies, industry, and other sectors. Through this work, we identified seven main challenges: 1) metadata shortcomings, 2) variable data quality and reusability, 3) open data inaccessibility, 4) lack of standardization, 5) authorship and acknowledgement issues 6) lack of funding, and 7) unequal barriers around the globe. Our key recommendation is to improve resources to advance Open Data practices. This includes dedicated funds for capacity building, hiring and maintaining of skilled personnel, and robust digital infrastructures for preparation, storage, and long-term maintenance of Open Data. Further, to incentivize data sharing we reinforce the need for standardized best practices to handle data acknowledgement and citations for both data users and data providers. We also highlight and discuss regional disparities in resources and research practices within a global perspective.

Original languageEnglish
Article number1497105
JournalFrontiers in Environmental Science
Volume12
DOIs
StatePublished - 2024

Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. J. P. M. was funded by the European Union\u2019s Horizon 2020 research and innovation programme, grant agreement number 101017861 (SMARTLAGOON). C. C. B was supported by the NSF award OIA-2019528. S. C. G. was funded by BOEM cooperative agreement M19AAC00015. K. S and L. G. T. N were funded from European Union\u2019s Horizon 2021 research and innovation programme under the Marie Sklodowska-Curie grant agreement No.956623, MSCA-ITN-ETN-European Training Network (inventWater Project), and H.-P. G from the European Union\u2019s Horizon 2020 research and innovation program under the Marie Sk\u0142odowska-Curie grant agreement No 722518 (MANTEL project). A. S. L. L. acknowledges support for her Ph.D. from the U.S. National Science Foundation (NSF; DGE-1840995 and DEB-1753639), the Institute for Critical Technology and Applied Science (ICTAS), and the College of Science Roundtable at Virginia Tech. R. M. P. was supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Water Power Technologies Office, and Environmental Sciences Division at Oak Ridge National Laboratory (ORNL). ORNL is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725. R. S. L. F. was funded by VUB Research. This work was conceived at the 2023 virtual meeting of the Global Lake Ecological Observatory Network (GLEON).

Keywords

  • aquatic sciences
  • data collection
  • data management
  • data sharing
  • fair principles
  • open data
  • open science

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