Oceanographic Data Repositories: An Analysis of the International Situation

As the global open science movement has recently proven its effectiveness in responding to the corona pandemic, research on disciplinary or institutional data repositories and establishing service platforms for the open and sharing research data are also active in Korea. The purpose of the research data repository is not to manage data per se but to discover and innovate knowledge and to integrate and reuse subsequent data and knowledge. Therefore, recent repository-related studies emphasize implementing the FAIR principle in this collaborative process, from observation to data documentation, data combination, quality control, and data publication. In particular, high-level data interoperability through the FAIR implementation of the repository is essential for ocean observation that requires multidisciplinary collaborative research. In Korea, ocean observatory organizations have repositories, including the ocean science data repository, JOISS; however, no studies evaluate the establishment and operation of data repositories in the FAIR principle. Therefore, this study aims to examine the construction process and data management status of the JOISS repository and the main functions and services of the web platform in terms of the data lifecycle and evaluate The FAIR principle of Open Science works in such an operating system and its limitations. The study provides implications for the improvement direction of data management and services of domestic marine repositories, including the JOISS, in an environment where the diversity and volume of data are rapidly increasing along with the evolution of ocean observation.

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Accounting for spatial scale and temporal variation in fish-habitat analyses using baited remote underwater video stations (BRUVS)

Wines

Young

Zavalas

et al. 2020

Mar. Ecol. Prog. Ser.

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With the implementation of marine spatial planning in many coastal regions of the world, there is a need to understand how marine species and communities respond to environmental heterogeneity. Predictive modelling approaches are one efficient method for associating marine communities with variations across the seascape. These approaches, along with increasing access to spatially explicit environmental data, provide improved opportunities for modelling fish assemblages. Baited remote underwater video stations (BRUVS) are a popular means of gathering fish assemblage data in the coastal zone, but have biases in bait attraction, trophic groups sampled, and behavioral conditions. To account for these biases, spatial and temporal scales of analyses must be considered. In this study, we combined time-series BRUVS observations with seafloor and oceanographic variables in generalized additive models to model patterns of relative species richness and abundance in temperate coastal fish assemblages across multiple habitat types, functional trophic groups, and spatial scales from 5-500 m. We show that the spatial and temporal scale of analyses and behavioral characteristics of target species (such as mobility) are important considerations when predicting the spatial distribution of a particular assemblage or functional subset. The resulting models performed well, with prediction accuracies up to 79% while explaining between 24 and 83% of variance. These models were then used to extrapolate assemblage characteristics over broader areas of the seafloor to expand our understanding of fish distributions, providing valuable insights for marine spatial planning, including marine protected area assessment.

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Oceanographic Data Repositories: An Analysis of the International Situation

Cited by 3 publications

References 7 publications

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Is the ocean science data repository, JOISS able to be FAIR?

Accounting for spatial scale and temporal variation in fish-habitat analyses using baited remote underwater video stations (BRUVS)

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