Cloud-Native Data Infrastructure for Ecosystem Science and Innovation

Terrestrial Ecosystem Research Network (TERN) is an NCRIS-funded land-based observatory that measures the environment from continental to site scale with different observation methods, including remote-sensing, in-situ and human. The significant data collection demands innovative data management approaches to meet the needs of scalability, flexibility and near-real-time processing. The paper explores developing and managing cloud-native data infrastructure tailored for ecosystem science. By leveraging the ARDC NeCTAR cloud, the data infrastructure enables effective management of large volumes of data, containerised applications to submit and discover data at the collection level, multiple data dashboards to find and access data at the observation level and The Virtual desktop environment for analysis and collaboration. In addition, Apache airflow and Kubernetes are used for automated data processing and onboarding with overarching solid data governance and controlled vocabularies to describe all data-related artefacts. The cloud-native infrastructure aims to accelerate scientific data discovery, foster interdisciplinary research, and drive innovation in ecosystem management and conservation efforts.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-31
DOI
https://doi.org/10.5281/zenodo.15293635
Primary Topic
Plant Molecular Biology Research
Type
article
Field-Weighted Citation Impact
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article

Cloud-Native Data Infrastructure for Ecosystem Science and Innovation

Zenodo (CERN European Organization for Nuclear Research)
Plant Molecular Biology Research
article

Cloud-Native Data Infrastructure for Ecosystem Science and Innovation

article en

Abstract

Terrestrial Ecosystem Research Network (TERN) is an NCRIS-funded land-based observatory that measures the environment from continental to site scale with different observation methods, including remote-sensing, in-situ and human. The significant data collection demands innovative data management approaches to meet the needs of scalability, flexibility and near-real-time processing. The paper explores developing and managing cloud-native data infrastructure tailored for ecosystem science. By leveraging the ARDC NeCTAR cloud, the data infrastructure enables effective management of large volumes of data, containerised applications to submit and discover data at the collection level, multiple data dashboards to find and access data at the observation level and The Virtual desktop environment for analysis and collaboration. In addition, Apache airflow and Kubernetes are used for automated data processing and onboarding with overarching solid data governance and controlled vocabularies to describe all data-related artefacts. The cloud-native infrastructure aims to accelerate scientific data discovery, foster interdisciplinary research, and drive innovation in ecosystem management and conservation efforts.

Zenodo (CERN European Organization for Nuclear Research)
The University of Queensland (AU)
Industry, innovation and infrastructure
Openalex Percentile: Top 77%
Plant Molecular Biology Research
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