Reference model guided system design and implementation for interoperable environmental research infrastructures
Zhao, Z.; Martin, P.; Grosso, P.; Los, W.; de Laat, C.; Jeffrey, K.; Hardisty, A.; Vermeulen, A.; Castelli, D.; Legre, Y.; Kutsch, W. (2015). Reference model guided system design and implementation for interoperable environmental research infrastructures, in: 11th IEEE International Conference on eScience, eScience 2015: Proceedings. . https://dx.doi.org/10.1109/escience.2015.41
In: (2015). 11th IEEE International Conference on eScience, eScience 2015: Proceedings. IEEE Computer Society: USA. ISBN 978-1-4673-9325-6. xvii, 594 pp., more
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| Available in | Authors |
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Document type: Conference paper
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| Author keywords |
research infrastructure , system-level science , reference model , e-research , e-science , environmental research |
| Authors | | Top |
- Zhao, Z.
- Martin, P.
- Grosso, P.
- Los, W.
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- de Laat, C.
- Jeffrey, K.
- Hardisty, A.
- Vermeulen, A.
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- Castelli, D.
- Legre, Y.
- Kutsch, W.
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| Abstract |
Environmental research infrastructures (RIs) support their respective research communities by integrating large-scale sensor/observation networks with data curation services, analytical tools and common operational policies. These RIs are developed as pillars of intra-and interdisciplinary research, however comprehension of the complex, pathologically interconnected aspects of the Earth's ecosystem increasingly requires that researchers conduct their experiments across infrastructure boundaries. Consequently, almost all data-related activities within these infrastructures, from data capture to data usage, needs to be designed to be broadly interoperable in order to enable real interdisciplinary innovation. The Data for Science theme in the EU Horizon 2020 project ENVRI PLUS intends to address this interoperability challenge as it relates to the design, implementation and operation of environmental science RIs, the theme focuses on key issues of data identification and citation, curation, cataloguing, processing, optimization, and provenance, supported by a generic cross-infrastructure reference model. |
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