Reference model guided system design and implementation for interoperable environmental research infrastructures
(2015) 11th IEEE International Conference on eScience, eScience 2015 p.551-556- 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... (More)
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 ENVRIPLUS 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.
(Less)
- author
- organization
- publishing date
- 2015-10-22
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- E-research, E-science, Environmental research, Reference model, Research infrastructure, System-level science
- host publication
- Proceedings - 11th IEEE International Conference on eScience, eScience 2015
- article number
- 7304340
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 11th IEEE International Conference on eScience, eScience 2015
- conference location
- Munich, Germany
- conference dates
- 2015-08-31 - 2015-09-04
- external identifiers
-
- wos:000380433500071
- scopus:84959051112
- ISBN
- 9781467393256
- DOI
- 10.1109/eScience.2015.41
- language
- English
- LU publication?
- yes
- id
- 6b887039-4abe-4c4a-8c80-fc445945f746
- date added to LUP
- 2016-09-23 07:51:15
- date last changed
- 2024-07-26 18:42:56
@inproceedings{6b887039-4abe-4c4a-8c80-fc445945f746, abstract = {{<p>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 ENVRIPLUS 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.</p>}}, author = {{Zhao, Zhiming and Martin, Paul and Grosso, Paola and Los, Wouter and De Laat, Cees and Jeffrey, Keith and Hardisty, Alex and Vermeulen, Alex and Castelli, Donatella and Legre, Yannick and Kutsch, Werner}}, booktitle = {{Proceedings - 11th IEEE International Conference on eScience, eScience 2015}}, isbn = {{9781467393256}}, keywords = {{E-research; E-science; Environmental research; Reference model; Research infrastructure; System-level science}}, language = {{eng}}, month = {{10}}, pages = {{551--556}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Reference model guided system design and implementation for interoperable environmental research infrastructures}}, url = {{http://dx.doi.org/10.1109/eScience.2015.41}}, doi = {{10.1109/eScience.2015.41}}, year = {{2015}}, }