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Reference model guided system design and implementation for interoperable environmental research infrastructures

Zhao, Zhiming; Martin, Paul; Grosso, Paola; Los, Wouter; De Laat, Cees; Jeffrey, Keith; Hardisty, Alex; Vermeulen, Alex LU ; Castelli, Donatella and Legre, Yannick, et al. (2015) 11th IEEE International Conference on eScience, eScience 2015 In Proceedings - 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.

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organization
publishing date
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
in
Proceedings - 11th IEEE International Conference on eScience, eScience 2015
pages
6 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
11th IEEE International Conference on eScience, eScience 2015
external identifiers
  • Scopus:84959051112
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
2016-10-04 15:19:01
@misc{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},
  keyword      = {E-research,E-science,Environmental research,Reference model,Research infrastructure,System-level science},
  language     = {eng},
  month        = {10},
  pages        = {551--556},
  publisher    = {ARRAY(0x8451b90)},
  series       = {Proceedings - 11th IEEE International Conference on eScience, eScience 2015},
  title        = {Reference model guided system design and implementation for interoperable environmental research infrastructures},
  url          = {http://dx.doi.org/10.1109/eScience.2015.41},
  year         = {2015},
}