Earth Science Informatics

, Volume 9, Issue 1, pp 47–65 | Cite as

Knowledge-based environmental research infrastructure: moving beyond data

  • Markus StockerEmail author
  • Mauno Rönkkö
  • Mikko Kolehmainen
Research Article


Over the past decades, sensor networks have been deployed around the world to monitor over time and space a large number of properties appertaining to various environmental phenomena. A popular example is the monitoring of particulate matter and gases in ambient air undertaken, for instance, to assess air quality and inform decision makers and the public. Such infrastructure can generate large amounts of data, which must be processed to derive useful information. Infrastructure may be for environmental research, specifically. In order to reduce duplication and improve interoperability, efforts have been initiated more recently that aim at abstract architectural descriptions of infrastructure that supports the acquisition, curation, access, and processing of measurement and observation data. The ENVRI Reference Model (ENVRI-RM) is an example for an abstract architectural description of infrastructure tailored for environmental research. We briefly summarize ENVRI-RM and provide an overview of its subsystems, functionality, and viewpoints. We highlight that its primary focus is on the data life-cycle in environmental research infrastructure. As our contribution, weextend ENVRI-RM with functionality for the acquisition of knowledge from data, and the curation, access, and processing of knowledge. The extension, which we name +K, aims at addressing the knowledge life-cycle in environmental research infrastructure. We present the +K subsystems and functionality, and discuss the extension from ENVRI-RM viewpoints. We argue that the +K extension can be superimposed on ENVRI-RM to form the ENVRI-RM+K model for the ‘archetypical’ knowledge-based environmental research infrastructure that addresses both data and knowledge life-cycles. We demonstrate the application of the extension to a concrete use case in aerosol science.


Environmental research infrastructure Knowledge-based systems Knowledge acquisition Knowledge representation and reasoning Ontology Semantic web technologies 



This research is funded by the Academy of Finland project “FResCo: High-quality Measurement Infrastructure for Future Resilient Control Systems” (Grant number 264060).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Markus Stocker
    • 1
    Email author
  • Mauno Rönkkö
    • 1
  • Mikko Kolehmainen
    • 1
  1. 1.Research Group of Environmental InformaticsDepartment of Environmental Science, University of Eastern FinlandKuopioFinland

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