OB-VISLY

An Ontology-based Visual Analytics Approach to Big Data from Agricultural Monitoring Infrastructure

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OB-VISLY
  • Project duration: October 2020 - April 2023
  • Project status: ongoing
  • Funding:
    Excellence Science (Horizon 2020 /EU funding /Project)
  • Total project budget: €171,473.28
  • Website: https://www.ob-visly.com/

Project funded by

Our partners

Stichting Wageningen Research

OB-VISLY  aims to bridge the gap between the current approaches to data organization and human-computer interfaces by exploiting an ontology-based visual analytics approach to agricultural data. By integrating agricultural data, ontology (conceptual and formal data description), computational algorithms, and visualization means, OBVISLY will create a comprehensive strategy, which can enable domain experts that often lack information retrieval proficiency to acquire knowledge from high complexity datasets. Along with the increasing sensor data availability, and in particular sensor data from agricultural monitoring infrastructure, the necessity for innovations in data analysis has emerged due to rapid socio-economic and climate change, which affects the food production security and causes the need to sustain under the competitive conditions and increase the agricultural potential in Europe.

OB-VISLY contributes to European priority in establishing digital single market that oers additional tools for large and small companies, researchers, citizens, and public authorities make the most of new technologies by creating an approach that connects science and technology through visual interfaces that brings a large amount of information to the users independent from their digital skills. Furthermore, this project will establish an innovative infrastructure for a smart European agricultural and food sector by creating a visual analytics-enabled dataspace.

https://www.ob-visly.com/

Publications
An Ontology-based Visual Analytics for Apple Variety Testing
Chuprikova E, Mejia Aguilar A, Monsorno R (2021)
Presentation/Speech

Conference: EGU General Assembly 2021 | Vienna | 19.4.2021 - 30.7.2021

More information: https://meetingorganizer.copernicus.org/EGU21/session/40927# ...

https://hdl.handle.net/10863/18815

An Ontology-based Visual Analytics for Apple Variety Testing
Chuprikova E, Mejia Aguilar A, Monsorno R (2021)
Conference proceedings article

Conference: EGU General Assembly 2021 | Vienna | 19.4.2021 - 30.7.2021

http://doi.org/10.5194/egusphere-egu21-15804

https://hdl.handle.net/10863/19471

Our partners

National Research Institute for Agriculture - INRAE

Project Team
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