Ontology-based Visual Analytics for Agriculture

The EU-funded OB-VISLY project exploits advances in data integration using ontology, data analytics and visulization and analytics providings insight into apple variety testing data.

Objectives

OB-VISLY aims to build a human-centered approach to Big Data acquired from agricultural monitoring (in particular apple orchards and vineyards) by developing ontology-based visual analytics. OB-VISLY will be designed as an interactive visual analytics system enabled to answer “what” and “why” about fruit-growing activities. Thus, the system will go beyond the traditional ways of organizing data by creating a dataspace to explore and get insight. The main objectives are:

  • To establish a regionally important dataspace enabled to (a) synthesize information about fruit-growing apple orchards and vineyards and (b) derive insight from massive, dynamic, and often conflicting data by providing up-to-date, consistent, and credible assessments from agricultural monitoring data.

  • To create (a) a single visual analytics user interface that can (b) turn the data into knowledge for users of different information retrieval proficiency.