Open geospatial infrastructure for data management and analytics in interdisciplinary research

Abstract

The terms Internet of Things and Big Data are currently subject to much attention, though the specific impact of these terms in our practical lives are difficult to apprehend. Data-driven approaches do lead to new possibilities, and significant improvements within a broad range of domains can be achieved through a cloud-based infrastructure. In the agricultural sector, data-driven precision agriculture shows great potential in facilitating the increase in food production demanded by the increasing world population. However, the adoption rate of precision agriculture technology has been slow, and information and communications technology needed to promote the implementation of precision agriculture is limited by proprietary integrations and non-standardized data formats and connections. In this paper, an open geospatial data infrastructure is presented, based on standards defined by the Open Geospatial Consortium (OGC). The emphasis in the design was on improved interoperability, with the capability of using sensors, performing cloud processing, carrying out regional statistics, and provide seamless connectivity to machine terminals. The infrastructure was implemented through open source software, and was complemented by open data from governmental offices along with ESA satellite imagery. Four use cases are presented, covering analysis of nearly 50 000 crop fields and providing seamless interaction with an emulated machine terminal. They act to showcase both for how the infrastructure enables modularity and interoperability, and for the new possibilities which arise from this new approach to data within the agricultural domain.