LinkedGeoClimate: An Interoperable Platform for Climate Data Access Within Geographical Context

Abstract

Climate data (e.g., air temperature and precipitation) are used in a variety of environmental sectors, such as determining which crops to cultivate for farmlands, and optimizing the placement of products in retail stores. Currently, access to climate data is popularly managed by sophisticated database management systems, which are efficient for data processing but have limited data exchangeability across systems. By contrast, many semantic studies focus on the use of RDF knowledge graphs (KGs) for climate data access, which is semantically interoperable such that data can be easily shared between different RDF KGs based on predefined domain ontologies. However, climate data is often consumed in a certain geographical context to understand its relationships with other environmental sectors. For example, the geographical context of farmyards is needed to determine which climate stations nearby are used. The interoperability proposed for the geographical context of climate data access is under-explored by relevant semantic studies, resulting in additional resource waste in integrating heterogeneous geospatial information for climate data access. In this article, we propose LinkedGeoClimate, which is an interoperable RDF KGs platform for climate data access within an enriched geographical context. LinkedGeoClimate provides the necessary geographical and geospatial information for climate data access and further advances interoperable climate data access when mutual spatial relationships with other environmental sectors are concerned.

Keywords

• Climate data
• GeoSPARQL
• geographical data
• knowledge graphs (KGs)
• RDF