LinkClimate: An interoperable knowledge graph platform for climate data. (December 2022)

• Record Type: Journal Article
• Authors: Wu, Jiantao; Orlandi, Fabrizio; O'Sullivan, Declan; Dev, Soumyabrata
• Is Part Of: Computers & geosciences. Volume 169(2022)
• Publication Date: 2022-12
• Subjects: Knowledge graph -- Climate data -- Ontology -- Linked data -- SPARQL -- Climate change; Environmental policy -- Periodicals; 550.5
• DOI: 10.1016/j.cageo.2022.105215
• Languages: English
• ISSNs: 0098-3004

Abstract

Abstract: Climate science has become more ambitious in recent years as global awareness about the environment has grown. To better understand climate, historical climate( e.g. archived meteorological variables such as temperature, wind, water, etc.) and climate-related data ( e.g. geographical features and human activities) are widely used by today's climate research to derive models for an explainable climate change and its effects. However, such data sources are often dispersed across a multitude of disconnected data silos on the Web. Moreover, there is a lack of advanced climate data platforms to enable multi-source heterogeneous climate data analysis, therefore, researchers must face a stern challenge in collecting and analyzing multi-source data. In this paper, we address this problem by proposing a climate knowledge graph for the integration of multiple climate data and other data sources into one service, leveraging Web technologies ( e.g. HTTP) for multi-source climate data analysis. The proposed knowledge graph is primarily composed of data from the National Oceanic and Atmospheric Administration's daily climate summaries, OpenStreetMap, and Wikidata, and it supports joint data queries on these widely used databases. This paper shows, with a use case in Ireland and the United Kingdom, how climate researchers could benefit from this platform as it allows them to easily integrate datasets from different domains and geographical locations. Highlights: Interoperable knowledge graphs advances integrating and updating multi-source data. OpenStreetMap data enhance the geographical features of the knowledge graph data. Exploring the knowledge graph structures visually is necessary for non-experts.