English

An Ontology Model for Climatic Data Analysis

Databases 2021-06-08 v1

Abstract

Recently ontologies have been exploited in a wide range of research areas for data modeling and data management. They greatly assists in defining the semantic model of the underlying data combined with domain knowledge. In this paper, we propose the Climate Analysis (CA) Ontology to model climate datasets used by remote sensing analysts. We use the data published by National Oceanic and Atmospheric Administration (NOAA) to further explore how ontology modeling can be used to facilitate the field of climatic data processing. The idea of this work is to convert relational climate data to the Resource Description Framework (RDF) data model, so that it can be stored in a graph database and easily accessed through the Web as Linked Data. Typically, this provides climate researchers, who are interested in datasets such as NOAA, with the potential of enriching and interlinking with other databases. As a result, our approach facilitates data integration and analysis of diverse climatic data sources and allows researchers to interrogate these sources directly on the Web using the standard SPARQL query language.

Keywords

Cite

@article{arxiv.2106.03085,
  title  = {An Ontology Model for Climatic Data Analysis},
  author = {Jiantao Wu and Fabrizio Orlandi and Declan O'Sullivan and Soumyabrata Dev},
  journal= {arXiv preprint arXiv:2106.03085},
  year   = {2021}
}

Comments

Published in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2021

R2 v1 2026-06-24T02:52:49.191Z