An Ontology Model for Climatic Data Analysis

TL;DR

This paper introduces the Climate Analysis Ontology to model and convert NOAA climate data into RDF format, enabling easier web-based access, integration, and analysis through linked data and SPARQL queries.

Contribution

It presents a novel ontology model for climatic data that facilitates data conversion, integration, and web-based querying of NOAA datasets.

Findings

Enables conversion of NOAA data to RDF format.

Supports data integration and interlinking with other datasets.

Allows direct web-based querying using SPARQL.

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.