Abstract
In 2012 the Australian Bureau of Meteorology published a dataset, ACORN-SAT, containing the homogenised daily temperature observations of 112 locations throughout Australia for the last 100 years. The dataset employs the latest analysis techniques and takes advantage of newly digitised observational data to monitor climate variability and change in Australia. The observations in ACORN-SAT were initially published only as comma separated values, whereas the metadata was published in a PDF report. In 2013 we converted the metadata and the observation data into RDF and published the result as Linked Open Data, accessible online via a pilot government linked data service built on the Linked Data API. In this article we describe the process of transforming the original tabular data into a Linked Sensor Data Cube [in: Proc. of the 5th International Workshop on Semantic Sensor Networks, SSN12, CEUR-WS.org, 2012, pp.-1-16] based on the W3C Semantic Sensor Network ontology [Web Semantics: Science, Services and Agents on the World Wide Web 17 (2012), 25-32] and the W3C RDF Data Cube vocabulary [The RDF Data Cube Vocabulary, W3C Recommendation, 16 January 2014]. We further discuss how the dataset has since been used and interlinked with near-real time weather observations for the 112 sensing locations of the ACORN-SAT that are published by the Bureau of Meteorology. Both the original ACORN-SAT dataset and the weather observation data are accessible online at lab.environment.data.gov.au.
Original language | English |
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Pages (from-to) | 959-967 |
Number of pages | 9 |
Journal | Semantic Web |
Volume | 8 |
Issue number | 6 |
DOIs | |
Publication status | Published - 2017 |