AGSO Journal Volume 14: Australian Geological Survey Articles
Updated 1mo ago
2filesPDF
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Description
AGSO Journal volume 14, number 4 contains eight peer-reviewed scientific articles published by the Australian Geological Survey Organisation. The articles likely cover topics including granite and gabbro field relationships, Proterozoic granite ages, enhanced oil recovery potential, groundwater quality, benthic marine communities, palynostratigraphy, and Cretaceous ammonites. The journal issue is hosted by the Australian Ocean Data Network and was last updated on 2026-05-05.
Use Cases
Analyze granite and gabbro field relationships in the Lamboo Complex based on the article by Blake and Hoatson.
Date tectonothermal events in northeastern Australia based on Proterozoic granite ages described by Black and Withnall.
Assess enhanced oil recovery potential in Australia based on the article by Wright et al.
Evaluate groundwater quality in the Northern Territory based on the preliminary overview by Childs and McDonald.
Study Late Miocene-Early Pliocene palynostratigraphy in the Murray Basin based on the two-part article by Macphail et al.
Strengths
Contains eight peer-reviewed scientific articles from a government geological survey.
Articles cover a diverse range of geological and earth science topics specific to Australia.
Last updated metadata indicates a recent platform update on 2026-05-05.
Limitations
Row count and column-level documentation are absent; field semantics must be inferred after download.
Description metadata is limited; actual data quality requires manual inspection after download.
Data may reflect geographic bias inherent to data_gov_au, focusing primarily on Australian regions.
Provenance
Source
Australian Geological Survey Organisation (AGSO)
Collection Method
Peer-reviewed scientific publication.
Freshness
Last updated 2026-05-05 01:43:17.519741; freshness should be verified.
Geography
Australia, Papua New Guinea
File formats are PDF and HTML, indicating the dataset is a collection of documents rather than structured tabular data.