A Linked Data API, using Python Flask which is an HTTP API framework, used to deliver representations of GA's aerial Surveys online as Linked Data. The API reads data from another HTTP API: the ARGUS XML API. The ARGUS XML API is generated by Oracle software and delivers XML representations of Survey objects stored in the ARGUS database. The online endpoints for the ARGUS XML API as accessed by this Surveys API are given in a config file within this API's code. Details about how to use this API are given within the main README file of this API's code repository (README.md).

<div>Quality assurance and quality control (QAQC) of geochemical data is an important first step before any interpretation of the data is undertaken. Due to the increasing number of elements that are being reported by laboratories undertaking multi-element analysis, the time to undertake QAQC of the data has increased. In order to alleviate the increasing time constraints of undertaking QAQC this python script was developed. This script provides a quick first pass of the data automatically to produce summary statistics and plots of the included standards laboratory duplicates and analytical duplicates. The statistics and plots allow for rapid assessment of geochemical data to discover potential issues with the data and trends though time, whilst also providing a consistent approach. It should be noted that no general quality cut-offs have been included within the script as it does not replace the need for an expert examining the data to identify potential issues.</div>

<div>Levelling of geochemical data between surveys is a vital step in using datasets together. This code can apply a number of approaches to eliminate inter-laboratory differences from multi-generational and spatially isolated geochemical surveys. This codes allow the use of a variety of levelling methods: re-analysis, single standards, and multiple standards. The methodology and effectiveness of each of these methods are outlined in Main, P.T. and Champion, D.C., 2022. Levelling of multi-generational and spatially isolated geochemical surveys. Journal of Geochemical Exploration.</div>