Towards improved quality of soil morphology and analytical data in Australia: starting the discussion
Andrew J. W. Biggs A C and Ross Searle B
+ Author Affiliations
- Author Affiliations
A Department of Natural Resources and Mines, PO Box 318, Toowoomba, Qld 4350, Australia.
B CSIRO Land & Water, Ecosciences Precinct, GPO Box 2583, Brisbane, Qld 4001, Australia.
C Corresponding author. Email: andrew.biggs@dnrm.qld.gov.au
Soil Research 55(4) 309-317 https://doi.org/10.1071/SR16140
Submitted: 23 May 2016 Accepted: 24 November 2016 Published: 14 December 2016
Abstract
The development and implementation of a national data schema for soil data in Australia over the last two decades, coupled with advances in information technology, has led to the realisation of more comprehensive state and national soil databases. This has facilitated increased access to soil data for many purposes, including the creation of many digital soil-mapping products, such as the Soil and Landscape Grid of Australia. Consequently, users of soil data have a growing need for clarity concerning the quality of the data; many new users have little understanding of the varying quality of the data. To date, statements about the quality of primary soil data have typically been qualitative and/or judgemental rather than explicit. The consequences of poor-quality primary data and of the lack of a coding system for data quality are growing with increased usage and with demand for soil data at the regional to national scale. Pillar 4 of the Global Soil Partnership and the National Soil Research, Development and Extension Strategy both identify the need to improve the quality of soil data. Various international standards do exist with respect to the quality of soil data but these tend to focus on general principles and quality-assurance frameworks rather than the detail of describing data quality. The aim of this paper is to stimulate a discussion in the Australian soil science community on how to quantify and describe the quality of primary soil data. We provide examples of the data quality issues and propose a framework for structured data-quality checking procedures and quality coding of soil morphological and analytical data in Australia.
Additional keywords: DSM, soil databases, soil morphology.
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