Brown, D J

McCrabb, E J

Bradley, P E

Rose, I J

Banks, Robert

Guy, S Z Y

2023-02-09

<p>Data quality influences the accuracy of estimated breeding values, and hence the accuracy of selection and genetic progress. This paper describes how a data quality score (DQS) was created to characterise the overall data quality for Australian sheep flocks. The data quality metrics investigated captured data quantity (e.g. degree of performance/pedigree recording), accuracy, structure (e.g. sire representation and linkage) and timeliness of data submission. These metrics were combined to calculate the overall DQS, with weightings dependant on breed type, variation and relationships between metrics. The DQS was well received by industry, with overwhelming support to publish the DQS after an initial producer education campaign. The DQS will help identify and highlight breeders who collect high quality data, help breeders improve their data quality, and increase information available to ram buyers. This research supports Australia's sheep industry to value phenotypes in an objective manner.</p>

Proceedings of the 12th World Congress on Genetics Applied to Livestock Production, p. 3062-3065

9789086869404

https://hdl.handle.net/1959.11/57555

Wageningen Academic Publishers

Attribution 4.0 International

The Data Quality Score: objective assessment of data quality for Australian sheep breeders

Conference Publication

Publication