Data is an increasingly important part of a modern lab and due to the rise of high throughput sequencing the influence of bioinformatics, data analysis, big data and data integrity has increased significantly. Qlip, the largest dairy laboratory in Europe, applies data science to the data they collect during their milk analyses. They literally go from lab data to big data. Erik Bos explains how Qlip tackles this, while Frans Boeijen from iValidate it discusses the validation of software and ensuring data integrity during his presentation.
Qlip in Zutphen stands for quality assurance in the dairy chain. In addition to audits and inspections at dairy factories and all Dutch dairy farmers, it is also the largest dairy laboratory in Europe. The company has a highly industrialized laboratory where almost 15 million samples are analyzed annually. The data from these analyzes is used (in combination with various other data sources) for various purposes to improve quality. By applying data science to these 'big data' sources, predictions are made about, among other things, milk quality, grazing and the number of shortcomings in compliance with quality standards on dairy farms. Erik Bos provides insight into how Qlip approaches this.
The way we collect data continues to develop and is accompanied by the introduction of new technologies; data is recorded on paper, in spreadsheets and in databases. The requirements we impose remain the same: have confidence in the quality and integrity of the data. Unfortunately, inspections see problems in practice: it is often not possible to demonstrate that quality and integrity are guaranteed. During validation, we need to pay attention to the data flows: where does data come from, what do we do with it and where does it go? Frans Boeijen van iValidate it During his presentation, we will discuss how we safeguard the integrity of the data. And, not unimportantly: how do you demonstrate this during inspections?
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Nederlands