An algorithm to process, clean and aggregate the data from IVOG® electronic feeding stations
This combination of two RMarkdown reports describes a process of processing, cleaning and aggregating the data of IVOG® electronic feeding stations (Hokofarm group, the Netherlands). Along the way, the algorithms create visualisations and quantifications of the data, the choices made and their effects. In addition, different datasets are created and exported for future use. As all the code is provided and RMarkdown files can be easily reproduced, these algorithms can be used to clean your data, aggregate it to different levels, and gain more insight into your data's patterns and quality. In some cases and with some adaptations, the algorithm could also be applied to other types of feeding stations and sensors, for more information on this we refer to the README file. The algorithm covers eight main parts, split across two reports: 1) Pre-processing to put the data in the right format; 2) Assessing data completeness and visualisation of its pre-cleaning quality; 3) Cleaning of the data using pre-set rules; 4) Visualisation and summary of the cleaning results; 5) Aggregation of the data to different time and subject levels; 6) Calculation of a meal criterion using a three-part probability density function; 7) Application of the meal criterion to aggregate the data further to the meal level; and 8) Visualisation of the meal-level data. More information on different parts of the algorithm and on preparatory steps to take before the algorithm can run can be found shortly in the first chunk of each RMarkdown file ('setup') and more elaborately in the README file. A description of all used variables can also be found in the README file. For the most effective use of the algorithm, we advice to start by reading the README file.
Wageningen Institute of Animal Sciences, Wageningen University and Research
Next Level Animal Sciences