Key partners in all areas of pig production (farmers, veterinary surgeons, marketing organizations, animal feed manufacturers and slaughter companies) collaborated in the project and made their data available for analysis. Data included health, production, reproduction and nutritional data, mortality statistics, veterinary records, transport data, carcass quality and weather data. The interdisciplinary research team created a data store, which amalgamated this heterogeneous data. Methods for transporting, loading cleaning, processing and analysing the data were designed and implemented. Analyses focused on answering research questions that were identified by the pig production partners as being important for solving production problems. Results of the analysis were communicated regularly to the pig production partners who evaluated the results and provided inputs to improve both the understanding of the data and the results of the analyses.
Large data volumes can no longer be analysed using conventional methods. They have to be made usable by applying new methods. These methods have not had any impact on animal husbandry even though they would be of great interest for pig farming in Switzerland in particular. Swiss pig production differs from the intensive production systems in other European countries because of its complex, small-scale structure. Although all stages of production generate animal health data, it is not being used in a way that brings together all the various stages. If this information was suitably prepared and analysed, it will be possible to recognize new links, causes and risk factors in relation to diseases and/or a drop in performance, and to identify the best strategies for combating them.
The overarching goal of the project was to develop new methods aimed at gaining a better understanding of, and optimizing, the structure and complexity of the pig farming and production network in Switzerland. To achieve this goal the project aimed at:
-
demonstrating that new, useful and valuable information can be created by combining many disparate data sets from across a complete pig supply chain
-
developing trusting relationships between the researchers in the project and the data collectors in a complete Swiss pig production system so that they are comfortable enough to share their data and the results of data analyses with each other
-
processing and joining the many different data sets from a pig supply chain together in a single data store that is suitable for data analyses
-
using existing methods or developing new methods to analyse the data in order to produce new information that is useful and valued by the swine supply chain partners in the project
-
successfully conducting a research project involving researchers from different disciplines who have never worked together before
The adoption of Big Data approaches by the Swiss swine industry has been relatively slow, especially when compared to other industries and countries. It was well known that the structure of the swine and pork production system in Switzerland differs greatly from the intensive production systems in other countries. For that reason, the methods developed and applied elsewhere were of limited value for Switzerland. It required to create a new strategy for the adoption of Big Data approaches for the Swiss swine industry. This project demonstrated that it is possible to combine data from various actors in the pig supply chain. It also firmly established that this approach can generate new and useful information. The Pig Data project can be seen as a pilot experience about the application of Big Data approaches in the Swiss swine industry. Its success was key to drawing the attention of key stakeholders (such as the Federal Food Safety and Veterinary Office) to the importance of this topic and for the planning of new projects that will further explore the field. This is evidenced by the official support of a new project that aims at establishing a ‘competence & information centre for pig health in Switzerland’ which will collect, analyse and publish health data from various projects and practitioners in the field in order to obtain a real-time overview of the population’s health status and the occurrence of emerging and re-emerging diseases.
PIG DATA: Health Analytics for the Swiss Swine Industry