Developing, maintaining and working with databases for multi-source, multi-level and multi-type data.
A series of workshops to discuss and build interdisciplinary relationships for a project on antimicrobial resistance.
Antimicrobial resistance – a critical global public health issue
Antimicrobial resistance (AMR) is a critical public health issue worldwide, with profound implications for human and animal health.
The UK government is interested in reducing antimicrobial (AM) in livestock and has developed a 5-year plan including goals to integrate AM use and AMR surveillance data from humans, animals and the environment and improve analysis of this data.
Currently there is no real understanding of and no system to effectively monitor how AMs are being used in livestock across the UK so the project involved developing a database that will integrate AM use and AMR data from multiple sources from dairy farms across the UK into a single, flexible resource.
Database development
The team are developing a database that will integrate AM use and AMR data from multiple sources from dairy farms across the UK into a single, flexible resource.
The plan was to gather data on use of AMs on farms from farmers, veterinarians and retailers, but because the data is from multiple sources and in different formats, it requires complex cleaning and validations.
In order to build such a database, using data that is multi-faceted, large-scale and from many sources is a challenging process. The team realized that this problem is not unique and that researchers dealing with genetics and health data as well as environmental, travel and commuting data also face similar challenges in manging their data. The workshops and meetings were aimed at bringing people together from across disciplines to share ideas and establish solutions to building an effective database.
AMR Community transformation
The resource will transform the AMR community, enabling access to a wealth of data that will be used to inform policy and commercial practice for research and industry.
People involved in this project
- Dr Harriet Mills (Senior Research Associate in Medical Statistics)
- Dr Kristen Reyher (Senior Lecturer in Farm Animal Science)
- Jonathan Massey (PhD student)