Investigating gaps for novel animal health surveillance data within Scotland -R. McManus

Sensors have become ubiquitous in our current world and the livestock farming sector offers multiple research avenues for the application of sensor technology, from early disease detection to virtual fencing. Animal health surveillance in Scotland currently relies on post-mortem examinations of animals and on data derived from laboratory submitted samples. Sensor-derived syndromic surveillance of livestock has been identified as a gap in Scotland’s current animal health surveillance capabilities. Real-time data from on-farm herds has the potential to underpin improved production and endemic disease detection and the earlier identification and investigation of potential outbreaks. Using the data journeys approach, the aim of this project is to elucidate the conceptual journey of thermal imagery and drone-derived data from farm to policy. This approach aims to situate data across interconnected sites of practice, highlighting the movement of data in and between sites and exposing areas of potential ‘data friction’. The term ‘data friction’ is used to describe the complex factors (political, ethical, legal, social and economic) that come together to slow down and restrict data generation, movement and use.