Session VI 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.

1. EuFMD
OS22 Investigating Gaps for Novel
Animal Health Surveillance
Data Within Scotland
Rosemary McManus
University of Glasgow

2. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 2
Rosemary McManus
Gaps for Novel Animal Health Data
OBJECTIVES
Map the data journey of current animal
health surveillance in Scotland to understand
where novel data could be most useful
Engage and interview stakeholders to identify
areas of data friction using both deductive
and inductive approaches

3. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 3
Rosemary McManus
Gaps for Novel Animal Health Data
Data Friction: used to describe the complex factors (political, ethical, legal, social, economic etc.) that come
together to slow down and restrict data generation, movement and use (Bates et al., 2016).
Data Journey: a critical data studies methodology for illuminating the socio-material constitution of data objects
and flows as data move between different sites of practice (Bates et al., 2016).
Data Producer: collects, processes, and stores data from their data domain, in addition to monitoring and
ensuring the quality of their data assets (Amazon Web Services).
Data Consumer: consume the data from the data producer. Can be any user, application or system that uses
data collected by another system or stored in a data repository (Satori Cyber).
Data Governance: used on both macro (international) and micro (individual institution) levels. Importance? Aims
to ensure availability, usability, consistency, and regulatory and legal compliance: means that more data can go
further.

4. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 4
Rosemary McManus
Gaps for Novel Animal Health Data
Preliminary map illustrating
the DATA JOURNEY of
animal health surveillance
data from farm to policy in
Scotland, UK in the event of
an outbreak of FMD
Data moves through multiple
institutions and stakeholders.
Arrows show the direction of
data movement (can flow in
both directions).
References:
Foot and Mouth Disease Control Strategy
for Great Britain, 2011. DEFRA.
(https://www.gov.uk/government/publication
s/foot-and-mouth-disease-control-strategy-
for-great-britain)
Exotic Animal Disease Contingency
Framework Plan: Version 7, August 2022.
The Scottish Government.
(https://www.gov.scot/publications/exotic-
animal-disease-contingency-framework-
plan-august-2022)

5. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 5
Rosemary McManus
Gaps for Novel Animal Health Data
Map illustrating the
PROJECTED DATA
JOURNEY of animal health
surveillance data from farm to
policy in Scotland, UK in the
event of a FMD outbreak,
including NOVEL DATA.

6. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 6
Rosemary McManus
Gaps for Novel Animal Health Data
Veterinary and
Epidemiological
DATA FRICTION

7. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 7
Rosemary McManus
Gaps for Novel Animal Health Data
Data
Management
DATA FRICTION

8. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 8
Rosemary McManus
Gaps for Novel Animal Health Data
Legal and Regulatory
DATA FRICTION

9. #OS22
Digitalization and innovation applied to the prevention and control of
foot-and-mouth and similar transboundary animal diseases (FAST) OS22 9
Investigating Gaps for Novel Animal Health Surveillance Data
Within Scotland
Rosemary McManus, William Weir, Lorenzo Viora, Robert Barker, Yunhyong Kim, Pauline McBride,
Shufan Yang, Lisa A Boden
Rosemary McManus
Gaps for Novel Animal Health Data
This project is part of a collaboration between
multiple institutions investigating the use of
stationary and drone-acquired thermal imagery
to aid disease detection in livestock.
This project was supported by a University of
Glasgow Vet Fund PhD studentship.

10. Thank you !..
https://www.gla.ac.uk/schools/bohvm/
rosemary.mcmanus@glasgow.ac.uk