The UK Animal Welfare Research Network Composition by Alistair Lawrence

The AWRN already has in excess of 200 people signed up as members. Understanding how members of the network inter-relate in terms of their organisations, research interests and collaborations clearly would benefit from some form of network analysis.

Prior to the inaugural meeting we circulated a spreadsheet to collect data on AWRN members and their collaborations. Professor Tom Freeman (http://www.roslin.ed.ac.uk/tom-freeman/) helped with producing graphical representations of the network using the yEd software.

The results so far have helped in demonstrating some salient features of the network:

(a) the AWRN is mainly composed of established scientists with a bias to working on farm animals (figures 1 and 2) and with members mainly describing themselves as working in animal welfare science or animal behaviour;

Figure 1. Main research sectors AWRN members are involved with                            Figure 2. Main study species of AWRN members

                 

(b) of the over 40 organisations involved only a few have critical mass in animal welfare science;

(c) analysis suggests that there is already a loose network of collaborations connecting some AWRN members and organisations but there are many members who are not yet connected to other members of the network (figure 3);

Figure 3. Current network of collaborations within AWRN members (each node represents an individual researcher). Where a researcher has a connection back to themselves this indicates that they were missing one or more connections to others.

(d) there are some key areas of science that appear under-represented in the network including neuroscience, molecular biology and quantitative biology (figure 4).

Figure 4. Main study areas of the AWRN members

It does seem that further network analysis could help the AWRN shape itself to be better connected, to fill science gaps and to ensure that our science is having impact. The AWRN steering group will be considering how to progress further network analysis in the months to come. In the meantime, if you would like to learn more about the yEd software it is available to download using the following link: https://www.yworks.com/products/yed. If you are a member of the network and would like to view the yEd graphs which were produced by Alistair to visualise the network collaborations, please contact: Alistair.Lawrence@sruc.ac.uk or awrn-manager@bristol.ac.uk.