The core team of the Supporting Evidence-Based Interventions project met with a range of global livestock research for development stakeholders in Rome on 25-26 January 2017. The meeting served to launch the SEBI project but also to think through the options for establishing a Community of Practice for the global livestock data community.
Some highlights of the meeting:
Name: The CoP will be called Livestock Data for Decisions (LD4D).
Domain: Participants agreed that LD4D will provide a forum for pooling and sharing of livestock data expertise. It will co-ordinate the various agendas of different stakeholders in this space including donors. The scope will be relatively broad but the CoP will concentrate on improving access to and use of livestock productivity data in low and middle income countries to support better decision making in the first instance. To begin with the focus will be on smallholder farmers and pastoralists with the possibility of extending reach to more commercial farmers as the CoP evolves.
Membership: Members of the CoP are likely to include a range of “data suppliers” and “data users”. The CoP will allow these different member types to interact effectively to ensure that data supply meets the demands of those who use it. Further thought is needed to work out how participation could be achieved in different geographies and at different scales. This might involve some pilot activities in particular target countries as a first step. A key element of CoP participation will be the development of horizontal links across different target geographies to allow broad lessons to be learned about how best to use livestock data for effective livestock sector development.
Practice: The CoP will provide a forum for the global livestock data community to come together to share best practice and harmonize approaches. This initiative will allow disparate data sources to be brought together and used more effectively. Bringing the livestock data community together will allow agreement around common indicators which will inform data collection going forward and will allow more effective cross-regional learning. Finally, the CoP will provide a useful interface between country-level practitioners and the livestock modelling community to improve the design of models to deal with real-world problems as faced by national decision makers. As a first step to build this relationship it would be useful to conduct a systematic assessment of the data demands of livestock decision makers in pilot geographies.
Charter: The overall objective for the CoP was broadly agreed as “Livestock practitioners are empowered to improve the quality and relevance of decision making by and through access to and utilization of fit for purpose livestock data and analytics”. In addition the five initial pillars of the CoP were defined as:
- Brokering supply and demand
- Sharing best practice
- Facilitating and sharing use of datasets, tools, analytical outputs and methods
- Access to expertise
- Training, capacity building and mentoring
Roadmap: Activities were agreed according to different time-scales. In the short term (0-6 months) immediate priorities are to conduct a data demand analysis, analyze success factors from existing CoPs, develop branding and a website with associated communication forum, and identify a preliminary country to focus early efforts on. Also in the short term a further convening to consolidate the CoP is needed in the next 4-5 months. In the medium term (6-18 months), priorities will be improving the data sharing platform and engaging a wider group of stakeholders in the CoP. In the longer term (>18 months), the CoP will need to consolidate understanding of end user needs and evolve accordingly.
Conclusion: The Rome meeting provided the space for extremely fruitful discussions around the proposed Livestock Data Community of Practice. Participants left the meeting with a much richer understanding of what the CoP would involve and how it could facilitate a transformation in the quality of decision making in the livestock sector in low and middle-income countries.