As can be seen in our case studies, there is a wide range of options for data collection, reflecting the diverse needs, budgets and human capacity within different projects. Digital technology is increasingly being used for monitoring projects – you can find out more about options and considerations in our digital technology section. However, technology is not necessary for many initiatives and in some instances it may be a hindrance. The Moabi monitoring project in DRC provides an interesting example of how technology, and paper and pen monitoring, are both used, harnessing their respective advantages.
Data collection forms, and advice on how to design them, can be found in our resources section. You can also download forms associated with a particular project by visiting the case studies (note: forms are available for some case studies and not others).
It is also useful to consider the way in which data is collected. For example, it may be more efficient and robust if data collection can be undertaken as part of daily activities, like hunting, rather than requiring special trips.
Data analysis and management
Data analysis can be simple, or highly complex, depending on the decision-making aims of the project. The questions of who should be responsible, and how it should be tackled, should be decided in conjunction with designing the methodology. Analysis can be undertaken by communities, by external stakeholders or facilitators (e.g. scientists), or as a collaborative effort.
We suggest exploring our case studies to understand some of the approaches that have been adopted. Our article on Sustainable Forest Management also describes some of the key benefits of ensuring that local forest users and decision-makers are involved in the analysis stage. These include greater local understanding and ownership of the results and, crucially, greater ability among local people to use the results to make informed decisions.
Insights from the Forest COMPASS project in Guyana reveal that it can be important for data to be managed in a way that allows communities to retain control of their data. This may require local capacity building. For tips, see our article on data management and infrastructure (this project used smartphones, computers and online data storage) and the documents in the Resources section. Meanwhile, the Forest COMPASS project in Brazil highlighted that rigorous data analysis can require considerable time, possibly leading to bottlenecks in quick access and response to the data by stakeholders. It is important, therefore, to build in sufficient time and resources to undertake the required analysis, or simplify the questions during the planning phase.