The Data4Nature cluster brings together expertise at the interface of ecology, data science, synthesis statistics and data governance to develop new methods and provide local to global leadership in the growing field of ecoinformatics. We will leverage the power of new technologies to detect change in species and ecosystems, and seek to integrate existing streams of ecological data into a province-wide observation network that respects Indigenous data sovereignty. Such large amounts of integrated data will enable us to work with multi-sectoral partners to co-develop models of ecological change for societal good.
The Data4Nature cluster brings together expertise at the interface of ecology, data science, synthesis statistics and data governance to develop new methods and provide local to global leadership in the growing field of ecoinformatics. We will leverage the power of new technologies to detect change in species and ecosystems, and seek to integrate existing streams of ecological data into a province-wide observation network that respects Indigenous data sovereignty. Such large amounts of integrated data will enable us to work with multi-sectoral partners to co-develop models of ecological change for societal good.
The Data4Nature team covers three faculties, seven departments and two institutes, and our study systems are as diverse as forests, oceans, tundra, tropics, cities and farms. However, what unites us is a common vision for how data-intensive approaches can accelerate our ability to understand and manage the environment.
Objectives
- Promote and develop Data4Nature’s excellence in ecoinformatics, by: (i) accelerating the development and sharing of advanced computational methods within the team; (ii) showcasing Data4Nature research and applications; and (iii) sparking new collaborations between team members.
- Create and fund a BC BON (Biodiversity Observation Network) by: (i) developing and communicating a compelling vision; (ii) engaging partners; and (iii) obtaining funding.
- Catalyze regional, national and international partnerships by: (i) developing joint projects with multi-sectoral partners; (ii) obtaining funding for such projects.
- Promote justice, equity, reconciliation and inclusion in environmental data science by (i) developing an Indigenous Data Sovereignty strategy; and (ii) increasing the participation of under-represented groups.
