Natural sciences are facing tremendous challenges that may also represent unprecedented opportunities. Decades of worldwide effort have delivered enormous volumes of biodiversity data and started to address our great need for improved understanding of natural systems. Nevertheless, available data remain uneven and insufficient to deliver knowledge at the scales and coverage required. As we face planet-wide issues such as impacts of climate change on biodiversity patterns, human health, and food security, we need transformational approaches that maximize and expand the flow of relevant observations from all regions. Our solutions need to cross disciplinary boundaries and facilitate participation by interested stakeholders everywhere. Only data-intensive frontier scientific research can secure the insights we need to support science, sustainability and conservation.

Addressing these grand challenges will require us to develop robust and sustainable interconnected solutions that bring together the strengths of many different technologies. These include high-throughput streams of observations from diverse instruments, industrial-scale imaging of natural science collections (including 3D imaging), next generation sequencing, and machine learning approaches, among others. How can traditional scientific disciplines, such as taxonomy and biogeography, most benefit from novel sources of data and technological breakthroughs?

A global approach is also needed to equip scientists with user-friendly tools and with the data skills needed for collaborative international open science. Greater collaboration can improve both timeliness and quality of knowledge products. Greater openness, including learning from open software practices, can allow scientists to integrate programmes of both fundamental and applied research and to ensure cross-fertilisation between the efforts of academia, governments and the public. The goal should be fair, equitable and sustainable growth in knowledge both for scientific progress and for societal advances.

Events (plenary sessions, symposia, workshops, hackathons, …) in this track will provide the opportunity for the conference delegates to discuss a wide range of topics. Some examples:

1. Highlight opportunities for effective interlinkage between diverse data sources for cross-disciplinary research; share innovative ideas and/or proofs of concepts;  
2. Serve as a platform to transfer knowledge and experience between delegates on data-driven biodiversity and geoscience scientific projects and their impact on science and society;
3. Demonstrate the current and potential future impact of scientific tools (including software, workflows and protocols) for data curation, analysis and publication;
4. Share experiences around specific bottlenecks affecting the availability or quality of online data resources and online services for science; include vision for future directions;
5. Discuss the need for capacity enhancement in digital skills and competencies for everyone in the biodiversity_next data pipeline;
6. Highlight strong scientific use cases that require collaboration among biodiversity and geoscience researchers, data managers, collection managers, informaticians, infrastructure operators, industry, and policy makers;
7. Provide the opportunity for early career researchers to share their experiences and gain exposure to new developments big-data-driven research around biodiversity and geoscience.