Rich digital data underlie modern research work at every step, and how these data are handled, structured and shared has a major impact on the pace of scientific progress. New technologies that generate massive datasets, interconnect lab devices, and enable automated experiments, challenge traditional methods for disseminating scholarly knowledge. The FAIR and open data science movements present complementary visions for more transparent, reproducible and digitally-savvy future for our research. These movements recognize that for complex research data to be shared and used effectively, we need powerful infrastructures, as well as community-supported reporting standards and well-designed exchange formats for data and metadata. At the same time, success requires not only an investment in infrastructure and formats, but also a change in the culture of data generation and sharing among researchers. 

This symposium will address the many ways that data transparency contributes to the research progress. Attendees will learn from leaders in the FAIR and open data movements who are advocating for better practices in their fields and demonstrating their commitment in their own work.

Talks will present tools that can help researchers better handle and share data, and methods to combat common statistical abuses that undermine reliability and reproducibility. Key topics on the reproducible sharing of methods and code will also be covered, since both are essential for data to be made usable and transparent. 

A series of talks will also be presented by influential publishers, funders and others who are developing policies that incentivize and support data management and sharing. In addition, we will look at the essential services and infrastructure needed to support modern data-driven science, from repositories to high-performance computing, and the necessary role of international cooperation in maintaining these resources.

The symposium will cover a wide range of research fields, including biomedical research, physics and social science, and will also explore how open data practices are transforming sectors outside academia, like health care and journalism.