平特五不中

ABSTRACT:

The generation of rigorous reproducible scientific data requires quality training and education of graduate students and postdoctoral fellows. However, with the rapidly increasing speed of technology development individual research labs cannot stay state-of-the-art in all of these areas. Thus, rigorous training and application of the latest technologies requires the establishment, operation and sustainability of centralized scientific platforms operated by expert platform scientists for different technology areas. In addition, funders around the globe are requiring researchers to deposit their research data outputs in public repositories for sharing. Research data that is shared must follow the international FAIR data policies. That is, the data must be Findable, Accessible, Interoperable and Reusable. Although national mandates are rolling out across the globe there are little or no resources being provided for the complex processes that are required to share data. Collection and sharing of extensive metadata information about sample preparation, hardware configurations, software settings and data processing steps is essential to give value to shared data. This metadata must use a common language to be understandable by the scientific community and computing resources are needed for terabyte sized data sets and secure access for all researchers.

This seminar will focus on national and international networks in the bioimaging community and how these networks are developing and implementing quality training, developing standards and quality control processes, building community consensus, common terminologies, tools and resources to ensure rigorous and reproducible FAIR data sharing to accelerate scientific discovery. We are leading the way with the development of a Canadian cloud based national image data resource but resources and investments are needed if we want to be in the forefront.

This seminar will take place in-person and online details in attached poster below