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Thursday, October 17 • 2:00pm - 2:30pm
2 x 15 minute talks - Skills in Scholarly Communication

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This half-hour session will include the following two short talks:

Training biomedical researchers to effectively collaborate with data scientists
(Alisa Surkis)
It is not realistic to expect that all biomedical and health sciences researchers will acquire the skills needed to apply data science techniques to their work. However, these researchers are all going to have to function in a research environment where the use of data science techniques is increasingly important. Collaborations between data scientists and researchers with domain expertise afford new opportunities. However, a lack of researcher awareness about data science can result in missed opportunities for collaboration, and differences in perspective and language can result in failed collaborations. Seeing no existing curricula that met the specific need identified, we developed a class to bridge that gap - Data Science for Non-Data Scientists. The class explains the possibilities, techniques, and terminology of data science, as well as conveying its limitations such as issues of interpretation, implementation and bias. This presentation will describe the motivation for developing the class, outline the approach taken and the elements of the class, describe the different settings in which it has been taught within our institution, and detail the outcomes of the class.

A Reproducibility Workshop Series for Biomedical Researchers
(Ariel Deardorff)
The library, graduate division and Open Science Group of the University of California, San Francisco (UCSF), are collaborating with other experts on "open" to create a for-credit workshop series. The series is targeted at UCSF graduate students and researchers. It is in response to the need for hands-on reproducibility training for biomedical researchers, and aims to translate recommendations for best practice into actionable steps and training. In addition to covering open data, open code, open protocols, and open access, this workshop series will include sessions on designing rigorous experiments, engaging with new forms of peer review and building a reproducible lab. The eight-part series is scheduled for Fall 2019 and has been designed to meet the rigor and reproducibility requirements of the National Institutes of Health (https://www.nih.gov/research-training/rigor-reproducibility). The goal of this project is for subject experts to provide hands-on training that will improve research workflows, stimulate conversations about open science and research reproducibility, and build an open curriculum that can be replicated by other institutions. This talk will describe this innovative workshop series and report on pre-workshop assessments of researchers' knowledge and behaviors regarding reproducibility.

avatar for Alisa Surkis

Alisa Surkis

avatar for Ariel Deardorff

Ariel Deardorff

Director of Data Science and Open Scholarship, UC San Francisco

Thursday October 17, 2019 2:00pm - 2:30pm BST
Thistle Room