The interdisciplinary nature of today’s scientific research programs demands an equivalent approach to training. This is particularly relevant in areas such as informatics education, where biomedical and technical topics tend to compete for space in crowded curricula. For many students with non-technical backgrounds, graduate programs do not include sufficient technical training (basic computer literacy, programming languages, data management and analysis, data workflow management, etc.) to give them the necessary tools for success with cutting-edge research. Additionally, curricula are often slow to change and do not always support training for skills demanded by current job markets. There is a need for supplementary training methods that help those with domain knowledge acquire technical expertise. Using a variety of practices such as topical workshops and online, self-paced training platforms, demand for technical training in R, Python, SQL, and other popular tools can be met. With a mission to serve the Feinberg School of Medicine, the Galter Health Sciences Library & Learning Center, in partnership with university core facilities and centers, is the ideal nexus for training and consultation in best practices related to data management and analysis as well as the development of infrastructure that will serve to connect researchers, their output, and their expertise with others in the research community.
To support these objectives, Galter has recently established the DataLab. We are focused on training & development, collaborative innovation, and connecting faculty, staff, and students in the Feinberg School of Medicine to data-related resources here at Northwestern. Through our free DataClinic service, we provide consultation and training for all stages of the research data life cycle. We engage the research community by hosting and sponsoring events that promote best practices related to reproducibility and openness in the sciences. In partnership with the National Center for Data to Health (CD2H), CERN, and others, we are developing a next-generation repository and data index system that will help scientists across the clinical and translational spectrum to locate tools, data, and expertise that will enhance their research process.
More information about the DataLab can be found here.
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