Crash Course: Data Management for Postdocs

Start your postdoctoral work at McMaster off on the right track with Research Data Management Services! Postdoctoral research work ranges from an individual project within a team to collaborating with a faculty mentor. We’ll speak to the breadth of postdoc scholarship in this introductory workshop. You’ll learn about research data management best practices and how investing a small amount of time in organizing your data now can save you a lot of time and prevent future headaches. We will go over best practices for data planning, storage, organization, preservation, and sharing. We’ll also discuss how postdocs can be advocates for research data management and guide best practices for reproducible research within their lab or group.

Workshop Preparation

None

Facilitator Bio

Danica Evering (they/them) is a Research Data Management Specialist grounded in curiosity and a deep commitment to ethics. Danica is available to help students, postdocs, faculty, and staff with RDM through the data lifecycle—Data Management Plans, storage and backup, data security, data sharing. With an MA in Media Studies, Danica fosters active interest in RDM across disciplines, with a knack for engaging researchers who might not even realize they have data to manage. Outside of work they sing in a choir, play PC games, maintain an art writing practice, grow a garden, contribute Wikipedia articles, and run.

Isaac Pratt (he/him) is a research scientist by training and has a PhD in Anatomy & Cell Biology. He leverages nearly a decade of interdisciplinary research experience to help support students, staff, and faculty. His expertise lies in questions surrounding data storage, security, planning, archival, and sharing. Isaac also provides support and curation services for McMaster Dataverse. His other interests include reproducible research methods, open science, and data science.

Workshop Slides

Coming soon.

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