Effective data management can increase the pace of the research process, contribute to the soundness of research results, and meet funding agency requirements by making research data easy to share. Join us for an overview of best practices including backup procedures, tips on effective file names, data security and access controls, and data documentation/metadata. This seminar is for faculty, postdoctoral researchers and graduate students from all disciplines. This course does not focus on creating or using any particular data collection or analysis tool (e.g. REDCap, SPSS), but discusses data management at a general level. <Register here><Handouts>
Please join us for a workshop, hosted by the Center for Open Science and JHU Data Management Services, to learn easy, practical steps researchers can take to increase the reproducibility of their work.
The workshop will be hands-on. (Please bring a laptop if possible.) Using an example study, attendees will actively participate in creating a reproducible project from start to finish.
Topics covered include:
- Project documentation
- Version control
- Pre-analysis plans
- Open source tools: in this specific instance, the Open Science Framework to easily implement these concepts in one easily accessible space
With researchers increasingly encouraged or required to share their data, preparing to share datasets with confidential identifiers of people and organizations is particularly challenging. Join JHU Data Management Services for an overview of techniques for assessing disclosure risk and hiding personal identifiers and Protected Health Information in quantitative and qualitative data, in compliance with IRB and HIPAA guidance. We also discuss preparing consent forms that facilitate data sharing, and keeping identifier data secure during and after projects. <Handout><Register here>