Data Management and Sharing
If you need assistance with Data Management and Sharing Plans for your grant proposals, please contact Data Services via firstname.lastname@example.org.
Data Services supports researchers, faculty, and students with a spectrum of resources for working with data to make your research and teaching successful. These include: data management and archiving; using GIS and geospatial data; finding and accessing data, and using other tools and software for working with data. Visit Data Services' consultation schedule, live webinars and self-paced online training sessions, and steps to share your data on our data repository (Johns Hopkins Research Data Repository) or our main website to learn more about Data Services.
Join Our ListServ
Join our listserv! We send out a few emails each year to keep you updated on our workshops, events and data-related news. To join the listserv, send an email to email@example.com with 'subscribe' in the subject line. You'll receive confirmation when your email address has been successfully added.
JHU Data Services supports members of the JHU community with a spectrum of resources for working with data. We have many guides to help you in your research and/or teaching endeavors:
|GIS & Maps
|An overview of introductory geospatial concepts
|Esri Software Access
|Information and links to download Esri software and data for the JHU community
|Teaching GIS & Maps
|Resources for JHU community members teaching GIS
|Maps & Online Map Resources
|Information on accessing Johns Hopkins University's map collection, and beyond
|Data and Statistics
|Information on accessing data and statistics for a variety of subject areas
Data Management & Analysis
|Best practices for data management
|Documenting Research Data
|Collection of resources shared in Data Services' Documenting Your Research Data online module
|Human Subject Identifiers
|Introduction to concepts and techniques for protecting and removing human subject identifiers
|Qualitative Data Analysis Software
|Overview and resource links for qualitative data analysis software (QDAS) such as nVivo and ATLAS.ti
|Using R and Python
|Resources for learning and using R and/or Python in your research.
|Guide for technologies, techniques, and best practices for data visualization.