Events

In this workshop by Johns Hopkins Data Services, attendees will overview best practices and factors to consider when preparing to share human-participant data in a repository, from the beginning of your project to the end.

This Johns Hopkins Data Services 90-minute workshop is designed to help you explore how maps and spatial thinking can support your work. Whether you are studying environmental patterns, public health, social trends, historical events, or other topics, maps can be a powerful way to analyze and communicate your findings.

Join Amy Lynne Shelton, executive director of the Center for Talented Youth, for a discussion about why it is essential for parents and educators to foster a balanced mindset and encourage students to embrace mistakes as valuable opportunities for growth.

Financial wellness educator Shahar Ziv will present a session on investing, hosted by Student Financial Support. Come learn about investing and possibly win a giveaway.

Join Johns Hopkins Data Services in the first session of this two-part workshop to explore how the Hopkins AI Lab (a generative artificial intelligence platform that provides secure, JHED-authenticated access to multiple large language models) can support your data-driven research.

Join Johns Hopkins Data Services for the final of a two-part workshop to explore how the Hopkins AI Lab can support your data-driven research, especially the practical applications of the generative artificial intelligence tool provided by Johns Hopkins for accessing, analyzing, cleaning, and visualizing data.

Curious about how artificial intelligence can support your mapping or geospatial analysis work? This one-hour workshop introduces how to use the Hopkins AI Lab to help you brainstorm, plan, and troubleshoot common geographic information systems tasks.

Protecting research participant and patients' privacy is challenging not just for security but also when anonymizing data for external collaborators, publications, and research databases. Join Johns Hopkins Data Services for an overview of common privacy disclosure risks from personal and health identifiers in data.

This class builds upon the introductory session on privacy protection for shared data, as a next step toward applying techniques for de-identifying several types of personal and health identifiers. Join Johns Hopkins Data Services in working through case examples and anonymization methods at an "intermediate" level suitable for preparing data for external collaborations and restricted access research databases.

The 20- to 30-minute Johns Hopkins East Baltimore Community & Connection Strolls around Eager Park in East Baltimore combine movement with meaningful conversation around engaging topics or questions. Whether you are looking to de-stress, meet new people, or simply enjoy a break in your day, all modes of participation are welcome—walkers, wheelchairs, strollers, or seated persons.