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Upcoming Training & Workshops
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 JHU Data Services for an overview of common privacy disclosure risks from personal and health identifiers in data. We discuss how to comply with IRB and HIPAA guidance for data security within the research team and introduce techniques for de-identifying data for external collaborators and public databases. You may preview session topics in our online module and guide.
Registration link: https://jhu.libcal.com/event/8218893
Do you work with data in spreadsheets? This JHU Data Services workshop will teach you how to clean and standardize your tabular data efficiently and reproducibly using OpenRefine. OpenRefine is a free, open-source tool with a graphical user interface (GUI) to clean and organize data – no coding required! The bulk of this 2.5-hour workshop will be a hands-on tutorial cleaning a dataset in OpenRefine.
After taking this workshop, participants will:
- Understand the common features of messy datasets
- Be able to carry out several transformations in OpenRefine to clean and standardize data for further analysis
- Leave with a test project that can be used to practice further data analysis or learn advanced features of OpenRefine, such as working with APIs
Registration link: https://jhu.libcal.com/event/8218934
Prerequisite: Introduction to R for Absolute Beginners or some experience using R. The dplyr package is a popular R package that people often use to manipulate and join datasets. You will need to have either some basic knowledge about using R or have previously attended our Introduction to R for Absolute Beginners workshop in order to take this one. Join JHU Data Services for this workshop and you will learn to use several functions, including mutate(), filter(), select(), summarize() and group_by(), in dplyr to manipulate data for the first half of the workshop. For the second part of this workshop, you will learn the join functions (e.g. left_join(), right_join(), inner_join(), semi_join(), anti_join(), full_join(), bind_rows() and bind_cols()) and set operations (e.g. union(), intersect() and setdiff()) in dplyr to combine two datasets. You will have plenty of opportunities to do hands-on activities on your laptop and work on datasets provided by instructors.
Registration link: https://jhu.libcal.com/event/8218962
This JHU Data Services half-day course introduces students to ArcGIS Pro, the most widely used geographic information systems (GIS) software. Learn the basics which include how to work with spatial data and how to create maps. If your research calls for making maps or using a geographic information system to analyze data, then this class is for you.
Registration link: https://jhu.libcal.com/event/8218969
This JHU Data Services half-day course introduces students to the tools in ArcGIS Pro, tools. Learn how to work with spatial data and get an introduction to the most often used geospatial analytic tools. Take this class if you want to learn how to use the many geoprocessing tools.
Registration link: https://jhu.libcal.com/event/8219143