Category Archives: machine learning

Helenmary Sheridan, Research Data Management Consultant

Helenmary Sheridan, research data management consultant
Need held curating your data or identifying a repository to share data? Helenmary can help!

CDVS welcomes Helenmary Sheridan as the third member of the research data management (RDM) team. Helenmary joined Duke in August 2024 to help the library scale up classes, group trainings, and individualized consultations on RDM topics including NIH data management plans, data sharing in repositories such as the Duke Research Data Repository, and improving research reproducibility through documentation. Her position is supported by the Compute and Data Services Alliance for Research (CDSA), a new cross-campus initiative to support researchers with their computational needs.

Prior to joining Duke, Helenmary was the Data Services Librarian at the health sciences library at the University of Pittsburgh, where she provided data management training to faculty, staff, and students across the health disciplines. She has nearly ten years of experience working with scientific metadata and file formats, especially for data from imaging research (biomedical and otherwise.)

Helenmary’s favorite part of her job is teaching, especially Introduction to Research Data Management workshops for new graduate students and faculty that may be their first formal experience with research data methods. “It sounds like a dry subject,” she says, “so I love to see how excited researchers get when they realize how much easier these tools can make their lives.” You can contact Helenmary through the CDVS inbox at: askdata@duke.edu.

2020 RStudio Conference Livestream Coming to Duke Libraries

RStudio 2020 Conference LogoInterested in attending the 2020 RStudio Conference, but unable to travel to San Francisco? With the generous support of RStudio and the Department of Statistical Science, Duke Libraries will host a livestream of the annual RStudio conference starting on Wednesday, January 29th at 11AM. See the latest in machine learning, data science, data visualization, and R. Registration links and information about sessions follow. Registration is required for the first session and keynote presentations.  Please see the links in the agenda that follows.

Wednesday, January 29th

Location: Rubenstein Library 249 – Carpenter Conference Room

11:00 – 12:00 RStudio Welcome – Special Live Opening Interactive Event for Watch Party Groups
12:00 – 1:00 Welcome for Hadley Wickham and Opening Keynote – Open Source Software for Data Science (JJ Allaire)
1:00 – 2:00 Data, visualization, and designing with AI (Fernanda Viegas and Martin Wattenberg, Google)
2:30 – 4:00 Education Track (registration is not required)
Meet you where you R – Lauren Chadwick, R Studio.
Data Science Education in 2022 (Karl Howe and Greg Wilson, R Studio)
Data science education as an economic and public health intervention in East Baltimore (Jeff Leek, Johns Hopkins)
Of Teacups, Giraffes, & R Markdown (Desiree Deleon, Emory)

Location: Edge Workshop Room – Bostock 127

5:15 – 6:45 All About Shiny  (registration is not required)
Production-grade Shiny Apps with golem (Colin Fay, ThinkR)
Making the Shiny Contest (Duke’s own Mine Cetinkaya-Rundel)
Styling Shiny Apps with Sass and Bootstrap 4(Joe Cheng, RStudio)
Reproducible Shiny Apps with shinymeta (Carson Stewart, RStudio)
7:00 – 8:30 Learning and Using R (registration is not required)
Learning and using R: Flipbooks (Evangeline Reynolds, U Denver)
Learning R with Humorous Side Projects (Ryan Timpe, Lego Group)
Toward a grammar of psychological Experiments (Danielle, Navaro, University of New South Wales)
R for Graphical Clinical Trial Reporting(Frank Harrell, Vanderbilt)

Thursday, January 30th

Location: Edge Workshop Room – Bostock 127

12:00 – 1:00 Keynote: Object of type closure is not subsettable (Jenny Bryan, RStudio)
1:23 – 3:00 Data Visualization Track (registration is not required)
The Glamour of Graphics (William Chase, University of Pennsylvania)
3D ggplots with rayshader (Dr. Tyler Morgan-Wall, Institute for Defense Analyses)
Designing Effective Visualizations (Miriah Meyer, University of Utah)
Tidyverse 2019-2020 (Hadley Wickham, RStudio)
3:00 – 4:00 Livestream of Rstudio Conference Sessions (registration is not required)
4:00 – 5:30 Data Visualization Track 2 (registration is not required)
Spruce up your ggplot2 visualizations with formatted text (Claus Wilke, UT Austin)
The little package that could: taking visualizations to the next level with the scales package (Dana Seidel, Plenty Unlimited)
Extending your ability to extend ggplot2 (Thomas Lin Pedersen, RStudio)
5:45 – 6:30 Career Advice for Data Scientists Panel Discussion (registration is not required)
7:00 – 8:00 Keynote: NSSD Episode 100 (Hillary Parker, Stitchfix and Roger Peng, JHU)