Interested 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.
You are invited to stop by the Edge Workshop Room on Mondays for a new Rfun program, the R Open Labs, 6-7pm, Sept. 16 through Oct. 28. No need to register although you are encouraged to double-check the R Open Labs schedule/hours. Bring your laptop!
This is your chance to polish R skills in a comfortable and supportive setting. If you’re a bit more advanced, come and help by demonstrating the supportive learning community that R is known for.
No Prerequisites, but please bring your laptop with R/RStudio installed. No skill level expected. Beginners, intermediate, and advanced are all welcome. One of the great characteristics of the R community is the supportive culture. While we hope you have attended our Intro to R workshop (or watched the video, or equivalent). This is an opportunity to learn more about R and to demystify some part of R that your find confusing.
What are Open Labs
Open labs are semi-structured workshops designed to help you learn R. Each week brief instruction will be provided, followed by time to practice, work together, ask questions and get help. Participants can join the lab any time during the session, and are welcome to work on unrelated projects.
The Open Labs model was established by our colleagues at Columbia and adopted by UNC Chapel Hill. We’re giving this a try as well. Come help us define our direction and structure. Our goal is to connect researchers and foster a community for R users on campus.
How do I Get Started?
Attend an R Open Lab. Labs occur on Mondays, 6pm-7pm in the Edge Workshop Room in the Bostock Library. In our first meeting we will decide, as a group, which resource will guide us. We will pick one of the following resources…
R for Data Science by Hadley Wickham & Garrett Grolemund (select chapters, workbook problems, and solutions)
Please bring a laptop with R and R Studio installed. If you have problems installing the software, we can assist you with installation as time allows. Since we’re just beginning with R Open Labs, we think there will be time for one-on-one attention as well through learning and community building.
How to install R and R Studio
If you are getting started with R and haven’t already installed anything, consider using using these installation instructions. Or simply skip the installation and use one of these free cloud environments:
We’ll start at the beginning, however, R Open Labs recommends that you attend our Intro to R workshop or watch the recorded video. Being a beginner makes you part of our target audience so come ready to learn and ask questions. We also suggest working through materials from our other workshops, or any of the resource materials listed in the Attend an R Open Lab section (above). But don’t let lack of experience stop you from attending. The resources mentioned above will be the target of our learning and exploration.
As data driven research has grown at Duke, Data and Visualization Services receives an increasing number of requests for partnerships, instruction, and consultations. These requests have deepened our relationships with researchers across campus such that we now regularly interact with researchers in all of Duke’s schools, disciplines, and interdepartmental initiatives.
In order to expand the Libraries commitment to partnering with researchers on data driven research at Duke, Duke University Libraries is elevating the Data and Visualization Services department to the Center for Data and Visualization Sciences (CDVS). The change is designed to enable the new Center to:
Expand partnerships for research and teaching
Augment the ability of the department to partner on grant, development, and funding opportunities
Develop new opportunities for research, teaching, and collections – especially in the areas of data science, data visualization, and GIS/mapping research
Recognize the breadth and demand for the Libraries expertise in data driven research support
Enhance the role of CDVS activities within Bostock Libraries’ Edge Research Commons
We believe that the new Center for Data and Visualization Sciences will enable us to partner with an increasingly large and diverse range of data research interests at Duke and beyond through funded projects and co-curricular initiatives at Duke. We look forward to working with you on your next data driven project!
A goal of Duke University Libraries (DUL) is to support the growing and changing needs of the Duke research community. This can take many forms. Within Data and Visualization Services, we provide learning opportunities, consulting services, and computational resources to help Duke researchers implement their data-driven research projects. Monitoring and assessing new tools and platforms also helps DUL stay in tune with changing research norms and practices. Today the increasing focus on the importance of transparency and reproducibility has resulted in the development of new tools and resources to help researchers produce and share more reproducible results. One such tool is Code Ocean.
Code Ocean is a computational reproducibility platform that employs Docker technology to execute code in the cloud. The platform does two key things—it integrates the metadata, code, data and dependencies into a single ‘compute capsule’, ensuring that the code will run—and it does this in a single web interface that displays all inputs and results. Within the platform, it is possible to develop, edit or download the code, run routines, and visualize, save or download output, all from a personal computer. Users or reviewers can upload their own data and test the effects of changing parameters or modification of the code. Users can also share their data and code through the platform. Code Ocean provides a DOI for all capsules facilitating attribution and a permanent connection to any published work.
In order to help us understand and evaluate the usefulness of the Code Ocean platform to the Duke research community, DUL will be offering trial access to the Code Ocean cloud-based computational reproducibility platform starting on October 1, 2018. To learn more about what is included in the trial access and to sign up to participate, visit the Code Ocean pilot portal page.