Category Archives: workshops

CDVS Data Workshops: Spring 2022

As we begin the new year, the Center of Data and Visualization Sciences is happy to announce a series of twenty-one data workshops designed to empower you to reach your goals in 2022. With a focus on data management, data visualization, and data science, we hope to provide a diverse set of approaches that can save time, increase the impact of your research, and further your career goals.

While the pandemic has shifted most of our data workshops online, we remain keenly interested in offering workshops that reflect the needs and preferences of the Duke research community. In November, we surveyed our 2021 workshop participants to understand how we can better serve our attendees this spring. We’d like to thank those who participated in our brief email survey and share a few of our observations based on the response that we received.

Workshops Formats

While some of our workshops participants (11%) prefer in-person workshops and others (24%) expressed a preference for hybrid workshops, a little over half of the survey respondents (52%) expressed a preference for live zoom workshops. Our goal for the spring is to continue offering “live” zoom sessions while continuing to explore possibilities for increasing the number of hybrid and in-person options. We hope to reevaluate our workshops communities preferences later this year and will continue to adjust formats as appropriate.

Workshop format preferences
52% of respondents prefer online instruction, while another 24% would like to hybrid options

Participant Expectations

With the rapid shift to online content in the last two years coupled with a growing body of online training materials, we are particularly interested in how our workshop attendees evaluate online courses and their expectations for these courses.  More specifically, we were curious about whether registering for an online session includes more than simply the expectation of attending the online workshop.

While we are delighted to learn that the majority of our respondents (87%) intend to attend the workshop (our turnout rate has traditionally been about 50%), we learned that a growing number of participants had other expectations (note: for this question, participants could choose more than one response). Roughly sixty-seven percent of the sample indicated they expected to have a recording of the session available. While another sixty-six percent indicated that they expected a copy of the workshop materials (slides, data, code) even if they were unable to attend.

As a result of our survey, CDVS will make an increasing amount of our content available online this spring..  In 2021, we launched a new webpage designed to showcase our learning materials. In addition to our online learning site, CDVS maintains a github site (CDVS) as well as site focused on R learning materials (Rfun).

We appreciate your feedback on the data workshops and look forward to working with you in the upcoming year!

5 CDVS Online Learning Things

Within the Center for Data and Visualization Sciences (CDVS) we pride ourselves on providing numerous educational opportunities for the Duke community. Like many others during the COVID-19 pandemic, we have spent a large amount of time considering how to translate our in-person workshops to online learning experiences, explored the use of flipped classroom models, and learned together about the wonderful (and sometimes not so wonderful) features of common technology platforms (we are talking about you, Zoom).

Online learning setupWe also wanted to more easily surface the various online learning resources we have developed over the years via the web. Recognizing that learning takes place both synchronously and asynchronously, we have made available numerous guides, slide decks, example datasets, and both short-form and full-length workshops on our Online Learning Page. Below we highlight 5 online learning resources that we thought others interested in data driven research may wish to explore:

  • Mapping & GIS: R has become a popular and reproducible option for mapping and spatial analysis. Our Geospatial Data in R guide and workshop video introduce the use of the R language for producing maps. We cover the advantages of a code-driven approach such as R for visualizing geospatial data and demonstrate how to quickly and efficiently create a variety of map types for a website, presentation, or publication. 
  • Data Visualization: Visualization is a powerful way to reveal patterns in data, attract attention, and get your message across to an audience quickly and clearly. But, there are many steps in that journey from exploration to information to influence, and many choices to make when putting it all together to tell your story. In our Effective Data Visualization workshop, we cover some basic guidelines for effective visualization, point out a few common pitfalls to avoid, and run through a critique and iterations of an existing visualization to help you start seeing better choices beyond the program defaults.
  • Data ScienceQuickStart with R is our beginning data science module focusing on the Tidyverse — a data-first approach to data wrangling, analysis, and visualization.  Beyond introducing the Tidyverse approach to reproducible data workflows, we offer a rich allotment of other R learning resources at our Rfun site: workshop videos, case studies, shareable data, and code. Links to all our data science materials can also be found collated on our Online Learning page (above).
  • Data Management: Various stakeholders are stressing the importance of practices that make research more open, transparent, and reproducible including NIH who has released a new data management & sharing policy. In collaboration with the Office of Scientific Integrity, our Meeting Data Management Plan Requirements workshop presents details on the new NIH policy, describes what makes a strong plan, and where to find guidance, tools, resources, and assistance for building funder-based plans.
  • Data Sources: The U.S. Census has been collecting information on persons and businesses since the late 18th century, and tackling this huge volume of data can be daunting. Our guide to U.S. Census data highlights many useful places to view or download this data, with the Product Comparisons tab providing in chart form a quick overview of product contents and features. Other tabs provide more details about these dissemination products, as well as about sources for Economic Census data.

In the areas of data science, mapping & GIS, data visualization, and data management, we cover many other topics and tools including ArcGIS, QGIS, Tableau, Python for tabular data and visualization, Adobe Illustrator, MS PowerPoint, effective academic posters, reproducibility, ethics of data management and sharing, and publishing research data. Access more resources and past recordings on our online learning page or go to our upcoming workshops list to register for a synchronous learning opportunity.

Flipping Data Workshops

John Little is the Data Science Librarian in Duke Libraries Center for Data and Visualizations Sciences. Contact him at

The Center for Data and Visualization Sciences is and has been open since March! We never closed. We’re answering questions, teaching workshops, have remote virtual machines available, and business is booming.  

What’s changed? Due to COVID-19, the CDVS staff are working remotely. While we love meeting with people face-to-face in our lab, that is not currently possible. Meanwhile, digital data wants to be analyzed and our patrons still want to learn. By late spring I began planning to flip my workshops for fall 2020. My main goal was to transform a workshop into something more rewarding than watching the video of a lecture, something that lets the learner engage at their pace, on their terms.  

How to flip

Flipping the workshop is a strategy to merge student engagement and active learning.  In traditional instruction, a teacher presents a topic and assigns work aimed at reinforcing the lesson. 

Background:  I offer discrete two-hour workshops that are open to the entire university. There are very few prerequisites and people come with their own level of experience.  Since the workshops attract a broad audience, I focus on skills and techniques using general examples that reliably convey information to all learners. In this environment, discipline specific examples risk losing large portions of the audience. As an instructor I must try to leave my expectations of students’ skills and background knowledge — at the door.  

In a flipped classroom, materials are assigned and made available in advance. In this way, group Zoom-time can be used for questions and examples. This instruction model allows students to learn at their own pace, pause and rewind videos, practice exercises, or speed up lectures. During the workshop, students can bring questions relevant to their particular point of confusion.  

The main instructor goal is to facilitate a topic for student engagement that puts the students in control. This approach has a democratizing effect that allows students to become more active and familiar with the materials.  With flipped workshops, student questions appear to be more thoughtful and relevant. When the student is invited to take charge of their learning, the process of investigation becomes their self-driven passion.  

For my flipped workshops materials, I offer basic videos to introduce and reinforce particular techniques. I try to keep each video short, less than 25 minutes.  At the same time I offer plenty of additional videos on different topical details. More in-depth videos can cover important details that may feel ancillary or even demotivating, even if those details improve task efficiency. Sometimes the details are easier to digest when the student is engaged. This means students start at their own level and gain background when they’re ready.  Students may not return to the background material for weeks, but the materials will be ready when they are.

Flipping a consultation?

The Center for Data & Visualization Sciences provides open workshops and Zoom-based consulting. The flipped workshop model aligns perfectly with our consulting services since students can engage with the flipped workshop materials (recordings, code, exercises) at any time. When the student is ready for more information, whether a general question or a specific research question, I can refer to targeted background materials during my consultations. With the background resources, I can keep my consultations relevant and brief while also reducing the risk of under-informing.  

For my flipped workshop on R, or other CDVS workshops, please see our workshop page.

Fall 2020 – CDVS Research and Education During COVID-19

The Center for Data and Visualization Sciences is glad to welcome you back to a new academic year! We’re excited to have friends and colleagues returning to the Triangle and happy to connect with Duke community members who will not be on campus this fall.

This fall, CDVS will expand its existing online consultations with a new chat service and new online workshops for all members of the Duke community. Since mid-March, CDVS staff have redesigned instructional sessions, constructed new workflows for accessing research data, and built new platforms for accessing data tools virtually. We look forward to connecting with you online and working with you to achieve your research goals.

In addition to our expanded online tools and instruction, we have redesigned our CDVS-Announce data newsletter to provide a monthly update of data news, events, and workshops at Duke. We hope you will consider subscribing.

Upcoming Virtual CDVS Workshops

CDVS continues to offer a full workshops series for the latest strategies and tools for data focused research. Upcoming workshops for early September include:

R for data science: getting started, EDA, data wrangling
Thursday, Sep 1, 2020 10am – 12pm
This workshop is part of the Rfun series. R and the Tidyverse are a data-first coding language that enables reproducible workflows. In this two-part workshop, you’ll learn the fundamentals of R, everything you need to know to quickly get started. You’ll learn how to access and install RStudio, how to wrangle data for analysis, gain a brief introduction to visualization, practice Exploratory Data Analysis (EDA), and how to generate reports.

Research Data Management 101
Wednesday, Sep 9, 2020 10am – 12pm
This workshop will introduce data management practices for researchers to consider and apply throughout the research lifecycle. Good data management practices pertaining to planning, organization, documentation, storage and backup, sharing, citation, and preservation will be presented using examples that span disciplines. During the workshop, participants will also engage in discussions with their peers on data management concepts as well as learn about how to assess data management tools.

R for Data Science: Visualization, Pivot, Join, Regression
Wednesday, Sep 9, 2020 1pm – 3pm
This workshop will introduce data management practices for researchers to consider and apply throughout the research lifecycle. Good data management practices pertaining to planning, organization, documentation, storage and backup, sharing, citation, and preservation will be presented using examples that span disciplines. During the workshop, participants will also engage in discussions with their peers on data management concepts as well as learn about how to assess data management tools.

ArcGIS StoryMaps
Thursday, September 10, 2020 1pm – 2:30pm
This workshop will help you get started telling stories with maps on the ArcGIS StoryMaps platform. This easy-to-use web application integrates maps with narrative text, images, and videos to provide a powerful communication tool for any project with a geographic component. We will explore the capabilities of StoryMaps, share best practices for designing effective stories, and guide participants step-by-step through the process of creating their own application.

Assignment Tableau: Intro to Tableau work-together
Friday, September 11, 2020 10am – 11:30am
Work together over Zoom on an Intro to Tableau assignment. Tableau Public (available for both Windows and Mac) is incredibly useful free software that allows individuals to quickly and easily explore their data with a wide variety of visual representations, as well as create interactive web-based visualization dashboards. Attendees are expected to watch Intro to Tableau Fall 2019 online first, or have some experience with Tableau. This will be an opportunity to work together on the assignment from the end of that workshop, plus have questions answered live.

R Open Labs – open hours to learn more R

New this fall…

R fun: An R Learning Series
An R workshop series by the Center for Data and Visualization Sciences.

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/hoursBring 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…

  1. R for Data Science by Hadley Wickham & Garrett Grolemund (select chapters, workbook problems, and solutions)
  2. The RStudio interactive R Primers
  3. Advanced R by Hadley Wickham (select chapters and workbook problems)
  4. Or, the interactive learning series on R

Check our upcoming Monday schedule and feel free to RSVP.  We will meet for 6 nearly consecutive Mondays during the fall semester.

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:

Begin Working in R

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.

Is R help available outside of Open Labs?

If you require one-on-one help with R outside of the Open Labs, in-person assistance is available from the Library’s Center for Data & Visualization Sciences, our Center’s Rfun workshops, or our walk-in consulting in the Brandaleone Data and Visualization Lab (floormap. 1st Floor Bostock Library).


Announcing Tidyverse workshops for Winter 2018

Coming this winter the Data & Visualization Services Department will once again host a workshop series on the R programming language. Our spring offering is modeled on our well received R we having fun yet‽ (Rfun) fall workshop series. The four-part series will introduce R as a language for modern data manipulation by highlighting a set of tidyverse packages that enable functional data science. We will approach R using the free RStudio IDE, an intent to make reproducible literate code, and a bias towards the tidyverse. We believe this open tool-set provides a context that enables and reinforces reproducible workflows, analysis, and reporting.

This six-part series will introduce R as a language for modern data manipulation by highlighting a set of tidyverse packages that enable functional data science.

January Line-up

Title Date Registration Past Workshop
Intro to R Jan 19
1 – 3pm
register Resources
R Markdown
with Dr. Çetinkaya-Rundel
Jan 23
with Dr. Çetinkaya-Rundel
Jan 25
Mapping with R Jan 25
register Resources
Reproducibility & Git Jan 29
register Resources
Visualizationg with ggplot2 Feb 1
register Resources

An official announcement with links to registration is forthcoming. Feel free to subscribe to the Rfun or DVS-Announce lists. Or look to the DVS Workshop page for official registration links as soon as they are available.

Workshop Arrangement

This workshop series is intended to be iterative and recursive. We recommend starting with the Introduction to R. Proceed through the remaining three workshops in any order of interest.

Recordings and Past Workshops

We presented a similar version of this workshop series last fall and recorded each session whenever possible. You can stream past workshops and engage with the shareable data sets at your-own-pace (see the Past Workshop resources links, above.) Alternatively, all the past workshop resource links are presented in one listicle: Rfun recap.

Fall Data and Visualization Workshops

2017 Data and Visualization Workshops

Visualize, manage, and map your data in our Fall 2017 Workshop Series.  Our workshops are designed for researchers who are new to data driven research as well as those looking to expand skills with new methods and tools. With workshops exploring data visualization, digital mapping, data management, R, and Stata, the series offers a wide range of different data tools and techniques. This fall, we are extending our partnership with the Graduate School and offering several workshops in our data management series for RCR credit (please see course descriptions for further details).

Everyone is welcome at Duke Libraries workshops.  We hope to see you this fall!

Workshop Series by Theme

Data Management

09-13-2017 – Data Management Fundamentals
09-18-2017 – Reproducibility: Data Management, Git, & RStudio 
09-26-2017 – Writing a Data Management Plan
10-03-2017 – Increasing Openness and Reproducibility in Quantitative Research
10-18-2017 – Finding a Home for Your Data: An Introduction to Archives & Repositories
10-24-2017 – Consent, Data Sharing, and Data Reuse 
11-07-2017 – Research Collaboration Strategies & Tools 
11-09-2017 – Tidy Data Visualization with Python

Data Visualization

09-12-2017 – Introduction to Effective Data Visualization 
09-14-2017 – Easy Interactive Charts and Maps with Tableau 
09-20-2017 – Data Visualization with Excel
09-25-2017 – Visualization in R using ggplot2 
09-29-2017 – Adobe Illustrator to Enhance Charts and Graphs
10-13-2017 – Visualizing Qualitative Data
10-17-2017 – Designing Infographics in PowerPoint
11-09-2017 – Tidy Data Visualization with Python

Digital Mapping

09-12-2017 – Intro to ArcGIS Desktop
09-27-2017 – Intro to QGIS 
10-02-2017 – Mapping with R 
10-16-2017 – Cloud Mapping Applications 
10-24-2017 – Intro to ArcGIS Pro


11-09-2017 – Tidy Data Visualization with Python

R Workshops

09-11-2017 – Intro to R: Data Transformations, Analysis, and Data Structures  
09-18-2017 – Reproducibility: Data Management, Git, & RStudio 
09-25-2017 – Visualization in R using ggplot2 
10-02-2017 – Mapping with R 
10-17-2017 – Intro to R: Data Transformations, Analysis, and Data Structures
10-19-2017 – Developing Interactive Websites with R and Shiny 


09-20-2017 – Introduction to Stata
10-19-2017 – Introduction to Stata 













Fall 2016 DVS Workshop Series

GenericWorkshops-01Data and Visualization Services is happy to announce its Fall 2016 Workshop Series. Learn new ways of enhancing your research with a wide range of data driven research methods, data tools, and data sources.

Can’t attend a session?  We record and share most of our workshops online.  We are also happy to consult on any of the topics above in person.  We look forward to seeing you in the workshops, in the library, or online!

Data Sources
Data Cleaning and Analysis
Data Analysis
Introduction to Stata (Two sessions: Sep 21, Oct 18)
Mapping and GIS
Introduction to ArcGIS (Two sessions: Sep 14, Oct 13)
ArcGIS Online (Oct 17)
Data Visualization

Visualizing Qualitative Data (Oct 19)
Visualizing Basic Survey Data in Tableau – Likert Scales (Nov 10)

Data and Visualization Spring 2016 Workshops

Spring 2016 DVS WorkshopsSPRING 2016: Data and Visualization Workshops 

Interested in getting started in data driven research or exploring a new approach to working with research data?  Data and Visualization Services’ spring workshop series features a range of courses designed to showcase the latest data tools and methods.  Begin working with data in our Basic Data Cleaning/Analysis or the new Structuring Humanities Data  workshop.  Explore data visualization in the Making Data Visual class.  Our wide range of workshops offers a variety of approaches for the meeting the challenges of 21st century data driven research.   Please join us!

Workshop by Theme






* – For these workshops, no prior experience with data projects is necessary!  These workshops are great introductions to basic data practices.

DVS Fall Workshops

GenericWorkshops-01Data and Visualization Services is happy to announce its Fall 2015 Workshop Series.  With a range of workshops covering basic data skills to data visualization, we have a wide range of courses for different interests and skill levels..  New (and redesigned) workshops include:

  • OpenRefine: Data Mining and Transformations, Text Normalization
  • Historical GIS
  • Advanced Excel for Data Projects
  • Analysis with R
  • Webscraping and Gathering Data from Websites

Workshop descriptions and registration information are available at:




OpenRefine: Data Mining and Transformations, Text Normalization
Sep 9
Basic Data Cleaning and Analysis for Data Tables
Sep 15
Introduction to ArcGIS
Sep 16
Easy Interactive Charts and Maps with Tableau
Sep 18
Introduction to Stata
Sep 22
Historical GIS
Sep 23
Advanced Excel for Data Projects
Sep 28
Easy Interactive Charts and Maps with Tableau
Sep 29
Analysis with R
Sep 30
ArcGIS Online
Oct 1
Web Scraping and Gathering Data from Websites
Oct 2
Advanced Excel for Data Projects
Oct 6
Basic Data Cleaning and Analysis for Data Tables
Oct 7
Introduction to Stata
Oct 14
Introduction to ArcGIS
Oct 15
OpenRefine: Data Mining and Transformations, Text Normalization
Oct 20
Analysis with R
Oct 20