Reproducibility And Communication In R




Reproducibility and Communication in R

6 November 2018

New York

Added 01-Jan-1970

This month it is our please to have Noam Ross and our very own, Ludmila Janda present on Reproducibility and Communication in R!

6:30-6:45pm General networking
6:45-6:55pm R-Ladies New York Announcements
6:55-7:25pm Reproducibility in an Office World or: How I Learned to Stop Worrying and Love OpenXML by Noam Ross
7:25-7:55pm A Data Odyssey: Communicating Results With Coworkers
by Ludamila Janda
7:55-8:00pm R-Ladies Community announcement
8:00-8:30pm Networking

Reproducibility in an Office World or: How I Learned to Stop Worrying and Love OpenXML

Many data scientists operate at the interface of two cultures with different tools and workflows - programmatic workflows (e.g., R Markdown) and WYSIWYG documents (e.g., Microsoft Word). The noisy interface between these can be an impediment to reproducibility, as well as a royal pain. I will discuss approaches I and others have tried in dealing with these issues, and why and how some have failed and succeeded. I'll also demonstrate some tools, including packages officer and rvg and some rarely used feaures of rmarkdown that ease the flow when collaborating across the divide.

Noam Ross is a Senior Research Scientist at EcoHealth Alliance, a non-profit in NYC that researches the connections between human and wildlife health. Noam builds models to understand and predict disease circulation in wildlife and spillover into people. Noam is also editor for software peer review at rOpenSci, a developer collective that builds R packages and catalyzes communities to enable open research and data. He has a Ph.D. in ecology from the University of California-Davis. Follow him on twitter at @noamross.

Title: A Data Odyssey: Communicating Results With Coworkers


Often, data scientists are tasked with communicating their results with people in the workplace who do not share the same technical background. Bridging the gaps between parties can be a perilous journey. In this talk, I will discuss how I have attempted to navigate this tricky terrain and provide some pointers for clear language use and data visualization choices. I’ll demonstrate how I pass on insights through visualizations using packages such as ggridges and ggalluvial and how I use rmarkdown to craft reports and take my coworkers on data adventures.


Ludmila Janda is a Data Scientist at Amplify, a pioneer in K–12 education since 2000, leading the way in next-generation curriculum and assessment. Today, Amplify serves four million students in all 50 states. Luda’s work provides insights on student and teacher usage, student success, and Amplify’s broader impact. She is a proud RLady and has a Master’s in Public Policy from the University of North Carolina-Chapel Hill. Follow her on twitter at @ludmila_janda.