#  Data Provenance Session 

 



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## eeProv: Automatically tracking your data in R

[Margo Seltzer](https://www.eecs.harvard.edu/margo/), Herchel Smith Professor of Computer Science, Harvard University  
Barbara Lerner, Mt. Holyoke College  
Emery Boose, Harvard Forest  
  
**Room:** *TMEC 426 Conference Room, Tosteson Medical Education Center, Harvard Medical School*  
***2:30 - 4:00pm, July 12th***

This tutorial provides a hands-on introduction to the eeProv tool suite, an  
integrated collection of tools that help you debug and analyze R programs.  
At its core, eeProv is a data provenance system -- it automatically and  
transparently keeps track of where your data came from, how your data was  
transformed by R statements, functions, and packages, and what dependencies  
exist between data elements and data and code segments. We will introduce  
the ideas behind the system and then walk you through some example use cases.  
Finally, we'll turn you loose on some data, so you can become comfortable  
using the tool. We are looking forward to your feedback and ideally in your  
incorporating eeProv into your own R development.  
  
  
Please plan on bringing a laptop to the tutorial. We will provide all the software you’ll need.

Install virtual box from:   
<https://github.com/End-to-end-provenance/RDataTracker/wiki/Dataverse-User-Meeting--7-12-16>

[Community Notes Document for this session](https://docs.google.com/document/d/1v_OcVsEJo_Tq9sVU609fcIbo16PpiGcimYiybn8-T5o/edit?usp=sharing)