Appendix#
Keeping on top of provenance#
Licenses
Streamlining for reproducibility
Licenses#
Where does the file come from?
How can we describe this later to somebody?
Point and click is long to describe.
What are the rights we have?
Examples:
Creative Commons licenses, used for artistic products and data
Open Source licenses (BSD, GPL, MIT, etc.), used for software (code)
License applying to Geodist data
CEPII GeoDist is under an “Etalab 2.0 license”
Downloading via code#
Easiest:
Stata
use "$URL" , clear
Why not?
Will it be there in two months? In six years?
What if the internet connection is down?
Easy:
Stata
global URL "https://www.cepii.fr/distance/dist_cepii.dta"
copy "$URL" (outputfile), replace
R
rootdir <- getwd()
datadir <- paste(rootdir, "data", sep = "/")
Creating a README#
Cite both dataset and working paper.
Add data URL and time accessed (can you think of a way to automate this?).
Add a link to license (also: download and store the license).
Links#
Some additional guidance can be found on the website of the Social Science Data Editors (URLs subject to change):
Additional training resources#
“Day 1 Tutorial”: Presented on Sept 12, 2024 at FSRDC conference (pre-program), subject to change: https://larsvilhuber.github.io/day1-tutorial/
General purpose guidance about “self checking” your reproducibility package: https://larsvilhuber.github.io/self-checking-reproducibility/
Examples of replication packages#
https://doi.org/10.3886/E154241V2 not only code, but faces the problem that IRS data cannot have variables revealed. Their workaround is not the same one as in this tutorial.
https://www.openicpsr.org/openicpsr/project/162581/version/V1/view
This textbook’s source: labordynamicsinstitute/reproducibility-confidential
Licensed under 