Track the impact of research software.
Python CSS HTML JavaScript Shell PLSQL
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
data add files. Aug 29, 2015
models add python stuff back in it Jan 28, 2017
scripts remove --no-rq Jan 21, 2017
sql add library to is_organization Nov 12, 2015
templates add margin to link. Mar 4, 2018
test get github repos Jan 24, 2017
.gitignore add missing links Nov 9, 2015
LICENSE Initial commit Mar 28, 2015
Procfile remove reload Apr 1, 2016 fix to reload Jan 3, 2017 add end of project to readme. Mar 4, 2018
blog_notes.txt add blog notes Oct 1, 2015 change sort_score to impact Oct 1, 2015 caching in the github_repo module load now. Aug 30, 2015 add stuff in to check queue Jan 30, 2017
requirements.txt remove engagement subscore. Oct 19, 2015 newrelic back in, comment start_worker() back in. Sep 9, 2015 fixes to run updates Jan 20, 2017 get github repos Jan 24, 2017

the Depsy project has successfully concluded, and is no longer being maintained. We're now working on a followup project to track software impact, funded by the Sloan Foundation.

We need to value the software that powers science

Today's cutting-edge science is built on an array of specialist research software. This research software is often as important as traditional scholarly papers--but it's not treated that way when it comes to funding and tenure. There, the traditional publish-or-perish, show-me-the-Impact-Factor system still rules.

We need to fix that. We need to provide meaningful incentives for the scientist-developers who make important research software, so that we can keep doing important, software-driven science.

Depsy helps value research software

Lots of things have to happen to support this change. Depsy is a shot at making one of those things happen: a system that tracks the impact of software in software-native ways.

That means not just counting up citations to a hastily-written paper about the software, but actual mentions of the software itself in the literature. It means looking how software gets reused by other software, even when it's not cited at all. And it means understanding the full complexity of software authorship, where one project can involve hundreds of contributors in multiple roles that don't map to traditional paper authorship.

This is just the beginning

Depsy doesn't do any of these things perfectly, and it's not supposed to. Instead, Depsy is a proof-of-concept to show that we can do them at all. The data and tools are there. We can measure and reward software impact, like we measure and reward the impact of papers.

Given that, it's not a question of if research software becomes a first-class scientific product, but when and how. So let's start talking about when and how. Let's improve Depsy, let's build tools better than Depsy, and let's (most importantly) build the cultural and political structures that can use these systems.

Let's talk details


Depsy tracks research software packages hosted on either CRAN (the main software repository for the R programming language) or PyPI (the software repository for Python-language software). That adds up to 7,057 active R research software projects on Depsy, and 4,166 active Python research software projects.

We've found all this software being credited in the scholarly literature 83,445 times, reused by other software 960,619 times, and downloaded 221,368,685 (last month). For a better overview of all this data, plus details on how we collect and process it, check out the paper in progress.

Access to data

Everything in Depsy is open, and we encourage reuse of the data and code. You can use the API (see "View in Api" buttons on the package, person, and tag pages), or get larger-scale access via our read-only postgres database. The database connection details (plus an example of how to connect in R) are in the Knitr source for the paper.


Depsy is being built at Impactstory by Jason Priem and Heather Piwowar, and is funded by an EAGER grant from the National Science Foundation.