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https://github.com/emeryberger/csrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.
https://github.com/emeryberger/csrankings

computer-science computer-science-rankings conference dblp faculty metrics ranking

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A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

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README 

        
Computer Science Rankings

=========================



This ranking of top computer science schools is designed to identify institutions and faculty actively engaged in research across a number of areas of computer science. Unlike US News and World Report's approach, which is exclusively based on surveys, this ranking is entirely metrics-based. It measures the number of publications by faculty that have appeared at the most selective conferences in each area of computer science.



This approach is intended to be difficult to game, since publishing in such conferences is generally difficult: contrast this with other approaches like citation-based metrics, which have been repeatedly shown to be easy to manipulate. That said, incorporating citations in some form is a long-term goal.



See the FAQ for more details.



---



This repository contains all code and data used to build the computer science rankings website, hosted here:

https://csrankings.org



### Adding or modifying affiliations



**_NOTE: Updates are now processed on a quarterly basis. You may submit pull requests at any time, but they may not be processed until the next quarter (after three months have elapsed)._**



**You can now edit files directly in GitHub to create pull requests.** All data is

in the files `csrankings-[a-z].csv`, with authors listed in

alphabetical order by their first name, organized by the initial letter. Please read ```CONTRIBUTING.md``` for full details on

how to contribute.



### Trying it out at home



Because of GitHub size limits, to run this site, you will want to download the DBLP

data by running ``make update-dblp`` (note that this will consume

upwards of 19GiB of memory). To then rebuild the databases, just run

``make``. You can test it by running a local web server (e.g., ``python3 -m http.server``)

and then connecting to [http://0.0.0.0:8000](http://0.0.0.0:8000).



You will also need to install libxml2-utils (or whatever package

includes xmllint on your distro), npm, typescript, closure-compiler, python-lxml, [pypy](https://doc.pypy.org/en/latest/install.html),

and basex via a command line like:



``apt-get install libxml2-utils npm python-lxml basex; npm install -g typescript google-closure-compiler``



### Quick contribution via a shallow clone



A full clone of the CSrankings repository is almost 2GB, and the

`csrankings.csv` file is too large to edit via the GitHub web site. To

contribute a change without creating a full local clone of the

CSrankings repo, you can do a shallow clone. To do so, follow these

steps:



1. Fork the CSrankings repo. If you have an existing fork, but it is

not up to date with the main repository, this technique may not

work. If necessary, delete and re-create your fork to get it up to

date. (Do not delete your existing fork if it has unmerged changes you

want to preserve!)

1. Do a shallow clone of your fork: `git clone --depth 1

https://github.com/yourusername/CSrankings`. This will only download

the most recent commit, not the full git history.

1. Make your changes on a branch, push them to your clone, and create

a pull request on GitHub as usual.



If you want to make another contribution and some time has passed,

perform steps 1-3 again, creating a fresh fork and shallow clone.



### Acknowledgements and other rankings



This site was developed primarily by and is maintained by [Emery

Berger](https://emeryberger.com). It incorporates extensive feedback

from too many folks to mention here, including many contributors who

have helped to add and maintain faculty affiliations, home pages, and

so on.



This site was initially based on code and

data collected by [Swarat

Chaudhuri](https://www.cs.utexas.edu/~swarat/) (UT-Austin), though

it has evolved considerably since its inception. The

original faculty affiliation dataset was constructed by [Papoutsaki et

al.](http://cs.brown.edu/people/alexpap/faculty_dataset.html); since

then, it has been extensively cleaned and updated by numerous

contributors. A previous ranking

also used DBLP and Brown's dataset for [ranking theoretical computer

science](https://projects.csail.mit.edu/dnd/ranking/.).



This site uses information from [DBLP.org](http://dblp.org) which is made

available under the ODC Attribution License.



### License



CSRankings is covered by the [Creative Commons

Attribution-NonCommercial-NoDerivatives 4.0 International

License](https://creativecommons.org/licenses/by-nc-nd/4.0/).