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About Netzschleuder

This is a catalogue and repository of network datasets with the aim of aiding scientific research.

This website is meant to be browsed both by humans and machines alike, and can also be accessed via a convenient JSON API, or via the graph-tool library. The network datasets themselves are available in several machine-readable formats, in particular gt, GraphML, GML and CSV.

The upstream origin of each dataset is meant to be as transparent as possible. Each dataset contains its own publicly available extraction and parsing script, accessible via a git repository, which also includes the entire code for this website, released as Free Software under the AGPLv3.

Users are encouraged to inspect the entire pipeline from original upstream data publication, downloading, parsing and format conversion.

Users are also welcome to report problems or omissions with the datasets, as well as suggest new ones, either by opening an issue, or simply by forking the git repository and proposing a merge request.

Instructions about how to contribute to the repository are available in the wiki page.

Attribution

Whenever using the data contained in this website, you should cite primarily the upstream authors that are listed for every dataset.

If there is need to cite this website in particular, just use: Tiago P. Peixoto, "The Netzschleuder network catalogue and repository", https://networks.skewed.de/ (2020). (It is not our intention to "intercept" citations to the primary sources, so please only use this if referring to the repository as a whole.)

When collecting data for this website, we made extensive use of the Index of Complex Networks (ICON)1 by the group of Prof. Aaron Clauset at the University of Colorado Boulder, as well as the KONECT project2, by Jérôme Kunegis.

The dataset "tags" reflect in large part the taxonomy and graph attributes that have been compiled by the ICON project1, as well as the data descriptions themselves.


  1. Aaron Clauset, Ellen Tucker and Matthias Sainz, "The Colorado Index of Complex Networks." https://icon.colorado.edu/ (2016). 

  2. Jérôme Kunegis. "KONECT – The Koblenz Network Collection." In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. doi:10.1145/2487788.2488173  

Disclaimer

The data made available in this website are processed versions of the upstream sources, not verbatim copies. They are made available with the belief that this is not only permitted, but the expressed intent of the original authors was to foster public dissemination. If this is not the case for any particular dataset, please open an issue and this will be promptly rectified.

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