About Us
About the Index
The Index of Complex Networks (ICON) is a project based at the University of Colorado Boulder. It is coordinated by Prof. Aaron Clauset, with all the real work being carried out by a great team of student researchers.
ICON aims to assemble and provide a comprehensive index of real-world complex network data sets, across all domains of science. It is intentionally an index of data sets hosted elsewhere, not a repository -- ICON does not host any data sets itself. For each record in ICON, this website provides basic information about the network, including its domain, subdomain, size, a brief description, bibliographic reference, and instructions or a link for obtaining the data set from its host. ICON indexes all of the major network repositories as well as a large number of data sets found outside of these sites.
If you would like to cite ICON in a scientific publication, please cite:
Aaron Clauset, Ellen Tucker and Matthias Sainz, "The Colorado Index of Complex Networks." https://icon.colorado.edu (2016).
Project Team
(Project Lead) Prof. Aaron Clauset is a Professor in the Department of Computer Science and the BioFrontiers Institute, at the University of Colorado Boulder, and External Faculty at the Santa Fe Institute. His research focuses on the development and application of advanced computational tools for understanding the large-scale structure and function of complex systems. He received his Ph.D. in 2006 with honors from the University of New Mexico, and was subsequently an Omidyar Fellow at the Santa Fe Institute.
Publications
A. Ghasemian, H. Hosseinmardi, A. Galstyan, E.M. Airoldi, and A. Clauset
Proc. Natl. Acad. Sci. USA
data: the LinkPrediction corpus
Evaluating overfit and underfit in models of network community structure.
A. Ghasemian, H. Hosseinmardi, and A. Clauset
IEEE Trans. Knowledge and Data Engineering (TKDE) (2019).
data: the CommunityFitNet corpus
A. D. Broido and A. Clauset
Nature Communications
data: the ScaleFreeTest corpus
Characterizing the structural diversity of complex networks across domains.
K. Ikehara and A. Clauset
Preprint, arxiv:1710.11304 (2017).
Related Work
Raoul Wadhwa has created an ICON R package contain a number of ICON data sets.
Project Alumni
Rahul Shamkuwar was an undergraduate research assistant, majoring in Computer Science at CU Boulder with interest in distributed systems. He worked on the ICON project in 2024, where he designed the new web and database software using modern techniques.
Upasana Dutta was a masters student in Computer Science at CU Boulder, and working in part on the ICON project 2020-2022. Her interests focused on characterizing large-scale patterns in the structure of diverse networks across domains.
Alexander Ray was an undergraduate research assistant, majoring in Computer Science at CU Boulder, and working in part on the ICON project 2018-2020. His interests focused on efficient algorithms for network analysis, and the common structural patterns that span networks of different domains.
Christoph Uhl was an undergraduate research assistant, majoring in Computer Science at CU Boulder, and working in part on the ICON project 2018-2020.
Dr. Anna Broido was a doctoral student in Applied Mathematics at CU Boulder, working in part on the ICON project 2017-2019. Her dissertation focused on comparative approaches to network analysis, and methods to characterize the tail structure of degree distributions. She created the ScaleFreeTest corpus of networks .
Dr. Amir Ghasemian was a doctoral student in Computer Science at CU Boulder, working in part on the ICON project 2016-2018. His dissertation research focused on developing new methods for analyzing the large-scale structure of network. He created both the CommunityFitNet corpus of networks and the OptimalLinkPrediction corpus of networks .
Tetsumichi (Telly) Umada was an undergraduate research assistant, majoring in Computer Science and in Linguistics at CU Boulder, working on the ICON project from 2017-2018. His interests focused on in machine learning, deep learning, data visualization, and artificial intelligence.
Kansuke Ikehara was a masters student in Computer Science at CU Boulder, working on the ICON project from 2015-2016. His masters thesis focused on developing a comprehensive methodology for comparing different kinds of networks, and analyzed how structurally separable different types of networks were from each other.
McKenzie Weller is an undergraduate research assistant, majoring in Computer Science at CU Boulder, working on the ICON project 2016-2017. Her interests are in human-centered computing, human interaction and response.
Ellen Tucker was a staff researcher in Computer Science, working on the ICON project from 2015-2016. She evaluated structure patterns within an early version of the ICON corpus of network data sets. She received her BA in Mathematics in 2015 from CU Boulder, and went on to pursue a PhD in Computer Science at Northwestern University.
Matthias Sainz was an undergraduate research assistant, working on the ICON project from 2014-2016. He designed the web and database software that runs the site. He received his BS degree in Computer Science at CU Boulder in 2016, and went on to be a software developer at FullContact Inc, in Denver Colorado.
Funding Support
Funding for ICON was provided wholly by the University of Colorado Boulder.
Copyright © ICON 2016 - 2024.