A Taxonomy of Networks Jukka-Pekka Onnela 1,2,3,4†,∗ , Daniel J. Fenn 5,4,† , Stephen Reid 3 Mason A. Porter 6,4 , Peter J. Mucha 7 , Mark D. Fricker 8,4 , Nick S. Jones 3,9,4 1 Harvard Medical School, Harvard University, Boston MA 02115, USA 2 Harvard Kennedy School, Harvard University, Cambridge, MA 02138, USA 3 Department of Physics, University of Oxford, Oxford OX1 3PU, U.K. 4 CABDyN Complexity Centre, University of Oxford, Oxford OX1 1HP, U.K. 5 Mathematical and Computational Finance Group, University of Oxford, Oxford OX1 3LB, U.K. 6 Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, OX1 3LB, U.K. 7 Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics and Institute for Advanced Materials, Nanoscience & Technology, University of North Carolina, Chapel Hill, NC 27599, USA 8 Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, U.K. 9 Oxford Centre for Integrative Systems Biology, Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, U.K. † These authors contributed equally. ∗ To whom correspondence should be addressed: Onnela@med.harvard.edu The study of networks has grown into a substantial interdisciplinary endeavor across the natural, social, and information sciences. Yet there have been very few attempts to investigate the interrelatedness of the different classes of net- works studied by different disciplines. Here, we introduced a framework to establish a taxonomy of networks from various origins. The provision of this family tree not only helps understand the kinship of networks, but also fa- cilitates the transfer of empirical analysis, theoretical modeling, and concep- tual developments across disciplinary boundaries. The framework is based on probing the mesoscopic properties of networks, an important source of het- erogeneity for their structure and function. Using our method, we computed 1 arXiv:1006.5731v1 [physics.data-an] 29 Jun 2010