List of edges of the metabolic network of C.elegans. Data processed by members of our group.

Community identification using Extremal Optimization J. Duch and A. Arenas, Physical Review E , vol. 72, 027104

List of edges of the giant component of the network of users of the Pretty-Good-Privacy algorithm for secure information interchange. Data compiled by members of our group.

M. Boguña, R. Pastor-Satorras, A. Diaz-Guilera and A. Arenas, Physical Review E, vol. 70, 056122

List of edges of the network of Jazz musicians. Data compiled by members of our group.

P.Gleiser and L. Danon , Adv. Complex Syst.6, 565 (2003).

List of edges of the network of e-mail interchanges between members of the Univeristy Rovira i Virgili (Tarragona). Data compiled by members of our group.

R. Guimera, L. Danon, A. Diaz-Guilera, F. Giralt and A. Arenas, Physical Review E, vol. 68, 065103(R), (2003).

The Higgs dataset has been built after monitoring the spreading processes on Twitter before, during and after the announcement of the discovery of a new particle with the features of the elusive Higgs boson on 4th July 2012. The messages posted in Twitter about this discovery between 1st and 7th July 2012 are considered.

The four directional networks made available here have been extracted from user activities in Twitter as:
> Re-tweeting (retweet network).
> Replying (reply network) to existing tweets.
> Mentioning (mention network) other users.
> Friends/followers social relationships among user involved in the above activities.

M. De Domenico, A. Lima, P. Mougel and M. Musolesi. The Anatomy of a Scientific Rumor. (Nature Open Access) Scientific Reports 3, 2980 (2013).

Data was collected in 2013 from the official website of Transport for London ( https://www.tfl.gov.uk/) and manually cross-checked.
Nodes are train stations in London and edges encode existing routes between stations. Underground, Overground and DLR stations are considered (see https://www.tfl.gov.uk/ for further details). The multiplex network used in the paper makes use of three layers corresponding to:

> The aggregation to a single weighted graph of the networks of stations corresponding to each underground line (e.g., District, Circle, etc)
> The network of stations connected by Overground
> The network of stations connected by DLR

Raw data and geographical coordinates of stations are provided. We also provide the multiplex networks after considering real disruptions occurring in London.

Manlio De Domenico, Albert Solé-Ribalta, Sergio Gómez, and Alex Arenas, "Navigability of interconnected networks under random failures". PNAS 111, 8351-8356.

The multilayer network is composed by thirty-seven different layers each one corresponding to a different airline operating in Europe.

Ref: Alessio Cardillo, Jesús Gómez-Gardenes, Massimiliano Zanin, Miguel Romance, David Papo, Francisco del Pozo and Stefano Boccaletti - Emergence of network features from multiplexity. Scientific Reports 3, Article number: 1344 doi:10.1038/srep01344

The multiplex social network consists of five kinds of online and offline relationships (Facebook, Leisure, Work, Co-authorship, Lunch) between the employees of Computer Science department at Aarhus.

Ref: Matteo Magnani, Barbora Micenkova, Luca Rossi - Combinatorial Analysis of Multiple Networks. arXiv:1303.4986.

Data collected by Coleman, Katz and Menzel on medical innovation, considering physicians in four towns in Illinois, Peoria, Bloomington, Quincy and Galesburg.

They were concerned with the impact of network ties on the physicians adoption of a new drug, tetracycline. Three sociometric matrices (layers) were generated, based on the following questions:

> When you need information or advice about questions of therapy where do you usually turn?

> And who are the three or four physicians with whom you most often find yourself discussing cases or therapy in the course of an ordinary week -- last week for instance?

> Would you tell me the first names of your three friends whom you see most often socially?

Ref: J. Coleman, E. Katz, and H. Menzel.- "The Diffusion of an Innovation Among Physicians". Sociometry (1957) 20:253-270.

Interactions in a tailor shop in Zambia (then Northern Rhodesia) over a period of ten months.
Layers represent two different types of interaction, recorded at two different times (seven months apart) over a period of one month. TI1 and TI2 record the "instrumental" (work- and assistance-related) interactions at the two times; TS1 and TS2 the "sociational" (friendship, socioemotional) interactions.
The data are particularly interesting since an abortive strike occurred after the first set of observations, and a successful strike took place after the second.

Ref: Kapferer B. (1972) - "Strategy and transaction in an African factory".

The multiplex social network consists of 3 kinds of relationships (Advice, Friendship and "Reports to") between managers of a high-tech company.

Ref: D. Krackhardt - "Cognitive social structures". Social Networks (1987), 9, 104-134

The multiplex social network consists of 3 kinds of (Co-work, Friendship and Advice) between partners and associates of a corporate law partnership.

Ref: Emmanuel Lazega - "The Collegial Phenomenon: The Social Mechanisms of Cooperation Among Peers in a Corporate Law Partnership". Oxford University Press (2001). Tom A.B. Snijders, Philippa E. Pattison, Garry L. Robins, and Mark S. Handcock - "New specifications for exponential random graph models".

Ref: Tom A.B. Snijders, Philippa E. Pattison, Garry L. Robins, and Mark S. Handcock - "New specifications for exponential random graph models". Sociological Methodology (2006), 99-153.

The multiplex social network consists of 2 layers (marriage alliances and business relationships) describing florentine families in the Renaissance.

Ref: JF Padgett, CK Ansell - "Robust Action and the Rise of the Medici, 1400-1434". American journal of sociology, 1259-1319

The data were collected by Vickers from 29 seventh grade students in a school in Victoria, Australia. Students were asked to nominate their classmates on a number of relations including the following three (layers):

> Who do you get on with in the class?
> Who are your best friends in the class?
> Who would you prefer to work with?

Students 1 through 12 are boys and 13 through 29 are girls.

Ref: M. Vickers and S. Chan - Representing Classroom Social Structure. Melbourne: Victoria Institute of Secondary Educat