Estrada, Ernesto

Lillo, Fabrizio

Strano, Emanuele

Zanin, Massimiliano

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Eur. Phys. J. Special Topics 215, 1–4 (2013)c© EDP Sciences, Springer-Verlag 2013DOI: 10.1140/epjst/e2013-01710-xTHE EUROPEANPHYSICAL JOURNALSPECIAL TOPICSEditorialSpatially embedded socio-technical complexnetworksEmanuele Strano1,a, Massimiliano Zanin2,3,4, Ernesto Estrada5,and Fabrizio Lillo6,7,81 LaSIG laboratory, Lausanne Institute of Technology (EPFL), Lausanne, Switzerland2 Innaxis Foundation & Research Institute, Madrid, Spain3 Centre for Biomedical Technology, Polytechnic University of Madrid, Spain4 Faculdade de Cieˆncias e Tecnologia, Universidade Nova de Lisboa, Portugal5 Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK6 Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy7 Dipartimento di Fisica, viale delle Scienze, 90128 Palermo, Italy8 Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USAComplex networks have emerged as a powerful tool for the analysis of complex sys-tems, i.e., systems that are composed of a large number of elements interactingin a non-linear fashion. In the last decade we have contributed to a real NetworksRevolution that has percolated many ﬁelds of science. Examples range from commu-nication science, genetics and sociology to epidemiology and urban studies. One ofthe reasons underpinning this success can be found in the natural adaptability ofcomplex networks to diﬀerent problems. This allows simpliﬁcation of the system,concentrating attention on patterns of interconnections and essentially enabling allother elements to be neglected. Another great advantage of complex networks wasthe presence of a mature and solid ground for its development, that is, graph theoryand statistical physics.Further consideration of complex networks might provide us with a more inter-esting interpretation of the origin of its success. As in many other scientiﬁc andnon-scientiﬁc ﬁelds, the deep nature of an object always aspires to re-emerge beyondits latent functions or temporary uses. From time to time, it also transpires that asingle idea survives over a signiﬁcant period of time with diﬀerent aliases as it movesfrom ﬁeld to ﬁeld, instigating new challenges and gaining its own maturity across gen-erations of scientists and accompanying the evolution of technology. This is the casefor Spatially Embedded Socio-Technical Complex Networks, and recentlythere has been increasing interest in the spatiality of their organisation. Spatiality innetwork-like objects is certainly not new. Even if extremely important, let us leaveaside Euler, the classical Ko¨nigsberg problems, and the classical results on planargraphs. Let us also assume that the vast and old ﬁelds of transportation studies andtransportation engineering have been an important step in its application. We mightthen attempt an easy but useful exercise to determine the origin of the language priorto its mathematical formalisation, and hence the origins of thinking about the worldas a collection of connected objects embedded into a space and creating a uniquesystem. The study of ancient cartography provides us with an excellent opportunityfor achieving this.We report here on a very interesting and beautiful example, one of the wonderfulmaps created by the ancient Persian geographer Ibrahim Al-Istakhri.a e-mail: emanuele.strano@epfl.ch2 The European Physical Journal Special TopicsFig. 1. Map of the Greater Khorasan by the Persian geographer Ibrahim Al-Istakhri, circa980 AD. Source: Department of Oriental Manuscripts, Bibliothe`que National de France.The map presumably represents the Greater Khorasan, which is a historical regionin the northeast of Persia. This map was used by merchants to trace their commercialroutes for goods exchange. In it, the coloured circles represent ancient cities. The ﬁrstversion of this map dated from around 980 AD, almost eight hundred years beforeEuler solved the Ko¨nigsberg problem. Besides interesting considerations related tothe interpretation of this map, our primary question is: does this map represent acomplex spatial network? We invite the reader to observe it: many geographical enti-ties (cities) are represented by coloured circles, and are connected to each other withblack lines representing streets, and with large blue lines representing rivers. This iscertainly a procedural map that was used as we would use any contemporary tubemap: in other words, this is deﬁnitely a network! Nodes are both labeled and coloured,meaning that they provide information regarding their class (this could be a sort ofweight but is at least a class). Nodes are also present in diﬀerent sizes: for instance,those nodes with degree greater than two seem to be larger than the others. There arealso half-nodes, which may be bringing additional information related to the nodes’class. Links connecting nodes are divided into two main typologies, i.e., rivers andstreets, indicating that this is also a multilayered network. Distances between nodesdo not approximate the real distances between geographical entities, which indicatesthat the links are non-weighted and that the network is fully procedural. Further-more, streets sometimes intersect both other streets and rivers in a non-planar way;we are therefore facing a three-dimensional embedded graph (?). Links are incidentwith nodes, but they can be also tangent or transverse, leading to chains and possiblySpatially-Embedded Socio-Technical Complex Networks 3ﬁctitious nodes. Finally, we note the presence of unconnected nodes, indicating thatthe network has diﬀerent separated components.Without going further into this game (the colour of the nodes may indicate akind of centrality, as suggested by the big red node in the lower left-hand corner ofthe map), we have identiﬁed a one thousand year old multilayer, multi-componentand potentially weighted network. The fact that this is a map, i.e., a representa-tion of the geography of a place, and that it is not a speciﬁc symbolic representa-tion that only a few specialised people were able to understand, means that thisnetwork-map was already a part of a mature shared code of representation, and thatthe origin of this code must be much older than the map itself. We might producemore examples of proto-networks, for instance from the history of cladistic trees orfrom the history of the evolution of symbolic languages, but we leave the readerto keep enjoining this game. The case we report here aims only to show that spa-tial problems and network representations have been intrinsically connected for avery long time, and that this is an old marriage, much older than we might ty-pically think. This might also be the reason that this marriage continues to stim-ulate the scientiﬁc community through to the year 2011, when two events wereindependently organised to deepen this approach: the Evolution of ComplexTransportation Networks, a workshop organised at the University of Strathclyde byEmanuele Strano and supported by the Urban Design Studies Unit and the Instituteof Complex System at Strathclyde, and the Complexity and the Future of Transporta-tion Systems Satellite Meeting, organised by Fabrizio Lillo and Massimiliano Zaninwithin the European Conference on Complex Systems 2011 in Wien. This issue ofEPJ Special Topics gathers together some of the best contributions presented at bothevents, as well as from other external contributions.From urban mobility to worldwide patterns in air transport, this issue presentsthe reader with an overview of how the movements of people can be described bymeans of complex networks, and how the evolution of the associated transportationsystems through time can be explained. The paper Modeling the Air Transport withComplex Networks: a short review by Massimiliano Zanin and Fabrizio Lillo reviewsthe most important aspects of air transportation networks; in it, a comprehensivereview of works published on this subject is oﬀered to the interested reader, alongwith considerations of the most promising lines for future researches.Ranging from large to small scales, some of the most important transportationmodes are represented in this issue.Besides the aforementioned tutorial paper, Azzam et al. analyse the evolution ofthe worldwide air transport network using a huge data set describing scheduledpassenger movements between 1979 and 2007. Among their most important results,they challenge the idea that this network is stationary, demonstrating that it is theresult of a combination of accelerated growth and important external constraints(e.g., airline business considerations and global macroeconomics). Cardillo et al. alsopresent a study of air transportation networks that challenges the re-schedulingproblem in Europe by means of multiple-layer structure. They deﬁne a layer as agiven airline and ﬁnd that, compared with the classical one-layer representation, thestructure of the network is changing both quantitatively and qualitatively.The structure and evolution of the trans-African highway system are studiedby Adamatzky et al. by means of an original approach, i.e., the imitation of thedevelopment forces by means of the slime mould Physarum polycephalum. Whenmajor cities are represented on a surface by sources of nutrients, the slime mouldexpands in order to connect all of them. Remarkably, the networks created by this or-ganism resemble the real one, shedding light on the self-organised forces deﬁning thegrowth of human transportation networks, and on the potential of the bio-inspiredcomputing approach.4 The European Physical Journal Special TopicsAt the national level, the mining of large mobility data provides a solid basis forunderstanding and modeling human mobility. This is the main goal of Pappalardoet al. when they propose the use of unique datasets based on GPS for tracking10 million journeys undertaken by 150,000 cars in the entirety of Italy.In a similar fashion, Caschili et al. are proposing a study of community detectionin time-varying commuting networks detected over two decades, which is appliedto regional planning. Their approach is used to validate the actual number, size andposition of political sub-regional partitions in the region of Sardinia, Italy. They con-clude that even unconsciously, the recent new Sardinia’s partition reﬂects the realcommuters, behaviour.Barrena et al. propose the use of hypergraphs, i.e., networks composed of multi-ple interconnected layers, for the study of the topological characteristics of subwaynetworks. Besides the speciﬁc results obtained for the networks of Vienna,Los Angeles, Montreal and Moscow, the work extends many essential network metricsto multi-layer scenarios, providing important analytical demonstrations.The rather peculiar Minneapolis Skyway Network, that connects diﬀerentbuildings in Minneapolis by means of glass-enclosed bridges, is studied by Huanget al. Using historical data ranging from 1962 to 2002, and adopting an agent-basedapproach, they analyse the forces deﬁning the growth of such networks, and theconsequences on the accessibility of diﬀerent commercial zones.The evolution of an open source cartographic network, such as the Open StreetMap, has been proposed by Corcorain et al. They measure for the ﬁrst time thetopology of a top-down cartographic network, revealing how people map an areaand how top-down maps evolve in time. They found that diﬀerent cases share thesame growing processes and therefore that mapping might be governed by universalroles. Their results are indeed linked to the perception of space and navigationstrategies in a network-like environment. The reader might link to the navigabilityindices proposed by Lee et al. for evaluating the local performance of spatial net-works; among diﬀerent interesting ﬁndings, remarkably they show that an optimalpedestrian street network should be similar to a triangular grid, such as the streetnetwork pattern we are ﬁnding in most of the historical centres.Transportation may not simply refer to people: in modern society communica-tion networks are essential due to their large impact on the economy and on ourway of life. Chen et al. propose a model for explaining the structure (including thespatial structure) of access nodes within the Internet infrastructure.We would love to send a copy of this issue to Ibrahim Al-Istakhri for his commentsand to illustrate to him how much development networks have progressed since his pi-oneering eﬀorts. The study of complex networks has moved from qualitative analysisto a quantitative science, in which models and measures are used to explain not-so-trivial facts hidden within the structural patterns of connectivity. Despite many ofthe advances seen today, there is still room for the development of new qualitativeand quantitative tools for analysing complex transportation networks in a way thatmore extensive and reliable information is extracted from them.We are extremely grateful to the European Physical Journal Special Topics for having hostedthis issue and in particular to Christian Caron and Sabine Lehr. We furthermore expressour sincere gratitude to the authors of the diﬀerent manuscripts, and to all of our colleagueswho have assisted us in the reviewing process and preparation of this special issue. EmanueleStrano is particularly grateful to Franc¸ois Golay, Marc Barthe`lemy and Sergio Porta for theirconstant support, to Andrea Perna, Gianluca Oppo and Paola Pasino for their help in theorganisation of the workshop Evolution of Complex Transportation Networks, and LuigiFarrauto for providing the map of Greater Khorasan.

Spatially embedded socio-technical complex networks

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Spatially embedded socio-technical complex networks

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