European Survey of Information Society


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During the last few months the European Survey of Information Society has undergone many changes. Firstly, an update of ESIS I, covering the 15 member states of the EU, has begun.

Secondly, ESIS II, covering central and eastern Europe and the Mediterranean area, has been updated.

Thirdly, the ESIS Knowledge Base is now on-line.

This information source is therefore an essential guide for all persons concerned with the development of IS in the EU, CEEC and Mediterranean regions.

Furthermore, ESIS can play a role in the preparations of the EU and the CEEC for forthcoming enlargement by collecting basic data on the Information Society and helping develop a better understanding of the 'acquis communautaire' in the CEEC.

The ESIS inventory of IS projects conducted in the EU Member-States in 1997-1998 has been a key resource enabling users to monitor the progress of the Information Society in the European Union.

The European Commission has decided to launch an update campaign of the data held on ESIS projects, so that the database will remain one of the most comprehensive and up-to-date information sources on European Information Society projects.

The update will focus on IS projects, key persons and organisations and Basic Facts and Indicators as well as a survey of IS national strategies.

The updates will be made on-line by those responsible for each individual project. Furthermore, all the key features of ESIS 1 (as of January 1999) will remain available via the search engine as well.

The database of IS projects, promotional actions and key persons and organisations and the reports on regulatory developments, alternative networks, promotion activities, key persons and organisations and WWW indicators for the CEEC and the Mediterranean area have been updated and are now on-line.

The database now contains 377 IS projects, 594 promotional actions, 2122 key person contacts and 1985 organisations.


Cibercentro for Employment in Metropolitan Bilbao: A Successful Initiative to Broaden the Social Use of the Internet


Network science
Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology. The United States National Research Council defines network science as "the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena.
Probabilistic theory in network science developed as an offshoot of graph theory with Paul Erdos and Alfred Renyi's eight famous papers on random graphs. For social networks the exponential random graph model or p* is a notational framework used to represent the probability space of a tie occurring in a social network. An alternate approach to network probability structures is the network probability matrix, which models the probability of edges occurring in a network, based on the historic presence or absence of the edge in a sample of networks.
In 1998, David Krackhardt and Kathleen Carley introduced the idea of a meta-network with the PCANS Model. They suggest that "all organizations are structured along these three domains, Individuals, Tasks, and Resources". Their paper introduced the concept that networks occur across multiple domains and that they are interrelated. This field has grown into another sub-discipline of network science called dynamic network analysis.
More recently other network science efforts have focused on mathematically describing different network topologies. Duncan Watts reconciled empirical data on networks with mathematical representation, describing the small-world network. Albert-Laszlo Barabasi and Reka Albert developed the scale-free network which is a loosely defined network topology that contains hub vertices with many connections, that grow in a way to maintain a constant ratio in the number of the connections versus all other nodes. Although many networks, such as the internet, appear to maintain this aspect, other networks have long tailed distributions of nodes that only approximate scale free ratios.
In 2009, the U.S. Army formed the Network Science CTA, a collaborative research alliance among the Army Research Laboratory, CERDEC, and a consortium of about 30 industrial R&D labs and universities in the U.S. The goal of the alliance is to develop a deep understanding of the underlying commonalities among intertwined social/cognitive, information, and communications networks, and as a result improve our ability to analyze, predict, design, and influence complex systems interweaving many kinds of networks.