Abstract

Despite its long existence and international acceptance, network theory and analysis is a practically unknown approach in Documentation, both theoretically and methodologically speaking. Fortunately, this trend is changing, inasmuch as network theory and analysis may mean a quantitative and qualitative leap forward in the representation and analysis of the structure of all types of scientific domains, whether geographic, thematic or institutional. The extraordinary advances that have taken place in recent years in the study and analysis of complex networks have been made possible by a number of parallel developments. First of all, with computerized data acquisition and handling, large databases can be managed, leading to the emergence of different real network topologies. Secondly, the increase in computing power has made it possible to explore networks with millions of nodes. Thirdly, there is the slow but sure breakdown of boundaries between disciplines. This can be seen by researchers because of their ability to access and use databases that facilitate an understanding of the generic properties of complex networks.

Abstract

Actualmente los grandes experimentos científicos necesitan una gran organización en la que participan cientos de investigadores de varias instituciones. Un aspecto interesante, aunque poco estudiado, de este nuevo tipo de iniciativas científicas es la forma que toma la colaboración interna entre los miembros de las instituciones participantes. En este trabajo se investiga este tema en uno de los ejemplos más conocidos de big science: el experimento ATLAS del CERN. Mediante la aplicación de varias técnicas de análisis de redes a información proveniente de bases de datos internas del CERN, se identifican varios patrones de colaboración dentro del experimento. Se comprueba, por una parte, el alto nivel de colaboración entre las instituciones representadas en ATLAS, superior al observado usualmente en el campo de la física, y se identifican los actores principales en la red de colaboración. Por otra parte, se observa que la red de colaboración no sigue un patrón “libre de escala” o de “ley de potencia”, al contrario de lo que ocurre en otras redes de colaboración estudiadas en física y en otros campos. Finalmente, se advierte que la distancia geográfica entre dos instituciones no parece tener ningún efecto en la probabilidad de establecer relaciones de colaboración, contrastando también con lo que ocurre en otros tipos de redes de colaboración.AbstractNowadays big scientific experiments require large organizations and hundreds of researchers who participate from several institutions. An interesting, yet rarely studied aspect of this new kind of scientific enterprise is the internal collaboration between the members of the participating institutions. Here we assess this matter in one of the most well-known examples of big science: the ATLAS experiment at CERN. Applying different network analysis techniques to data from internal CERN databases, we have identified several collaboration patterns in the experiment. We observe, on the one hand, the high level of collaboration between the institutions represented in, higher than the average in the field of physics, and we identify the key institutions in the collaboration network. On the other hand, we notice that the collaboration network does not follow a scale-free or power-law model, contrary to what happens in other studied collaboration networks in physics and other areas. Finally, we observe that geographic distance between two institutions does not seem to affect the probability of establishing collaboration relationships, in contrast also to what happens in other kinds of collaboration networks.