Networks over space and time: modelling, analyzing, and representing complex data in the digital humanities 8 November 2013 Lisboa, Portugal

In the humanities, a close look at networks and relationships, whether formal or informal, personal or social, of information or of knowledge, of transportation or of communication, has always been an important subject of study and, at the same time, a powerful analytical process. In computer science, the study of networks and of methodologies for analysis and visualization of these relationships is nowadays anincreasingly well understood and practiced area of knowledge. In both the humanities and computer science, researchers are well aware of the dynamic nature of data and knowledge when viewed through the lenses of space and time.Networks can be studied in a purely spatial perspective, if the object of analysis is the distance between things or people. However, there are two other dimensions which render networks’ study in a more complex and richer methodology. Either time or social relationships help to extend the focus of analysis from distance to connectivity, and this is an important concept for the Humanities.

When put together, time, spatial analysis, with its derivative, spatial network analysis, and social network analysis, can be a powerful way of thinking about the world (theory) and of explaining it (methodology). And at the present time, with the integration and plasticity of the digital, the rising awareness about geography and time trough the Internet’s social networks, and the growing usability of the Web 2.0,thinking and explaining networks can benefit from powerful tools, increasingly complex and accessible at the same time. The aim of this workshop was to combine analytical perspectives in the study of networks, over space and time, in humanities disciplines and on various themes, to identify methodologies, discuss research results, and encourage interdisciplinary approaches. The main focus of the workshop was on the areas of modelling and representation, highlighting them more as methods of analysis and knowledge production than merely as tools.

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