Co-link analysis, innovation networks and scale-independence

Web indicators to reflect the university-government-industry structure for major EU universities

Objectives

This project consists of two parts:

1. Develop co-links indicators to explore the evolving actual and perceived relationships between university, industry and government, the co-evolution of science, technology and innovation and the similarity and differences of R&D institutions as seen from the world wide web (virtual space).
2. Develop and analyse scale-independent indicators to accurately portray the self-similar nature of the science, technology and innovation systems in virtual space.

Description of work/methodology

Co-link analysis:

A frequently occurring co-link suggests that a particular group, the linking community, perceives a relationship between two organisations. We will focus our attention strictly on co-links with major European University web sites. Co-link data will be collected using major EU Universities as the starting point (i.e. top 10% of universities by size in each nation). We anticipate that this will produce a data set of well over one million co-links to be analysed. For each major EU University the co-link data set will be prepared using the following steps: Links outside of the University's web domain to pages in the University's web domain will be collected using the major search engines (e.g. Google, AllTheWeb (Fast) and AltaVista). Programs or scripts written in PERL or PYTHON will be developed to facilitate collecting the primary links from the search engines and extracting the co-links from the primary web pages. Sectoral and geographical indicators will show the organisation of European, national, and regional systems of innovation in the Web representation.

Scale-independent indicators:

Scale-independence refers to the property of self-similarity in systems. One hypothesis is that many of the indicators that are currently used either over or underestimate attributes of individual systems. The question that will be addressed is can scale-independent indicators be developed to accurately portray the self-similar nature of the science, technology and innovation systems in virtual space? First a document will be prepared that discusses the theory, implications and design of scale-independent indicators. It will provide a review of the literature that explores the general scale-independent nature of the web structure and processes. And second, data from the co-link analysis and other sources such as the EICSTES project will be used to develop scale-independent indicators that characterise the self-similar activities and nature of the EU science, technology and innovation community on the web.