Data and Methods

In order to answer these questions, we have analyzed social processes in the cluster, using a mix of both,standardized, quantitative and open, qualitative methods of social research. The aim of qualitative forms of data collection is to explore new kinds of thought, routines and so on. The advantages of standardized methods are the comparability of answers and the possibility to represent wider spans of persons. The mixedmethodsdesign used combines both forms of data collection for a reciprocal correction, extension and validation
of the findings.

Qualitative interviews leave natural scientists interviewed
the possibility to answer the questions beyond given categories. Up to this point, we have conducted more than 40 interviews with scientists involved in different parts within UniCat, as well as a control group outside the cluster in comparison. For monitoring the social processes of the emerging cluster, it is necessary to regularly repeat data collection over time. This is the only possibility to inquire the consequences of UniCat concerning the cooperation between scientists or the production of scientific knowledge. The first Online-Survey with the title ANU (Analysing Networks in UniCat) took place in summer 2010 with an extraordinarily high response rate of 75%. We hope that we will be able to replicate this rate in future studies, as advanced methods of data analysis require high response rates and because missing data generate a strong bias in the interpretation of network-pictures and statistical parameters.

The conception and analysis of the survey is shaped by a network-perspective on social processes. Network Analysis therefore models the web of relations within the research projects only for a specific type of relation. An example for a network of reciprocal awareness of the scientists is shown in Figure 1. Similar to the interviews, a regular repetition of data collection is necessary for an appropriate interpretation of the consequences of UniCat.