Berlin: A Quantitative View of the Structure of Institutional Scientific Collaborations

TL;DR

This study analyzes the structure of scientific collaborations in Berlin using a large dataset, revealing regional and disciplinary patterns, with a focus on the role of the Berlin University Alliance and methodological insights into organization disambiguation.

Contribution

It provides a comprehensive quantitative analysis of Berlin's scientific collaboration network and evaluates organization disambiguation techniques, highlighting sectoral and regional collaboration patterns.

Findings

BUA members influence regional collaboration structures

Cohesive intraregional collaboration exists mainly in Medical and Health Sciences

Disciplinary divides are prominent in Agriculture and Humanities

Abstract

This paper examines the structure of scientific collaborations in a large European metropolitan area. It aims to identify strategic coalitions among organizations in Berlin as a specific case with high institutional and sectoral diversity. By adopting a global, regional and organization based approach we provide a quantitative, exploratory and macro view of this diversity. We use publications data with at least one organization located in Berlin from 1996-2017. We further investigate four members of the Berlin University Alliance (BUA) through their self-represented research profiles comparing it with empirical results of OECD disciplines. Using a bipartite network modeling framework, we are able to move beyond the uncontested trend towards team science and increasing internationalization. Our results show that BUA members shape the structure of scientific collaborations in the region. However, they are not collaborating cohesively in all disciplines. Larger divides exist in some disciplines e.g., Agricultural Sciences and Humanities. Only Medical and Health Sciences have cohesive intraregional collaborations which signals the success of regional cooperation established in 2003. We explain possible underlying factors shaping the observed trends and sectoral and intra-regional groupings. A major methodological contribution of this paper is evaluating coverage and accuracy of different organization name disambiguation techniques.