A Joint Infrastructure for Dynamic Relational Multilevel Data
While there is considerable progress in making data accessible through national and international data archives, expert knowledge on the content and scope of these databases, and their potential use for solving specific research problems, unfortunately, have remained fragmented across disciplines. Seemingly incompatible data structures are a further obstacle to interdisciplinary progress, as is the paucity of cross-study meta-analytic research designs. The consortium’s state-of-the-art research projects require rich multilevel, dynamic and relational data, thus, one of SCOOP’s missions is to maximally exploit this unused potential for synergies. A cross-disciplinary interface with both secondary and newly collected primary data is, therefore, one of the main deliverables of this Gravitation program. The innovative SCOOP Lab pioneers the systematic collection and linking of four different categories of data sources: experimental, historical, cross-national comparative, and panel surveys, including longitudinal social networks studies.