The research network will systematically focus on three aspects of the data linkage process: (1) different types of linkage designs and levels of aggregation (e.g., individual, spatial, temporal, party); (2) the linkage process itself and the mitigation of potential biases (e.g., dropout of units, approximate matching when no clear identifiers are available); (3) methods for the analysis of linked data (e.g., panel analysis, causal inference, media-content analysis).
 
Many political science research questions can only be answered by linking different data sources with one another in order to measure certain mechanisms more precisely and/or to improve causal inference. Classic examples include questions concerning representation, for which researchers match data on party positions (e.g., Chapel Hill Expert Survey), candidate’s policy preferences (e.g., candidate surveys), or legislative behaviour (e.g., parliamentary databases) with data on public opinion (e.g., European Social Survey) or specifically on voter preferences (e.g., European Election Study). Elite attitudes and behaviour can nowadays also be measured more dynamically with social media data; and, if linked to data on digital media consumption and behaviour among citizens and voters, they provide opportunities to study different forms of communication between representatives and their represented. Likewise, classic media and campaigning effects on voter preferences and behaviour can be studied by linking content analysis data via voters’ exposure measures collected by survey data, data donations, or online tracking data. Other questions may concern the role of external and/or contextual factors, such as the impact of weather conditions (meteorological data), natural disasters (e.g., seismological data), generational patterns (historical sociological data), or public administration (administrative or census data) on voter behaviour, which would also require geodata. Finally, addressing data linkage in political science research is timely and urgent given accelerating developments concerning Open Science, Big Data, open-source initiatives, and Artificial Intelligence.
 
As the research network’s main focus lies on theory-driven methods that link different data sources to analyse the interaction between elite and mass positions in various contexts and with regards to different research questions, it explicitly cross-cutting existing standing groups. Thereby, it seeks to connect researchers from different sub-disciplines of political science to showcase, critically discuss and advance different forms and purposes of data linkage in political science research.