CSDA Research - Výzkumný program Českého sociálněvědního datového archivu: Česká republika v Mezinárodním programu sociálních šetření ISSP, výzkum kvality dat a zdrojů dat

The project implements a research programme of the Czech Social Science Data Archive (CSDA). CSDA is a national research infrastructure providing data services for social research and higher education. It acquires, processes and preserves datasets and makes them available for secondary analysis. The archive also contextualizes data and links them with other relevant information. In addition, CSDA serves as the Czech national node of the large-scale pan-European distributed research infrastructure CESSDA. 
The principal activities of the proposed programme are following: (1) implementation of three Czech surveys of the International Social Survey Programme (ISSP), (2) methodology research on measurement tools, (3) mapping and analysis of data sources. ISSP is a long-term international programme of comparative surveys on important sociological topics. The project will implement three consecutive ISSP surveys in the Czech Republic: ISSP 2017 on Social Networks, ISSP 2018 on Religion, and ISSP 2019 on Social Inequality. At the same time, the team will focus on the study of (a) social networks, (b) religiosity, moral values, moral behaviour, and the role of religion in political attitudes, and (c) social inequalities and poverty. The project will also analyse the validity and equivalence of selected measurement tools in Czech surveys and adapt selected international tools for use in the Czech context. In addition, the project will  identify, describe and conduct the meta-analysis of empirical social science surveys undertaken prior to the mid-1990s.
The project will result in a number of scientific publications addressing important research questions.  At the same time, it will create the prerequisites for the fulfilment of the CSDA’s mission in the following areas: (1) facilitating Czech participation in international research programmes, (2) providing methodological resources and expertise on data sources, and (3) acquiring, archiving and providing access to datasets.