World Values Survey

Since 2015, the Institute for Comparative Survey Research is hosting the Secretariat of the World Values ​​Study Association - the largest social science research program and the largest academic survey infrastructure in the world (

The World Values ​​Survey (WVS) is a global comparative study of the values, attitudes and beliefs of people around the world. The project covers over 120 countries on all continents. Started in 1981 and until recently based at the University of Michigan in the US, in 2015 the secretariat of the WVS, the central body for the research development and administration of the project, was relocated to Vienna, Austria.

The director of the institute, Prof. Dr. Christian W. Haerpfer, is the President of the World Values ​​Survey Association since 2013 (re-elected for 2022-2028). ICSR-EAB's Senior Research Fellow, Dr Kseniya Kizilova is the Head of the Secretariat of the WVSA and responsible for the day-to-day coordination in the project. The World Values ​​Survey is repeated every 5 years; Most recently, the 7th wave of the WVS took place in the period 2017-2022 under the direction of the Institute. Over 150,000 respondents from nearly 90 countries were surveyed, with the data freely available to anyone and anyone interested via the WVS project website:

The World Values ​​Study Association is an international organization with a complex structure. The legal seat of the association is in Stockholm, Sweden; the Office and Secretariat of the President, responsible for coordinating administrative, financial and research activities, are located in Vienna, Austria; the data archive responsible for cleaning up the survey data and making the data available to the public at large is based in Madrid, Spain. WVSA also has regional offices in Latin America, Eastern, Southern and Northern Europe.

World Values Survey data can be accessed freely for non-commercial purposes such as research, policy-oriented and academic publications, teaching, conference presentations and similar.

Online Data analysis