Ex post survey harmonization is in a way a passive form of pooling research funding because you can utilize information from surveying that were made on somebody else’s expense. The aim of ex ante survey harmonization is to maximize the value from future retrospective harmonization; in a way, it is an active form of pooling research funding, because you benefit from money spent on related open governmental and open science survey programs.
We created a longitudinal dataset that contains data on the attitudes European people in various countries, provinces and regions thought climate change was a serious world problem back in 2013, 2015, 2017 and 2019. We join the data with air pollution data so that we can see how serious is the environmental degradation in the smaller area of each (anonymous) respondent.
Retrospective survey harmonization allows the comparison of opinion poll data conducted in different countries or time. In this example we are working with data from surveys that were ex ante harmonized to a certain degree – in our tutorials we are choosing questions that were asked in the same way in many natural languages. For example, you can compare what percentage of the European people in various countries, provinces and regions thought climate change was a serious world problem back in 2013, 2015, 2017 and 2019.
In our [tutorial series](http://netzero.dataobservatory.eu/post/2021-03-04_retroharmonize_intro/), we are going to harmonize the following questionnaire items from five Eurobarometer harmonized survey files. The Eurobarometer survey files are harmonized across countries, but they are only partially harmonized in time.