Data transitions have revolutionized many scientific disciplines, starting with the exact sciences, then the life sciences,
and now the social sciences and humanities are in the process of making the transition to becoming data intensive sciences,
with descriptions through quantitative measurements. New analysis tools and publicly accessible utterances, opinions, transactions
and interactions resulting from widespread internet and social media usage facilitate new, data-intensive research methods
in disciplines that have so far relied on small-scale literature and/or panel-based studies. To illustrate the new possibilities,
we report on a pilot carried out by a cross-disciplinary team consisting of computer scientists and researchers in religious
studies. In the latter area, research is often focused on mapping out the convictions, hopes, and beliefs of groups of people,
be it within certain religions or within any other group, such as those defined by a political party.
In the pilot, religious
scholars examined the core keywords in a left-wing political party in order to determine their hopes and beliefs. Rather than
following their standard way-of- working, they were equipped with a search engine with an index of content crawled from discussion
forums, the party’s web site plus a range of online publications relating to the party and going back to 1990. In this paper
we focus on lessons learned and on methodological innovations for religious scholars as well as for computer scientists building
the enabling technology.