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Data and Methodology Center

SCRIPTS is a research consortium that builds on the systematic collaboration of scholars from disciplines across the social sciences, area studies, and humanities. This methodological pluralism and critical reflection about data and methods is one of the features, and strengths, of SCRIPTS.


The Data and Methodology Center (DMC) contributes to a fruitful collaboration of scholars from a wide variety of disciplines, research traditions, and contexts. Its objective is to ensure and raise the standards of research by:

  1. consulting on training and research projects;
  2. offering a forum for critical reflection about the concepts, ethics and methods underlying data collection as well as analysis;
  3. discussing methodological innovations, especially those that connect quantitative and qualitative data;
  4. assisting with data management and data accessibility;
  5. establishing a central location making the collected data available to other scholars (data archive and services) and thus contributing to a growing infrastructure of accessible social science data.

We are currently in a process of evaluating the DMCs activities. These critical reflections might lead to adaptions or addition to the center’s agenda and activities. This page will be updated accordingly in due time.

Research Consulting

Research consulting is organized both at the individual level through individual research consultations and at a more general level through providing workshops and colloquia for scholars from SCRIPTS and partner institutions.

Data Science Training

In addition to several smaller events and endeavors, the Data Science Summer School 2021 was organized by the SCRIPTS Data and Methodology Center in cooperation with the Hertie School Data Science Lab and with support from the Stifterverband. It took place 09 July to 30 July 2021 and consisted of a series of 4-hour workshops on programming and data analysis for research. Courses included an introduction to R programming, to Python programming, to Machine Learning and to Deep Learning, as well as Web Scraping, quantitative text analysis with R, Natural Language Processing and Data Visualization. The recordings of all sessions and additional material can be permanently retrieved at the Data Science Summer School website.


Philip Warncke 
Academic Coordinator of the Data and Methodology Center