1. A Question Database for the German Longitudinal Election Study
Wolfgang Zenk-Möltgen
GESIS – Leibniz Institute for the Social Sciences
IASSIST 2014 – Aligning data and research infrastructure
Ryerson University, Toronto, Canada
June 3-6, 2014

2. Outline German Longitudinal Election Study (GLES)
GLES Question Database
Inside GLES Question Database
Future Work

3. German Longitudinal Election Study
National Election Study to enable analyses of changes of voters and voting behavior in longitudinal comparison
Conducted by 5 principle investigators together with GESIS and the German Society for Electoral Studies (DGfW)
Data collection in cross-section, short- and long-term longitudinal surveys
Candidate survey, analysis of TV debates, and content analysis of media
Using mixed methods like face to face, CATI, or web-survey
9 components connected by a core questionnaire
Funded by DFG for 2009, 2013 und 2017 national elections
Intended to be the basis of a long-running research programme
GESIS works on data documentation and distribution, provides advice to users, makes data freely available, and archives it

4. GLES Components Pre-election and Post-election Cross-Section (CAPI)
Rolling Cross-Section Campaign Survey (CATI 100 respondents per day)
Short-term Campaign Panel (online)
Campaign Media Content Analysis (online, 7 waves)
TV Debate Analysis (experiment, 4 waves)
Candidate Campaign Survey (Interviews with candidates, print and online)
Long-term Panel (CAPI and mixed mode)
Long-term Online Tracking (online, 4 waves per year)
Long-term Media Agenda Analysis (content analysis of TV news and newspapers)
Pre-election Online Tracking (separately funded)
Multi Level Panel (EU and state elections - separately funded)

5. GLES Components
Source:

6. GLES Question Database
Existing internal GLES database
Manage questions over different instruments: modes and points in time
Find differences in wording or answer categories
See questions related to specific concepts
Quickly access study level documentation

7. Question Search

8. Question Results

9. Questions with answer categories

10. Use facets to limit search results

11. Compare questions (or studies)

12. Question comparison

13. Study Search

14. Study search results

15. Select to compare

16. Compare studies

17. Open in Data Catalogue

18. Inside GLES QD DDI-L data model: STARDAT architecture
Import studies from data catalogue DBK in DDI-L format
Import questions from legacy database in Excel format

19. Manage Metadata

20. Import studies from DBK DDI-L

21. Import mapping from XLS

22. Import questions from XLS

23. Export DDI-L (study, …

24. … methodology, …

25. … and variables)

26. Future Work Improve Usability Apply GLES case to other collections
Expand functionality
Develop the STARDAT case
Editing options
Dataset documentation
Report generation

27. Acknowledgements to the project members:
Thank you!
Acknowledgements to the project members:
Monika Linne, Philipp Schaer, Daniel Hienert, Claus-Peter Klas Johann Schaible, Alexander Mühlbauer