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Research Infrastructure and Innovation Lab (ENTAILab)
ENTAILab Documentation - Hub
The Research Infrastructure and Innovation Lab (ENTAILab) is dedicated to the use of existing research infrastructures, their advancement and the demand-oriented generation of a new research infrastructure for the needs of the InfPP projects and the development of new data spaces. ENTAILab aims to create a unique infrastructure for research-based innovations in the field of survey data and beyond.
ENTAILab consists of a set of four infrastructure measures that provide a successful and supportive environment for research within and across the projects of InfPP. Together, they will systematically feed results back into different kinds of panel applications and studies and social science research in general.
Measures
Measure 1
Build on and Develop Existing Panel Studies
The InfPP initiative aims to expand data access for social science research by utilizing existing large-scale surveys and infrastructures such as the SOEP Innovation Panel, the GESIS Panel, the GESIS Access Panel for digital behavioural data, and the NEPS Next cohorts. These platforms enable innovative surveys and experiments, including the selection of special-interest groups, linking different data forms, and incorporating technical innovations such as app-based surveys and API data collection. Additionally, joint surveys and pilot studies can be developed based on research needs and target populations.
Measure 2Research-Driven Infrastructure for Advanced Survey-Related Data (CIRCLET)
ENTAILab involves the implementation, testing and provision of a strong research-oriented tool in the form of a research-driven infrastructure for advanced survey-related data (CIRCLET). CIRCLET will ensure the reproducibility and interoperability of methods working with survey data. This is done through a multi-phase strategy that drives, scales and evaluates the development of methods based on new survey data over the course of InfPP. CIRCLET develops, tests and provides generic services to open up new data and methodological horizons according to the evolving needs of InfPP.
Measure 3Data Protection and Ethics
Data protection and data ethics are crucial boundaries for research projects using survey data, Big Data, AI, and register data, which cut across all four research areas of the InfPP. Projects often face the challenge of balancing the requirements of data protection regulation with demands of specific research designs, while meeting ethical standards of research. Projects must clarify which data should be analysed and which data processes are planned without jeopardizing information privacy.
Measure 4Results for Future Data Spaces and Open Science
The New Data Spaces programme aims to produce new data, to generate knowledge and results on data, designs and instruments, and to provide tools, methods and guidelines that will benefit and systematically feed into large-scale panel studies, linked data, as well as smaller-scale data generation projects and applications. Thus, the programme is not limited to large-scale survey and panel studies, but will address future social science research as a whole.
Principal Investigators
- Prof. Dr. Cordula Artelt
- Prof. Dr. Corinna Kleinert
- Prof. Dr. Stefan Liebig
- Prof. Dr. Alexander Mehler
- Prof. Dr. Reinhard Pollak
- Prof. Dr. Sabine Zinn
