Projects | Call for proposals | 2027-30 ENTAILab

ENTAILab 2027-2030

Subject to further funding, SPP’s projects are supported and accompanied by a set of three unique research infrastructure services and measures developed and provided by the SPP’s Research Infrastructure and Innovation Lab (ENTAILab). ENTAILab measures offer outstanding opportunities for research on data collection, data processing and data analytics, while disseminating SPP project results to existing panel studies and other research and data provision programmes. As such, ENTAILab also provides the framework to enable the reuse, interoperability, and secure deployment of methods within and across SPP projects.

Applicants are strongly encouraged to consult the ENTAILab Measures early to ensure their proposals align with best practices and requirements related to data quality, data protection and ethics, and the use of existing technological infrastructure.

Measure 1: Build on and Develop Existing Panel Studies

Measure 1 provides methodological consulting on the evaluation of measurement quality and the assessment of selectivity, as well as on the appropriate application of statistical methods to address both issues. These services are available at the proposal stage and throughout ongoing projects. In addition, the lab synthesizes methodological insights across the four research areas, with a particular focus on multimode data acquisition and instrument validity. 

The resulting meta-level knowledge is used to inform and advance the design and implementation of large-scale social surveys.

Contact Measure 1 for more information and consultation related to questionnaire design and connection to important third parties. This includes, for example, establishing contact with existing panel surveys that offer questionnaire modules for projects or with survey research institutes.

Measure 2 – Research-Driven Infrastructure for Advanced Survey-Related Data (CIRCLET)

Measure 2 offers a range of innovative data analytics, machine learning and AI methods for generating and processing survey-relevant data. It offers the option to integrate these methods into project-specific processing chains. These pipelines and their constituent methods can be exchanged between SPP projects and reused as required. Measure 2 specifically supports this kind of reuse and interoperability. It relates this procedural innovation to two key enhancements. Firstly, it improves the integration of multimodal data. For example, it offers a platform for collecting interactive data in VR and its database-driven processing. Secondly, Measure 2 extends its pipelining mechanism to machine learning model training, making these models flexible, modularized, standardized and interchangeable between projects. Lastly, Measure 2 develops a web interface for its purposes, eliminating the need for complicated interface operations.

Measure 2 provides a technological framework that enables the reuse, interoperability, and secure deployment of computational methods within and across SPP projects. Its functionality includes (1) mechanisms for transferring models between projects without exposing sensitive data, (2) workflow orchestration tools for multi-stage pipelines in which specific components can run in secure computing environments, and (3) modular interfaces that allow models to be substituted or combined at any stage of a pipeline. ENTAILab's framework is designed to support SPP projects in incorporating these capabilities into their research workflows. By standardizing model exchange, secure execution, and workflow modularity, ENTAILab contributes to reproducible, comparable, and methodologically integrated research across the SPP.

Contact Measure 2 for more information about CIRCLET.

Measure 3: Data Protection and Ethics

Data protection and data ethics issues can create barriers and challenges for projects within the SPP 2431, which must balance data protection regulation and ethical standards with the demands of innovative research designs. AI methods raise particular questions about the explainability and reconstructability of training data and test results, which may themselves serve as input for further analysis. Measure 3 of ENTAILab supports SPP 2431 projects through workshops and individual counseling on issues related to data acquisition, data handling, data anonymization algorithmic data analysis, and data storage.

Beyond direct project support, Measure 3 functions as a laboratory for exploring emerging data protection and data ethics issues, testing new ethical standards and data protection procedures, and developing guidelines for future research. Through networking with international and national researchers, organizations, and associations, Measure 3 disseminates the ideas, solutions, and guidelines developed within the SPP 2431 to key organizations positioned to advance ethical issues in the social sciences, particularly the German Data Forum (RatSWD) and the German National Research Data Infrastructure (NFDI).

Contact Measure 3 for more information and consultation related to data protection and ethics considerations.