Programme Overview

New Data Spaces aims to open up new avenues for the social sciences

by building on the strengths of existing panel studies, by innovating new methods and procedures, and by complementing them with the intelligent integration of data derived through new technologies.

Our society faces a number of major social challenges in the coming decades. To expand and enrich our understanding of these challenges and the processes that underlie them, the social sciences need to go beyond the current data sources and methods and unlock emerging opportunities in new data spaces. Social science research needs to exploit the potential of new forms of data from administrative processes, data analytics and machine learning, digital communications and mobility, and other sources. It also needs new forms of data acquisition (such as virtual interviews, bots and augmented reality) alongside the ongoing development and expansion of well-established longitudinal survey programmes. These new data forms and data linkages must be initiated, developed and subjected to rigorous quality testing.

The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) founded the Infrastructure Priority Programme “New Data Spaces for the Social Sciences” (SPP 2431) in December 2022 as a long-term funding scheme.

Whereas a regular DFG-Priority programme (SPP) is for up to 6 years (consisting of two 3-year phases) the New Data Spaces programme may be funded for longer than six years, depending on the success of the overall programme.

The New Data Spaces programme objectives are:

Develop best-practice examples of data generation, data collection and data integration to enhance data quality.
Anchor innovations in existing panel studies, new data collection programmes and data analytic approaches.

For each funding phase the programme will invite project proposals in and across four main research areas that together aim to achieve the programme objectives.

Research Area 1: Data exploration and integration

Aims to enhance survey data through different means of data linkage. It brings together projects that analyse how to explore, curate, prepare and integrate different types of data, including ethical and methodological questions of data usage and the linkage of data from different sources.

Research Area 2: Respondent driven designs

Relates to the conception and design of studies. Projects in this area develop and test survey designs that are tailored to the needs of different respondent groups and tackle questions of sampling frames.

Research Area 3: Instrument validity

Targets projects dealing with questions of new construct measurement, data quality and instrument validity, in particular with regard to AI methods and unstructured data.

Research Area 4: Multi-modal data acquisition

Devoted to new means, methods and modes of data acquisition that make use of machine learning or data analytics in general, or AI, text mining and multimodal data mining in particular, or that utilizes technical innovations in surveying and ambulatory assessments.

2024-2027 Cohort

The first cohort of fifteen New Data Spaces projects was funded in 2024. All New Data Spaces projects are supported and accompanied by a set of unique measures developed and provided by a newly established Research Infrastructure and Innovation Lab (ENTAILab). In addition to providing infrastructural services, consultation, and supports to projects, ENTAILab also offers outstanding opportunities for research on data collection, processing and analytics, and using existing panel studies.