Macroscope

Fri, 14 Aug 2026 00:00:00 +0000

In this project we will construct a population level Macroscope, building on existing infrastructures and services from ODISSEI and CLARIAH to deliver unique opportunities for Social Science and Humanities scholars. A Macroscope is an instrument for the holistic study of complex social dynamics and the Dutch Macroscope will consist of four complementary and mutually reinforcing layers that support different phases of the research lifecycle in the Social Sciences and Humanities (SSH). First, the Macroscope Core will adapt foundational infrastructures to accommodate the complex, sensitive, and highly interrelated data found across the SSH domain. Second, the Data Harvesting Ecosystem will enable unprecedented levels of data variety. Through integrated data systems, new technologies, and intensive collaboration, it will be possible to collect diachronic, dynamic, population scale, network data on a plethora of social issues. Third, the AI Collaboratory will provide a community-oriented platform for the training and evaluation of complex models and tools including a next generation of secure Large Language Models with a vast array of applications for research. Fourth, the Macroscope Gateway will enable scholars from across the domain and beyond to utilise the Macroscope. Once completed in 2030, SSH researchers will be able to securely bring together an unprecedented range of data, tools, and computational resources to answer societal questions that cannot be addressed presently and conduct groundbreaking multi-disciplinary research into multi-scale, complex social dynamics such as how the Dutch language is evolving in a multimedia world or how demographic change is shifting the social fabric of the Netherlands.

Within the Macrosccope, I will lead the work on the Data collection task. We will concentrate on implementing innovations in long-running data collections and usher in a new era for large-scale social science data collection. It will help researchers, policy makers and the general public to understand how the Netherlands is changing in the short and long term, whilst cementing the Netherlands’ position as a global leader in social science digital technologies. The Netherlands has a central position in the European social science research landscape; the data collection task will put the Netherlands at the forefront of innovations in comparative European data collections. It will include the European Social Survey (ESS), European Values Study (EVS), World Values Survey (WVS), Dutch Parliamentary Election Study (NKO), Survey of Health, Ageing and Retirement in Europe (SHARE), the International Social Survey Programme (ISSP) and the Gender and Generations Programme (GGP). It consists of the following subtasks:

\USubtask 1: Integrating new technologies in large-scale data collection\u Recent changes in the legislative framework for the processing of personal data, including the GDPR, the Data Governance Act, the AI act, and the Data Services Act, create an unprecedented opportunity for securely and safely collecting and linking high-resolution new data types on a plethora of social phenomena. These new streams of data have the potential to revolutionize our understanding of social processes. Work in subtask 1 builds on the Netherlands’ world-leading existing infrastructure for data collections, and enhances it through technological innovations in the sphere of big data. It connects international survey research projects to each other, and develops and implements new technologies that serve the broader social science community in the Netherlands. Subtask 1 integrates and upgrades these new technologies to answer pressing social science questions that increasingly center on how people shape, interact and are affected by technologies and the digital world. In this subtask, innovations and methods stemming from the “Media and Web Data task” will be implemented in large scale surveys. As an example, within the NKO, digital behavioral data on news consumption and social media profiles will be collected for respondents, allowing the study of filter bubbles, algorithms, and effects on political attitudes and behavior. Similarly, in SHARE & GGP, we will link to biomedical data linked to fertility and healthy aging for respondents. Budget is available to fund extra costs associated with the collection of new data, analyzing how successful the innovative technologies are integrated within the data collection in terms of measurement (what do we measure) and representation (who do we measure), and ensuring that the new data are disseminated in a FAIR way, while ensuring participant’ privacy.

\USubtask 2: Hard-to-reach groups\u Subtask 2 concentrates on the inclusion of hard-to-reach societal groups in studies. A core goal of the social sciences is to study subgroups within the population that are underrepresented, marginalized or difficult to reach. The Netherlands Institute for Social Research (Dutch: SCP), for example, tries to evaluate whether social policies work for all. It has become increasingly difficult to reach people with low literacy skills or low levels of trust in institutions, partly because most of the research in the social sciences is conducted via the web. This task concentrates on implementing methods across the data collections of ODISSEI that are effective in reaching these hard-to-reach groups in an ever more digitized world, and data collection landscape. It includes experimentally testing variations of push-to-web (Dillman, 2017) methods that use web- and paper-and-pencil data collection, as well as the use of face-to-face interviewers on location that are proven to be effective at reaching hard-to-reach groups. This task will be carried out in collaboration with Statistics Netherlands and Ipsos I&O as the largest fieldwork agency in the Netherlands. The goal is to come up with guidelines on how to successfully approach and include hard-to-reach groups in social science research, and an effective and tested approach for conducting large-scale surveys.

\USubtask 3: NL survey alignment\u In this task, the integration of the existing surveys is consolidated. Overall, the main goal of this task is to make the surveys future-proof, make them cheaper to coordinate, and make them more timely. It will create the ODISSEI survey office that will coordinate the tendering, sampling, and coordination of all surveys, serve as a liaison to the international coordinators of surveys, and focus on harmonizing the surveys in terms of content.

The ODISSEI survey office will harmonize the surveys procedurally. Currently, survey fieldwork takes many months. A main reason surveys are slow is the time it takes to tender fieldwork, sample respondents from the population register (through RvIG, the National Service for Identity Data), and organize fieldwork. In many situations nowadays, the timeliness of surveys is very important, such as when an early election is called (NKO), or when attitudes towards quickly changing government policies need to be monitored (e.g., in the context of COVID-19). Rather than drawing separate samples for every individual survey, the ODISSEI survey office will develop an accelerated sampling service that can be used for all surveys in the Netherlands. Access to the accelerated sampling service is determined by the ODISSEI Data Collection Committee and open to social science studies. The ODISSEI survey office will also coordinate the tendering and fieldwork of all surveys, and be the main contact point for international partners, with the goal of fostering the harmonization of surveys at an international level.

The second part of this task focuses on integrating the surveys in terms of content. The current data collections in ODISSEI cater to different groups of end-users in the social sciences, biomedical sciences and humanities, and each have a different focus such as social attitudes, aging or politics. Some important research questions span multiple of these areas, and are currently not answerable using data from one survey alone. In this task, we will integrate surveys by fielding all surveys in the LISS panel so that researchers are able to study relations between topics asked in the different surveys. This will enable the study of e.g. the voting behavior of older people, how attitudes measured in ESS and EVS relate life histories in GGP, or how voting behavior can be explained longitudinally by linking to the rich set of covariates in LISS.

Outputs of this project are expected in the period 2026-2031, and can be found here .

face-to-face | Peter Lugtig

Macroscope