Open-source science is reshaping how we collaborate and innovate—making research faster, more flexible, and better equipped to tackle complex societal challenges.

In this video, I discuss:
🔹 The "production" side of open science
🔹 How open-source models are shaping social science research
🔹 The goals and progress of the CPF harmonization initiative
🔹 Key advantages—and challenges—of collaborative, transparent data work

But for more information, you can also check this open article that discusses these things in detail: lnkd.in/emyZN_HV

💡 Have a look at the full paper for a deeper dive into the topic. Any comments are welcome!

One example is the CPF Open Harmonization (www.cpfdata.com). These kinds of initiatives don’t replace traditional research infrastructures, but they can be powerful complementary solutions. In computational social science, especially where heavy coding is involved, they have great potential.

In this article, I explore what it means to “open” knowledge production in social science – especially through open-source and crowd-based collaboration 🤝 . This is where researchers work together in dynamic, open networks, even if they’re not formally connected.

Natural sciences are leading the way in these developments. But in social science? The shift to open is happening much more slowly.

🚀Open source tools, code sharing, collaborative workflows, crowd-based cooperations – these can be powerful ways to work faster, smarter, cheaper, and across disciplines. They help us tackle big questions and innovate in ways that traditional structures sometimes can’t.

Open science is changing how we produce, verify, and share knowledge. And it’s not just about open-access publications, preregistration, or replication studies. It’s also about rethinking how we collaborate and build scientific infrastructure.

Friendly team, vibrant environment and good networking! Profile: sociology, demography, epidemiology/health, organizational psychology, HRM, etc.

Great opportunity for working with comparative and longitudinal designs, high-quality data sources (e.g., Comparative Panel File cpfdata.com, SHARE), new data collection (LISS lissdata.nl), and advanced statistical modelling.

More info here: lnkd.in/et_RxUYT. This project examines the shifting retirement trajectories for women and their impact on physical and mental health.