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Abstract
Nowadays, big data analytics are increasingly replacing human decision-making processes in practice fields. In the welfare context, however, they are still being explored only marginally. The following theoretical discussion draws on the example of the MAEWIN project to explore the challenges of using big data when developing decision support systems in the context of social work. The project reveals some similarities with the well-known challenges of big data research (e.g., with regard to data protection, bias, and handling probabilities). However, it also has to face further challenges such as the different knowledge approaches within social work.
Acknowledgment
This research was supported by the Digital Society research program funded by the Ministry of Culture and Science of the German State of North Rhine-Westphalia.
Additional information
Notes on contributors
Diana Schneider
Diana Schneider has a BA in Philosophy, and German Literature and Language along with an MA in Culture and Technology focusing on Technology and Technology Development in Public Discourse. Since January 2018, she is a PhD candidate in the MAEWIN project as part of the Digital Society research program funded by the Ministry of Culture and Science of the German State of North Rhine-Westphalia.
Udo Seelmeyer
Udo Seelmeyer is Professor of Social Work Science at the Faculty of Social Work at Bielefeld University of Applied Sciences and Head of the scientific division "Competence Center Social Services" (kom.ds) at the Institute for Innovation Transfer at Bielefeld University. He is also deputy spokesman of the Digital Society research program funded by the Ministry of Culture and Science of the German State of North Rhine-Westphalia.