PADME-SoSci: A Platform for Analytics and Distributed Machine Learning for the Social Sciences

ACM/IEEE Joint Conference on Digital Libraries, pp. 251–252

Abstract

Data privacy and ownership are significant in social data science, raising legal and ethical concerns. Sharing and analyzing data is difficult when different parties own different parts of it. An approach to this challenge is to apply de-identification or anonymization techniques to the data before collecting it for analysis. However, this can reduce data utility and increase the risk of re-identification. To address these limitations, we present PADME-SoSci, a distributed analytics tool that federates model implementation and training. PADME-SoSci uses a federated approach where the model is implemented and deployed by all parties and visits each data location incrementally for training. This enables the analysis of data across locations while still allowing the model to be trained as if all data were in a single location. Training the model on data in its original location preserves data ownership. Furthermore, the results are not provided until the analysis is completed on all data locations to ensure privacy and avoid bias in the results.

Authors 8

1. Zeyd Boukhers

   University of Cologne · Fraunhofer Institute for Applied Information Technology · University Hospital Cologne

   Affiliation as printed

   Fraunhofer Institute for Applied Information Technology -FIT-,Sankt Augustin,Germany

   Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

   Fraunhofer Institute for Applied Information Technology -FIT-, Sankt Augustin, Germany

2. Arnim Bleier

   GESIS - Leibniz Institute for the Social Sciences

   Affiliation as printed

   3GESIS - Leibniz Institute for the Social Sciences,Cologne,Germany

   3GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany

3. Yeliz Üçer Yediel Aachen

   Fraunhofer Institute for Applied Information Technology · RWTH Aachen University

   Affiliation as printed

   Fraunhofer Institute for Applied Information Technology -FIT-,Sankt Augustin,Germany

   Fraunhofer Institute for Applied Information Technology -FIT-, Sankt Augustin, Germany

   RWTH Aachen University, Aachen, Germany

4. Mio Hienstorfer-Heitmann

   GESIS - Leibniz Institute for the Social Sciences

   Affiliation as printed

   3GESIS - Leibniz Institute for the Social Sciences,Cologne,Germany

   3GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany

5. Mehrshad Jaberansary

   University of Cologne · University Hospital Cologne

   Affiliation as printed

   Faculty of Medicine and University Hospital Cologne, University of Cologne,Cologne,Germany

   Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

6. Sascha Welten Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Aachen,Germany

   RWTH Aachen University, Aachen, Germany

7. Adamantios Koumpis

   University of Cologne · University Hospital Cologne

   Affiliation as printed

   Faculty of Medicine and University Hospital Cologne, University of Cologne,Cologne,Germany

   Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

8. Oya Beyan

   University of Cologne · Fraunhofer Institute for Applied Information Technology · University Hospital Cologne

   Affiliation as printed

   Fraunhofer Institute for Applied Information Technology -FIT-,Sankt Augustin,Germany

   Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

   Fraunhofer Institute for Applied Information Technology -FIT-, Sankt Augustin, Germany