ing.grid is proud to announce that we had one more successful open peer review process completed through our preprint platform. This led to the publication of the manuscript "PIA - A Concept for a Personal Information Assistant for Data Analysis and Machine Learning of Time-Continuous Data in Industrial Applications", available at https://doi.org/10.48694/inggrid.3827. This is the first publication from our 2022 NFDI4Ing Conference Special Issue.

The authors Christopher Schnur, Tanja Dorst, Kapil Sajjan Deshmukh, Sarah Zimmer, Philipp Litzenburger, Tizian Schneider, Lennard Margies, Rainer Müller and Andreas Schütze developed a concept to enable inexperienced users to perform a first data analysis project with machine learning and record data with high quality. The concept comprises three modules: accessibility of (meta)data and knowledge, measurement and data planning, and data analysis. Furthermore, the concept was implemented as a front-end demonstrator on the example of an assembly station and published on the GitHub platform for potential users to test and review the concept.

We congratulate the authors and thank the topical editor, Robert H. Schmitt, and the reviewers Anas Abdelrazeq and Marco Kemmerling for their valuable efforts. We also thank all the ongoing support offered by the TUjournals team at the University and State Library Darmstadt and the Janeway development team.

FAIR Data FAIR NFDI4Ing PIA Data Analysis Machine Learning