CAIN 2022
Mon 16 - Tue 17 May 2022
co-located with ICSE 2022
Tue 17 May 2022 08:45 - 09:00 at CAIN main room - AI Models & Pipelines Chair(s): Lucy Ellen Lwakatare

The establishment of collaborative AI pipelines, in which multiple organizations share their data and models, is often complicated by lengthy data governance processes and legal clarifications. Data sovereignty solutions, which ensure data is being used under agreed terms and conditions, are promising to overcome these problems. However, there is limited research on their applicability in AI pipelines. In this study, we extended an existing AI pipeline at Mondragon Corporation, in which sensor data is collected and then forwarded to a data quality service provider, with a data sovereignty component. By systematically reflecting and generalizing our experiences during the twelve-month action research project, we formulated ten lessons learned, four benefits, and three barriers to data-sovereign AI pipelines that can inform further research and custom implementations. Our results show that including a data sovereignty component can help to reduce existing barriers and increase the success of collaborative data science initiatives.

Tue 17 May

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07:45 - 09:15
AI Models & PipelinesCAIN 2022 at CAIN main room
Chair(s): Lucy Ellen Lwakatare University of Helsinki
07:45
15m
Industry talk
Practical Insights of Repairing Model Problems on Image ClassificationIndustry Talk
CAIN 2022
Akihito Yoshii Fujitsu Limited, Susumu Tokumoto Fujitsu Limited, Fuyuki Ishikawa National Institute of Informatics
08:00
15m
Research paper
UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in ManufacturingResearch Paper
CAIN 2022
Erik Johannes Husom SINTEF Digital, Simeon Tverdal SINTEF Digital, Arda Goknil SINTEF Digital, Sagar Sen
08:15
15m
Research paper
Black-Box Models for Non-Functional Properties of AI Software SystemsResearch Paper
CAIN 2022
Daniel Friesel Universität Osnabrück, Olaf Spinczyk Universität Osnabrück
DOI Pre-print
08:30
15m
Research paper
Improving Generalizability of ML-enabled Software through Domain SpecificationResearch Paper
CAIN 2022
Hamed Barzamini , Mona Rahimi Northern Illinois University, Murtuza Shahzad Northern Illinois University, Hamed Alhoori Northern Illinois University
08:45
15m
Research paper
Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon CorporationResearch Paper
CAIN 2022
Marcel Altendeitering Fraunhofer ISST, Julia Pampus Fraunhofer ISST, Felix Larrinaga Mondragon Unibertsitatea, Jon Legaristi Mondragon Unibertsitatea, Falk Howar TU Dortmund University
File Attached
09:00
15m
Other
Discussion on AI Models & Pipelines
CAIN 2022


Information for Participants
Tue 17 May 2022 07:45 - 09:15 at CAIN main room - AI Models & Pipelines Chair(s): Lucy Ellen Lwakatare
Info for room CAIN main room:

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