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A Study of Model Integration in ML-Enabled Software Systems

We are a research team from the Ruhr University Bochum, ITU Copenhagen and Chalmers | University of Gothenburg investigating ML-enabled software systems. Engineering such systems that rely on ML technologies for certain features is quite challenging, in fact, a whooping 80% of such projects fail. Therefore, the survey elicits practices and challenges related to the integration of ML models into software.

We invite practitioners involved with ML-enabled systems, such as developers, data scientists, or project managers, to take part. Your benefit is to reflect about your practices, learn about others' practices, and later receive a state-of-practice report with the results of this survey. 

The survey takes only 15 minutes to fill in. It contains questions on the ML technologies used in systems, on the integration of ML models into software and the reuse of ML models. Learn more about the study on our website: https://se.ruhr-uni-bochum.de/research/ml-enabled-systems/.

Thank you in advance,
Henriette Knopp (Ruhr University Bochum)(henriette.knopp@rub.de)
Yorick Sens (Ruhr University Bochum)
Sven Peldszus (ITU Copenhagen)
Thorsten Berger (Ruhr University Bochum, Chalmers | University of Gothenburg)

This survey is conforms to the ethics guidelines of the German Research Foundation.

This survey is anonymous.

The record of your survey responses does not contain any identifying information about you, unless a specific survey question explicitly asked for it.

If you used an identifying access code to access this survey, please rest assured that this code will not be stored together with your responses. It is managed in a separate database and will only be updated to indicate whether you did (or did not) complete this survey. There is no way of matching identification access codes with survey responses.

Privacy policy

We collect responses to survey questions, which include professional experiences, opinions, and demographic information. No personally identifiable information (PII) is required unless voluntarily provided. The data collected will be used solely for research purposes to analyze how industrial professionals engineering ML-enabled systems. All collected data will be stored securely and accessible only to authorized researchers. We employ appropriate technical and organizational measures to protect your data from unauthorized access, disclosure, or loss. Your responses will be analyzed in an aggregated and anonymized manner. No individual responses will be shared or published in a way that could identify participants. Participation in this survey is voluntary. You may choose not to answer any question or withdraw at any time without any consequences. If you wish to withdraw your personal data after submission, please contact us at henriette.knopp@rub.de. If you have any questions about this privacy policy or how your data is handled, please contact us.
 
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