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Scope
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Experience (related to terms such as lessons learned, good practice, tacit knowledge) has long been taken as one of the most important resources for organizations to be successful. The new era of Industry 4.0, IoT and the digital change in general strongly focuses on self-organizing, autonomous and self-adapting systems. Underlying approaches utilize the increasing amount of data being available and advanced data analytics algorithms. Do these developments mean that human insight and vision based on experience will decline in importance? Will big data override experience and intuition and will Industry 4.0 therefore spell the end of decisions based on experience and domain expertise and replace them with decisions based on data and text mining?

There is a large consensus in the knowledge management community that human experience will continue to play an important role for organizations. However, faced with new self-organizing and self-adapting systems, new perspectives and new approaches are needed to capture, share, utilize, and reuse experience in a digital world.

This workshop addresses all aspects of experience management, ranging from primarily ICT-based solutions to approaches that rely more on fostering and enabling social interactions. We especially encourage contributions that deal with the role of human experience in a new world of self-organizing systems and automatic decision-making based on big data.

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Topics of Interest
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Submissions from all areas contributing to the development and application of experience management (EM) systems are welcome. We explicitly encourage paper submissions from all kinds of disciplines such as computer science, social sciences, mathematics, economics in order to obtain aninterdisciplinary view on the subject.

Topics of interest include but are not limited to:

- Modeling, representing, discovering, sharing and utilizing experience
- Case-Based Reasoning
- Semantic technologies
- Data-driven EM
- Methods and approaches for integrating EM into organizations and their processes
- User acceptance of algorithm-driven decisions
- Explanation-aware computing
- Software engineering aspects of EM systems
- Case studies of EM from any application domain (e.g. finance, industry 4.0, commerce, eHealth, science)
- Aspects of EM in organizations (e.g. demographic shifts and HR challenges)
- EM in society, energy and sustainability
- How to motivate people to exchange their experience