About the Workshop
Industrial enterprises currently address the challenge of transforming the ideas of the Internet of Things, Industry 4.0, Cyber-Physical Systems, and similar concepts into reality. A direct application of the IoT approach to the production chains in manufacturing companies is presently not feasible, as there are many more parameters, but much less available data compared to other big data application domains. Modern production is characterized by vast amounts of data. However, this data is neither easily accessible, interpretable, nor connected to gain knowledge. Digital twins are supposed to provide a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital twins in inter-organizational production chains that cross several boundaries have not been addressed yet in a systematic manner.
In this context, also various data management challenges have to be addressed. Huge amounts of heterogeneous sensor data (numerical, audio, video, etc.) have to be processed in real-time in order to control the production machines. In addition, unstructured data from production reports or external sources have also to be integrated to analyze and optimize the production process. Well established mathematical models for production engineering have to be integrated with data-driven machine learning for cross-domain knowledge generation.
On the other hand, Industry 4.0 or the Industrial Internet of Things are the basis for new applications and business opportunities. By connecting physical objects, systems, machines, and applications, the data produced by these objects may become a valuable resource, i.e., a product in its own right. Thus, data management and analysis operations have to be linked questions about value creation within and across enterprises. These ideas raise new requirements in terms of trust, data security, and data sovereignty, which also have to be considered in data-oriented industrial applications.
The workshop aims at bringing together researchers from different domains and to discuss the challenges for data science in industrial settings. The workshop will provide a forum for the presentation of recent research results, work-in-progress reports, vision papers, a panel discussion, and an attractive keynote speaker.