First International Workshop on

Data Science for Industry 4.0

In conjunction with EDBT 2019

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.

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Publication

The proceedings of the workshop will be published online as a volume of the CEUR Workshop Proceedings, ISSN 1613-0073, a well-known website for publishing workshop proceedings. It is indexed by the major publication portals, such as Citeseer, DBLP, and Google Scholar. This will be either a separate volume or a joint volume with the other EDBT workshops. Furthermore, a special issue in an international journal related to the workshop theme is planned for which the authors of the best papers of the workshop will be invited to submit an extended version of their work. Back to Top

Important Dates

  • Submission deadline:   December 20, 2018
  • Notification:         January 31, 2019
  • Camera-Ready:   February 15, 2019
  • Workshop:            March 26, 2019
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List of Topics

Data Stream Processing for Industrial Data

  • Adaptive systems
  • Data Stream Mining
  • Concept Drift Adaption
  • Machine Learning in Industrial Applications
  • IoT Analytics

Query Processing and Data Integration for Industrial Data

  • Integration of Sensor Data
  • Query Processing in Distributed Streaming Systems
  • Data Integration and Change Propagation

Distributed Architectures for Efficient Management of IoT Data

  • Edge & Fog Computing
  • Blockchain for IoT & Industry 4.0
  • New Hardware Architectures for Industrial Data Management
  • In-Network Data Processing and Analysis
  • Distributed Communication Networks and Data Analysis
  • Dependability
  • Quality of Service

Applications for Industry 4.0 and IoT

  • Data Management for Manucfacturing Engineering
  • Smart Homes, Smart Cities, Smart Facilities
  • Data Analytics in Industrial Internet of Things

Other Emerging Topics for Industrial Applications

  • Modeling & Reasoning for Industry 4.0, IoT, Digital Twins
  • Data Security and Data Sovereignty
  • Human-centered Interfaces
  • Semantic Web and IoT, Web of Things
  • Standardization in Industrial IoT Applications
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Submission Guidelines

DSI4 welcomes the full paper submission of original and previously unpublished research.
All submissions will be peer-reviewed and, once accepted, they will be included in the workshop proceedings.
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Workshop Organizers

Publicity Chair

  • Chair Public Relations
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    Rihan Hai

    RWTH Aachen University, Germany

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Supported By

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Call for Papers

The Call for Papers can be downloaded here.
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