Special Session on Knowledge Graphs in Digitalization Era (KGDE2021)
34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2021)
The fourth industrial revolution, also known as Industry 4.0 (I40), is affecting almost every industry worldwide and is rapidly transforming how businesses operate in various domains such as: Health, Banking, Education, Transportation, Aeromechanics, Urbanization, Manufacturing, Petrochemical, Environments. Current trends in I40 includes: advanced process automation and robotics, Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning, Machine-to-Machine and Human-to-Machine Communication, and Sensor Technology and Data Analytics. I40 integrates mainly technologies related to Cyber-Physical Systems, IoT, AI, Data, and Knowledge in their different forms to reach an optimal value-added chain. This chain is associated with complex processes, manipulating huge amounts of data issued from different providers, systems, and platforms, that must be automated and optimized. These processes are usually driven by standards and norms. National and International institutions such as ISO, IEC, ETSI, NIST, ANSI, SAC, and AFNOR are spending a lot of effort in providing such norms and standards to facilitate collaboration, integration, sharing, enrichment of processes, their associated data, and then the final products.
The key drivers enabling the I40 trend is the rising data volumes, computational power and connectivity. In this context, the notion of Knowledge Graphs (KGs) plays a vital role in understanding the emerging analytics and business-intelligence capabilities. A Knowledge Graph can be considered as a Knowledge Base that consists of a set of concepts organized into a taxonomy, instances for each concept, and relationships among the instances. The information in a KG can be gathered from a variety of sources such as Social, Open, Private (personal/business) and IoT data islands. Accordingly, KGs can facilitate understanding the businesses’ big data as well as the connectivity between customers and supply chains through real-time access to production information, logistics and monitoring. The spectacular development of KGs contributes at the same time in inspiring enterprises to constitute networks of highly recognized authorities of norms and standards and in integrating them in their industry and manufacturing processes – the case of the Industry 4.0 Knowledge Graph (I40KG) – as well as in considering KGs as an important tool to enhance the quality of the value of the developed products.
Knowledge Graphs in Digitalization Era (KGDE) will be held as one of the sessions of the 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2021). The KGDE session aims at providing a forum for researchers and professionals interested in the contributions of Knowledge Graphs Networks in I40.
Call for paper
We are inviting original research submissions (FULL 12 pages) and work-in-progress (SHORT 6 pages). Submitted papers must be formatted using the Springer LNCS/LNAI style.
Topics of interest include but not limited to:
- Life Cycle of Construction of KGs
- KG Representation
- Quality of KGs
- KG Storage
- KG Exchange
- KG deployment Platforms
- KG-based Intelligent Applications for I40
- Contextualized KGs
- Exploratory Querying of KGs
- KG Visualization
- Added Value of Usage of KGs in I40
- KG-enabled AI Solutions for I40
- Modeling Languages and KGs in I40
- KG-driven Process Automation
- KG-driven Service Management
- KGs for Smart Factories
- KG-driven Data Curation
- KG-driven Process Mining
- KG-based Recommendation
- Designer/Customer Experience and KGs in I40
- Challenges, vision, and concepts for I40 and KGs
- Implementation and real-world case studies
- Intelligent Data Lakes and Knowledge Lakes
|Conference Sessions:||July 26 –29, 2021|
*Announcement: Due to the current pandemic of COVID-19, virtual video presentation can be considered and allowed for presenters from affected regions and countries.
Submission Site: https://cmt3.research.microsoft.com/IEAAIE2021/Submission/Index
- Ladjel Bellatreche, LIAS/ISAE-ENSMA, Poitiers, France
- Amin Beheshti, Department of Computing, Macquarie University, Sydney, Australia
- Stéphane Jean, LIAS/University of Poitiers, Poitiers, France
- Hamid Motahari, EY AI Lab, Palo Alto, USA