SS01 - Model-based/Data-driven Safety, Security and Privacy in Society 5.0

Special Session Organized by

Muhammad Taimoor Khan, University of Greenwich, UK and Dimitrios Serpanos, ISI Athena, ECE, University of Patras, Greece and Howard Shrobe, MIT CSAIL, USA and Kunio Uchiyama, AI Chip Design Centre, Japan

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Focus

In this Special Session Computing constitutes a fundamental component of the emerging Society 5.0, which combines cyber and physical spaces (i.e., processes) and requires control and monitoring techniques for its operation and management. In Society 5.0, people, things, and systems are connected in cyberspace and operate exploiting automated methods, including machine learning (ML) and artificial intelligence (AI). Such operation and management bring new value to industry and society in ways not previously possible. Typical cyber physical systems (CPS) are based on (I)IoT (Industrial - Internet of Things) and (I)CPS (Industrial - Cyber Physical Systems) and have applications in all critical infrastructure domains with strict real-time requirements, such as healthcare, electric grid, transportation, to name a few. Intentional or accidental errors/failures/attacks to these systems have highly severe consequences. Therefore, novel design methodologies are required to ensure that design of real-time cyber physical systems and applications in the emerging Society 5.0 are free of vulnerabilities, threats and attacks. Since the physical part of CPS involves several processes, typically, it is challenging to ensure that the design is free from all known vulnerabilities. It is necessary to develop run-time monitoring and analysis techniques that can help to detect run-time incidents by observing the processes and their data. Furthermore, adequate modelling of CPS physical processes and corresponding cyber and physical attacks is fundamental to systematically model, analyse and verify real-time security of CPS. Importantly, since AI and machine learning have demonstrated their success in many application areas including cyber security, this special session focuses on investigating AI, machine learning and formal methods-based techniques to develop safe and secure real-time cyber physical systems at all levels, from hardware components to applications.

Topics under this track include (but not limited to):
  • Data-driven (AI and Machine Learning-based)/model-based
  • Formal methods (FM)-based safety and security of critical systems at design-time and run-time
  • Safety, security and privacy of citizens in Society 5.0 including pandemics and disasters
  • Impact of pandemic and natural disasters on safety, security and privacy of citizens
  • CAD tools for AI-based cyber-physical systems (CPS)
  • CAD tools for safe, secure and privacy-aware RT-CPS
  • Case studies for AI and machine learning-based RT-CPS
  • Benchmarks for security, safety and privacy of RT-CPS
  • Challenges in modelling, analysis, safety, security and privacy of RT-CPS

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SS 02 - Dynamic Reliability Calculation of Industrial Automation Systems Using Digital Twins

Special Session Organized by

Nasser Jazdi, University of Stuttgart, Germany and Vicente Lucena, Federal University of Manaus, Brazil and Behrang Ashtari, Siemens Healthineers, Germany

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Focus

The digital twin has evolved from a mere idea to a more and more concrete technology that can support the engineering, maintenance, reconfiguration, recycling, etc. of an asset (an industrial automation system). An important future application of the digital twin would be the dynamic calculation of the reliability of the asset throughout its life cycle. However, the digital twin does not yet support reliability estimation sufficiently, despite the obvious benefits. Using the dynamic characteristics of a digital twin, reliability can be calculated dynamically and instantaneously, in contrast to conventional approaches to calculating the reliability of industrial automation systems, which only consider information from product specifications or experiments. Furthermore, the static information of an asset may age and therefore no longer accurately represent the asset in late phases of its life cycle. Challenges lie in approaches automatically spotting limitations of models, in calculation of reliability at runtime and in model quality management throughout life cycle.

Topics under this track include (but not limited to):
  • Dynamic calculation of the reliability of industrial automation systems
  • Digital Twin and its aspects considering reliability and safety
  • Adaptive models of digital twin
  • Challenges and limitations of using digital twins for reliability calculations
  • Experiences and case studies related to digital twins for functional safety and reliability calculation
  • Machine learning on resource limited industrial automation systems
  • Robust machine learning on systems with less data

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SS 03 - Industrial Cybersecurity Methods and Technologies

Special Session Organized by

Paulo C. Bartolomeu, Instituto de Telecomunicações, Portugal and Stefano Marrone, University of Campania, Italy and Ricardo J. Rodríguez, University of Zaragoza, Spain

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Focus

Industrial cybersecurity has become a key research topic in recent years due to the massive connectivity brought by the Internet of Things and the rise of cyberattacks against industrial assets. While fostering contemporary applications and use cases, ubiquitous Internet access has also exposed legacy operational technologies to new and challenging security threats that must be addressed. This Special Session focuses on novel security, safety, and privacy-enhancing technologies for current and future industrial applications.

Topics under this track include (but not limited to):
  • Security, safety, or privacy-enhancing technologies in industrial systems
  • Modeling of cybersecurity threats
  • Applications of distributed ledger technologies/blockchains in Industry 4.0
  • Self-sovereign identity for M2M and decentralized device-to-device communication
  • Hardware advances for securing Industrial devices and networks
  • Quantitative evaluation and/or interconnections among non-functional aspects (e.g., reliability vs. safety, security vs. performance)
  • Run-time methods and technologies for Complex Event Detection systems
  • Software engineering methods and techniques for high dependable control systems
  • Case studies / lessons learned of security, safety, or privacy assessments of industrial systems

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SS04 - Automation of modular systems and the Module Type Package

Special Session Organized by

Michelle Blumenstein, Helmut Schmidt University / University of the Federal Armed Forces Hamburg, Germany and Stephan Hensel, Semodia GmbH, Germany and Mario Hoernicke, ABB Corporate Research Ladenburg, Germany and Anselm Klose, TU Dresden, Germany and Andreas Stutz, Siemens AG, Technology and Innovations, Karlsruhe, Germany

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Focus

For a few years, the concepts of modular automation have been seen as a key technology for highly flexible operation in the process industry. The basic idea of this concept is that fully automated modules, so-called Process Equipment Assemblies (PEAs), with specified functionalities can be combined to form modular process plants. Recently, the attention for this topic has increased in industries far beyond the process industry. There’s research to use those concepts e.g. in production-related logistics for the supply and disposal of production plants, in shipbuilding for the integration of the various sub-systems into a ships’ information system, and in manufacturing industry in the context of machine capabilities and skills. Starting some years ago as German standard VDI/VDE/NAMUR 2658, the concepts are now on the threshold to international standardization in the form of a New Work Item Proposal for IEC 63280. In addition to that, other standardization activities such as OMAC PackML, the Open Process Automation Standard, the Industry 4.0 base system BaSys or the concept of the Asset Administration Shell are related to the VDI/VDE/NAMUR 2658 as they also act in the area of modular automation. Next to those standardization efforts, industry associations such as the BioPhorum or the VDMA are taking up the basic concepts of the VDI/VDE/NAMUR 2658 and develop them further within the framework of industry-specific extensions, concretizations and adaptations. With this proposal the organizers would like to provide a first international platform for work in this community and to support the international dissemination of the VDI/VDE/NAMUR 2658 concepts with regard to the beginning standardization within IEC 63280

Topics under this track include (but not limited to):
  • Cross-industry applications of Modular Automation concepts: process industry, discrete industry, intralogistics, ships/marines, energy industry, …
  • Industry-specific extensions and adaptions: bio-pharmaceutical, logistics, dairy, …
  • Conceptional comparisons: Open Process Automation Standard, OMAC PackML, OPC UA for Machinery, UMATI, …
  • Lifecycle and scalability: engineering, operation / laboratory, piloting, production, …
  • New technologies in the context of Modular Automation: Microservice architectures, micro frontends, method-based orchestration, low code programming/configuration, ...

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SS05 - Machine Learning and Data Analytics for Failure Analysis in Automation and the Manufacturing Industry

Special Session Organized by

Anis Hoayek, Mines Saint-Etienne, France and Ingmar Kallfass, University of Stuttgart, Germany and Simon Kamm, University of Stuttgart, Germany

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Focus

In automation and manufacturing industry, products are becoming more and more integrated and complex. These high technological products must operate reliably and safely in daily use as they are used in safety-critical applications (e.g. automotive domain). Post-production Failure Analysis is a process to build a progressive diagnosis and understanding of failure factors, leading to in-depth root cause analysis. In spite of a highly technological environment, the industrial process of Failure Analysis is often carried out manually, driven by single tasks coming from production, reliability testing and field returns, and relies heavily on human expert knowledge. Automation offers important opportunities here to improve the efficiency of failure analysis. Artificial Intelligence and Machine Learning algorithms are increasingly playing a leading role in suggesting solutions in fields related and not limited to anomaly detection, condition monitoring, failure analysis and root cause analysis in many domains. Therefore, this special session aims at discussing recent advances and developments in this field. In addition, recent advances coming from Industry 4.0 to support failure analysis on high technology manufactured devices are highly relevant for further automation of the failure analysis and are welcomed in this special session.

Topics under this track include (but not limited to):
  • Artificial intelligence and Machine learning for Failure Analysis
  • Statistical models and formalisms for production defect analysis
  • Industry 4.0 to support failure analysis, on high technology manufactured devices
  • Anomaly detection on industrial devices
  • Automation of Failure Analysis process
  • Root cause analysis, for industrial devices’ failures

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SS06 - Applications of Time Sensitive Networking (TSN)

Special Session Organized by

Dave Cavalcanti, Intel Corporation, USA and Tommaso Fedullo, Department of Management and Engineering, University of Padova, Italy and Alberto Morato, National Research Council of Italy, CNR-IEIIT, Padova, Italy

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Focus

This Special Session will investigate innovative applications of Time Sensitive Networking (TSN) technologies and standards. Emerging distributed computing, monitoring, data acquisition, and measurement systems are heavily reliant on wired and wireless real-time communications, allowing for seamless, standardized, and transparent device integration. In this context, Time Sensitive Networking provides a set of features capable of supporting a wide range of time-critical applications from the bottom of the automation pyramid all the way up to the edge and cloud computing. TSN can be seen as a toolbox that can be configured to enable accurate time synchronization and deterministic latency meeting time-critical requirements. TSN has applications across multiple markets segments and segment specific profiles have been (or are being) developed. For example, a TSN profile is being developed by the IEEE/IEC 60802 group for Industrial Automation and a profile for Audio Video Bridging systems has been developed by Avnu Alliance. Nevertheless, TSN capabilities are not limited to those application domains only. TSN capabilities to deliver time and timeless with high configurability can benefit a broader range of applications that, actually, need to be further investigated. For example, extended reality (XR), financial systems, safety-critical systems, sensors networks, and time-critical systems in industrial, robotics, avionics, aerospace, and automotive applications can benefit from the features of TSN-based Wired, Wireless, or hybrid communication networks, but they are also expected to bring new challenges. This special session will bring together case studies, prototypes, implementations, testing best practices, and innovative applications and challenges for TSN enabled by the latest wired/wireless communications and computing technologies.

Topics under this track include (but not limited to):
  • Industrial and enterprise applications
  • Industrial automation case studies
  • TSN for distributed measurement systems
  • Automotive applications of TSN
  • TSN and Extended Reality (augmented, virtual and mixed reality)
  • TSN for avionics/aerospace applications
  • TSN-based functional safety
  • TSN-based robotics systems and applications
  • TSN and hyperautomation
  • TSN interoperability and performance testing methodologies

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SS07 - Skill Based Systems Engineering (SEnSEI)

Special Session Organized by

Christian Diedrich, Otto von Guericke University, Germany and Roman Froschauer, University of Applied Sciences Upper Austria, Austria and Aljosha Köcher, Helmut Schmidt University, Germany and Kristof Meixner, CDL-SQI, TU Wien, Austria and Siwara Schmitt, Fraunhofer IESE, Germany

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Focus

The selection of proper automation components for a given task is a complex, challenging, and time-consuming task. As customer requirements tend to change more frequently, it becomes necessary to pursue flexible and variable automation approaches. Recent research has introduced approaches based on capabilities and skills using holistic data models, like ontologies, DSLs, or variability models. While capabilities are seen as abstract descriptions of the (manufacturing) processes that systems perform, skills are often described as their executable counterparts (i.e.,modelinginvocationinterfaceslikeOPCUA). To automatically find solutions for customer requirements, required tasks and domain-specific constraints have to be matched with capabilities provided by automation components. This matching can be done with various techniques like AI planning or knowledge graph exploration and reasoning. Skill-based process plans can then be orchestrated by combining the skills related to the previous step's capabilities. Finally, simulation andoptimization of such process plans can be performed before their deployment.

Topics under this track include (but not limited to):
  • Modeling of automation tasks and capabilities: Data Modeling, Modeling Languages, Knowledge Graphs, Rule Engines, Knowledge-based Systems
  • Finding possible components: Planning, Artificial intelligence, Capability-task-matching, Knowledge Graph Exploration
  • Skill-based processes: Generation/Modeling, Orchestration, Execution, Optimization
  • Simulation of a proposed plan: Optimization, simulation techniques
  • Derivation of code: Automated code generation, model-based programming

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SS08 - Industry 5.0 – Augmenting the Human Worker in Balanced Automation Systems

Special Session Organized by

Tamás Ruppert, MTA-PE Lendület Complex Systems Monitoring Research Group, University of Pannonia, Hungary and Andreas Löcklin, Institute of Industrial Automation and Software Engineering, University of Stuttgart,, Germany and David Romero, Advanced Manufacturing Research Group, Tecnológico de Monterrey, Mexico and Johan Stahre, Department of Industrial and Materials Science, Chalmers University of Technology,, Sweden

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Focus

The Fourth Industrial Revolution, or Industry 4.0, has created relevant changes in regards to the presence of human workers at the shop f loor, and the roles they play in smart, resilient manuf acturing systems. Although high to medium levels of automation, robotization, and digitalization are becoming a prevalent trend in many smart f actories, there is consensus that human workers will remain an essential part of such smart manuf acturing environments and systems. Nevertheless, “human-centric” strategies are still much underrepresented in the Industry 4.0 paradigm, making manuf acturing companies realize that they need to make significant efforts to put their human workers back at the center of their shop f loor digital transformations. This realization has created the emergence of a new Industrial Revolution, ref erred to as “Industry 5.0”, aimed at bringing back the human worker at the center of the development of the f actory of the f uture. The Fif th Industrial Revolution aims to pair humans, machines, robots, and artif icial intelligence to utilize human creativity even f urther and increase processes eff iciency by combining material and information workf lows with intelligent assets and systems. While the primary concern in the Industry 4.0 paradigm is or was about automation, robotization, and digitalization, the Industry 5.0 hallmark is the exploration of new synergies between humans and intelligent assets and systems. Also, Industry 5.0 is about the social sustainability and the resilience of human workers and human-technology systems. The recent “Operator 5.0” concept and vision show a f uture of work in this direction.

Topics under this track include (but not limited to):
  • Human-Machine/Robot/AI Interf ace in IIoT f or Industrial Applications
  • Digital Twins, Device Models, Adaptive- and Automation-Models
  • Human-Machine/Robot/AI Interf aces and SCADA Supervisory Systems.
  • Human Factors, Industrial Ergonomics, and Safety in Smart Maintenance Systems
  • Smart Manuf acturing Environments
  • Industrial Sensor Networks and Wearables Sensors
  • Real-time Locating Systems
  • Process Modelling and Simulation

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SS09 - Hyper-automation in Industry 4.0

Special Session Organized by

Giulia Michieletto, Department of Management and Engineering, University of Padova, Italy and Susruth Sudhakaran, Intel Corporation, USA

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Focus

This Special Session focuses on the emerging role of hyper-automation in Industry 4.0 and beyond, as the nexus among autonomous robotics, machine vision, and learning. Hyper-automation is currently representing a true digital transformation implying the combination of multiple and heterogeneous intelligent systems to fulfil complex needs, while increasing both the human expertise and the automation experience. The main advantages of hyper-automation include lower automation costs, improved IT-business alignment, and enhanced security and governance. Hyper-automation is rising with the evolution of automation technologies. In particular, the recent advances in intelligent sensing are leading to the design of immediate and accurate environment perception systems; the innovative Machine Learning and Artificial Intelligence techniques are entailing the possibility of elaborating large amounts of data to make and support decision processes; the cutting-edge trend in developing safe, secure, and time-sensitive communication protocols are encouraging the outline of large and distributed networked architectures. All these elements boost the exploitation of hyper-automated systems within the smart industrial context for the purpose of reducing the expenses, increasing the productivity and improving the efficiency via automation in all the processing stages. The concept of hyper-automation, thus, encompasses multiple versatile and enabling technologies including also process mining, Robotic Process Automation, digital twin of the organisation, optical character recognition, and natural language processing. For all these reasons, hyper-automation appears a promising and avant-garde framework for the Industry 4.0 and beyond, encouraging the investigation of its complexity and potentialities. This Special Session aims to assess the obtained results in the field of hyper-automation, focusing on implementations, case studies and prototype systems, as well as to address future research directions.

Topics under this track include (but not limited to):
  • hyper-automation: concepts, components, and case studies
  • business and process-oriented integration for hyper-automated systems
  • AI decision making based on advanced IoT analytics in the context of hyper-automation
  • hyper-automation integration with existing systems
  • Natural Language Processing and intra-active systems
  • fail-safe, reactive, and resilient hyper-automated systems
  • hyper-automated complex heterogeneous systems

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SS10 - Advanced Methods for the Management of Factory Networks

Special Session Organized by

Gianluca Cena, Institute of Electronics, Information Engineering and Telecommunications of the National Research Council of Italy(CNR-IEIIT), Torino, Italy and Maxim Friesen, Institute Industrial IT - inIT of Technische Hochschule OWL, Lemgo,, Germany and Mikael Gidlund, Department of Information Systems and Technology (IST) of Mid Sweden University, Sundsvall, Sweden and Arne Neumann, Institute Industrial IT - inIT of Technische Hochschule OWL, Lemgo,, Germany and Stefano Scanzio, Institute of Electronics, Information Engineering and Telecommunications of the National Research Council of Italy(CNR-IEIIT), Torino, Italy and Lukasz Wisniewski, Institute Industrial IT - inIT of Technische Hochschule OWL, Lemgo,, Germany

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Focus

Customization, resilience, and efficiency are some of the major challenges that production plants are faced with today and in the future. Comprehensive acquisition, processing, and utilization of process information can help to tackle these issues. They are themselves in turn based on comprehensive interconnection by data networks. Here, a variety of demanding requirements including reliability, determinism, update frequencies, data throughput, power consumption, safety, security, and mobility, as well as interoperability with legacy systems, lead to the deployment of a plurality of wired and wireless communication technologies. To overcome the resulting complexity of planning, configuring, operating, and maintaining such heterogeneous factory networkinfrastructures, advanced methods and tools are needed.

Topics under this track include (but not limited to):
  • Case studies on integrated wired and wireless communication technologies
  • Control and management architectures for heterogeneous and dependable factory networks, considering reactive and proactive (re-)configuration of network parameters
  • Information modelling for improving the interoperability and convergence of industrial network systems and use of digital twin technology for life-cycle management
  • Provisioning of end-to-end QoS and intelligent resource allocation in heterogeneous factory networks, including edge computing and storage
  • AI and ML based methods for the management of factory networks
  • Advanced measures for the management of safety and security in factory networks
  • Management of Low-power and Lossy Networks (LLNs)
  • Management of the perception and network layers in the Industrial IoT (IIoT)
  • Analogies in network management for verticals (vehicular, building automation, disaster recovery, etc.)

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SS11 - New technologies applied to industrial carbon neutrality: factory applications

Special Session Organized by

Miguel Delgado-Prieto, Technical University of Catalonia, Spain and Luis Romeral Martínez, Technical University of Catalonia, Spain

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Focus

The manufacturing sector accounts for approximately one-third of global greenhouse gas emissions. Therefore, the green and digital transformation of the industrial sector is essential for the transition to a sustainable energy model, adapting their energy generation infrastructure and their energy demanding systems to the latest trends, and preparing them for their active participation towards the foreseen European energy system. In this regard, this special session is focused on the discussion of emerging technologies, such as artificial intelligence, digital twins, industrial internet of things and cyberphysical systems, among others, applied to industrial carbon neutrality challenges.

Topics under this track include (but not limited to):
  • Industrial energy hubs
  • Industrial renewable infrastructures
  • Industrial demand response schemes
  • Digital models for the operation of energy systems in industry
  • Advanced control strategies of industrial systems for efficiency increase
  • Novel monitoring solutions for industrial assets performance monitoring

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SS12 - Automation of Automation

Special Session Organized by

Ramez Awad, Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Germany and Thomas Bauernhansl, Fraunhofer Institute for Manufacturing Engineering and Automation IPA; Institute of Industrial Manufacturing and Management IFF at the University of Stuttgart, Germany and Richard Bormann, Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Germany and Werner Kraus, Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Germany

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Focus

In this Special Session we will focus on methods, tools and technologies aimed at the reduction of lead time and engineering effort for designing, implementing or adapting a production line for new products, product variants or higher/lower production volumes.

Topics under this track include (but not limited to):
  • Manufacturability of products in general and w.r.t. specific production systems
  • Discovery of resource skills/capabilities, as well as asset management
  • Capability-based resource selection and task assignment
  • Generation of cell layouts and AGV transportation routes
  • Scheduling of production and logistic jobs
  • Generation of executable control programs
  • Coordination and orchestration of production and logistic agents
  • Usage of Machine Learning for robot programming
  • Automated risk assessment and CE declaration

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SS13 - Safety for heterogeneous agile production systems

Special Session Organized by

Rasmus Adler, Fraunhofer IESE, Germany and Dieter Etz, TU Wien, Austria and Andrey Morozov, University of Stuttgart, Germany and Florian Pelzer, TU Dresden, Germany and Leon Urbas, TU Dresden, Germany

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Focus

In various branches of industry, the need for flexible production options is becoming increasingly apparent. This trend is met with higher automation, digitalization, and modularization strategies of production systems to reduce time to market and create easily adaptable systems. However, acceleration and flexibility must not be at the expense of plant safety.

Flexible systems are accompanied by new requirements for (1) risk analysis and evaluation, (2) implementation of safety systems, and (3) regulatory approval of plant safety. The approaches from conventional plants are reaching their limits when transitioning towards lot size one and approving them individually becomes impossible for every single plant setup. The possible compositions of systems are hardly foreseeable, and the combinations of system configurations and parameter settings explode. Systems such as autonomous mobile robots (AMRs), collaborative robots (cobots), robotic manipulators, or drones can implement various tasks and dynamically form a system of systems for achieving a common mission. Moreover, the trend to Software-Defined Manufacturing (SDM), where a software update can drastically change the entire production process, requires a completely new approach to risk analysis that should be performed in automated way before each software update. Assuring the safety of such system of systems is challenging due to their dynamic nature and their unstable system boundaries.

Topics under this track include (but not limited to):
  • Cross-industry application of agile safety concepts: e.g. discrete industry, process industry
  • New technologies and strategies for plant safety
  • New safety approaches for system of systems in smart manufacturing, autonomous warehouses and modular automation
  • Safety assurance, safety cases, and upcoming safety regulation in smart manufacturing
  • Modeling and risk assessment of software-defined manufacturing systems
  • Symbiotic safety and safety of sociotechnical systems
  • Validation of concepts at demonstration plants
  • Subject areas according to IEC 61508 and derived standards such as Hazard and Risk Analysis and Technical Plant Safety

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SS14 - Knowledge Graphs for Smart Manufacturing: Modeling and Applications

Special Session Organized by

Irlan Grangel-Gonzale, Bosch Corporate Research, Germany and Tamás Ruppert, MTA-PE Lendület Complex Systems Monitoring Research Group, University of Pannonia, Hungary and Franz Listl, Siemens AG, Germany and Nada Sahlab, Institute of Industrial Automation and Software Engineering, University of Stuttgart, Germany

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Focus

Knowledge Graphs depict an effective way for structuring heterogeneous data, which is characterized by a high semantic expressiveness. They are used to continuously gather data describing dynamic real-world entities and their relations in a unified model for gaining new insights. Knowledge Graphs emerged in the past decade with research focused on knowledge representation, learning and application.

Enabling concepts of Industry 4.0, such as the Internet of Things, Cyber-Physical Systems as well as Digital Twin require mechanisms for handling highly heterogeneous, dynamic and complex data from the physical asset and its environment to realize various applications. Knowledge Graphs, although a promising approach to address some of the data modeling, exchange and management challenges remain scarce within the industrial domain.

The objective of this special session is to highlight on the potential and applicability of Knowledge Graphs for smart manufacturing.

Topics under this track include (but not limited to):
  • Knowledge Organization and Representation
  • Ontology-based Knowledge Graphs
  • Knowledge Graph evolution with streaming data
  • Knowledge Graph and its relevance to the Digital Twin
  • Knowledge Graphs and AI, e.g., graph embeddings
  • Applications of Knowledge Graphs

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