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检索条件"任意字段=Workshop on Knowledge and Data Engineering Exchange"

共 178 条记录，以下是1-10 订阅

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6th International workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2022, 4th International workshop on Machine Learning and knowledge Graphs, MLKgraphs 2022, 2nd International workshop on Time Ordered data, ProTime2022, 2nd International workshop on AI System engineering: Math, Modelling and Software, AISys2022, 1st International workshop on Distributed Ledgers and Related Technologies, DLRT2022 and 1st International workshop on Applied Research, Technology Transfer and knowledge exchange in Software and data Science, ARTE2022 held at 33rd International Conference on database and Expert Systems Applications, DEXA 2022

6th International Workshop on Cyber-Security and Functional ...

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6th International workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2022, 4th International workshop on Machine Learning and knowledge Graphs, MLKgraphs 2022, 2nd International workshop on Time Ordered data, ProTime2022, 2nd International workshop on AI System engineering: Math, Modelling and Software, AISys2022, 1st International workshop on Distributed Ledgers and Related Technologies, DLRT2022 and 1st International workshop on Applied Research, Technology Transfer and knowledge exchange in Software and data Science, ARTE2022 held at 33rd International Conference on database and Expert Systems Applications, DEXA 2022

ISBN: (纸本)9783031143427

The proceedings contain 40 papers. The special focus in this conference is on database and Expert Systems Applications. The topics include: Synthetic data in Automatic Number Plate Recognition;An Untold Tale of Scientific Collaboration: SCCH and AC 2 T;on the Creation and Maintenance of a Documentation Generator in an Applied Research Context;towards the Digitalization of Additive Manufacturing;Twenty Years of Successful Translational Research: A Case Study of Three COMET Centers;data Integration, Management, and Quality: From Basic Research to Industrial Application;building a YouTube Channel for Science Communication;introduction of Visual Regression Testing in Collaboration Between Industry and Academia;vibration Analysis for Rotatory Elements Wear Detection in Paper Mill Machine;applying Time-Inhomogeneous Markov Chains to Math Performance Rating;introducing data Science Techniques into a Company Producing Electrical Appliances;a Technology Transfer Portal to Promote Industry-Academia Collaboration in South-Tyrol;fast and Automatic Object Registration for Human-Robot Collaboration in Industrial Manufacturing;sending Spies as Insurance Against Bitcoin Pool Mining Block Withholding Attacks;risks in DeFi-Lending Protocols - An Exploratory Categorization and Analysis of Interest Rate Differences;battling the Bullwhip Effect with Cryptography;Reporting of Cross-Border Transactions for Tax Purposes via DLT;securing File System Integrity and Version History Via Directory Merkle Trees and Blockchains;taxation of Blockchain Staking Rewards: Propositions Based on a Comparative Legal Analysis;comparison Framework for Blockchain Interoperability Implementations;A Comparative Analysis of Anomaly Detection Methods for Predictive Maintenance in SME;towards Strategies for Secure data Transfer of IoT Devices with Limited Resources;application of Validation Obligations to Security Concerns;mode Switching for Secure Edge Devices;a Lifecycle Framework for Semantic Web Machine Learn

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EDDE: An Event-Driven data exchange to Accurately Introspect Cobot Applications 5

EDDE: An Event-Driven Data Exchange to Accurately Introspect...

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IEEE/ACM 5th International workshop on Robotics Software engineering (RoSE)

作者： Kolvig-Raun, Emil Stubbe Kjaergaard, Mikkel Baun Brorsen, Ralph Univ Southern Denmark Odense Denmark Univ Southern Denmark Ctr Software Engn Odense Denmark Universal Robots Odense Denmark

ISBN: (纸本)9798350301847

Commercialized collaborative robots (cobots) are typically programmed in proprietary languages and employ interfaces that gather data at predefined frequencies, such as the Real Time data exchange offered by Universal Robots (UR). This approach challenges the observability of program execution during runtime. To address this issue, the paper proposes applying software architectural knowledge from the introspection of Cyber-Physical Systems (CPSs) to the robotics domain. The proposed solution is to improve the classical protocol interfaces with an Event-Driven Architecture, enabling the acquisition of program events in relation to state variables and thus, richer information concerning runtime. The proposed architecture, called the Event-Driven data exchange, is implemented and evaluated on a UR e-Series cobot in a practical study. The study highlights the significance of implementing software architectural knowledge in CPSs, such as cobots to extend observability and data availability.

关键词： Event-Driven Architecture Industrial Automation Collaborative Robots Program Monitoring Debugging and Fault Localization data Collection Software Traceability

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Battalogy: Empowering Battery data Management through Ontology-driven knowledge Graph 3

Battalogy: Empowering Battery Data Management through Ontolo...

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Joint of the 3rd International workshop One knowledge Graph Generation from Text and data Quality Meets Machine Learning and knowledge Graphs, TEXT2KG 2024 and DQMLKG 2024

作者： Ismail, Muhamamd Fareedi, Abid Ali Nazir, Hammad Faculty of Computing Engineering and Sciences University of South Wales Treforest PontypriddCF37 1DL United Kingdom Halmstad University Halmstad Sweden

Developing a battery ontology to represent battery management knowledge is crucial in the new sustainable and green energy era. As battery production revenue is projected to exceed 300 billion US dollars annually by 2030, researchers are exploring new battery materials, models, standards, and manufacturing processes. AI and ML methods are being employed to manage battery manufacturing and enhance performance. data representation techniques and formats are important for enhancing the expressiveness of battery data and improving battery quality. This paper presents an ontology for creating a battery knowledge graph to address data interoperability challenges and share battery data among different actors. The battery ontology includes various types of knowledge, such as domain knowledge, battery applications, and core battery-specific knowledge. The ontology was evaluated through competency questions and usability tests. It aims to enhance battery production and design by facilitating efficient communication and data exchange between battery management systems and applications. This research has significant societal, economic, and environmental impacts as it contributes to developing more efficient and sustainable batteries. © 2024 Author.

关键词： knowledge graph

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GRANITE - EJEA: Europe meets Japan: Intercultural workshop on data Sovereignty and Generative AI : Applications, Design, Social, Ethical, and Technological Impact

GRANITE - EJEA: Europe meets Japan: Intercultural Workshop o...

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2024 Lock-in or log out? Wie digitale Souveranitat gelingt, INFORMATIK 2024

作者： Reiners, René Ganter-Richter, Sabine Frauhofer FIT Human-Centered Engineering & Design Schloss Birlinghoven 1 Sankt Augustin53757 Germany Wurzerstr. 136 Bonn53175 Germany

ISBN: (纸本)9783885797463

The workshop's primary goal is to bring together experts from academia and industry to discuss and develop new collaborative efforts with regard to the topics data souvereignty and generative AI. It serves as a platform to exchange knowledge, identify common challenges, and explore innovative solutions for Europe and Japan. The workshop is commonly organized by the GRANITE Network and the European-Japanese Experts Association (EJEA). GRANITE focuses on fostering global cooperation by creating a network of ambassadors in various fields of science and technology, whereas EJEA is dedicated to enhancing cooperation between Europe and Japan through various activities, including conferences, workshops, and research projects. On the European side, Fraunhofer FIT and the Network for Science play pivotal roles in driving the initiatives for both, GRANITE and EJEA. From Japan, the prefectures of Nagano and Kagawa are instrumental in facilitating the collaboration. © 2024 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Collaboration data Sovereignty Europe exchange Generative AI Japan Research

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Hearing the voice of experts: Unveiling Stack exchange communities' knowledge of test smells 16

Hearing the voice of experts: Unveiling Stack Exchange commu...

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16th IEEE/ACM International Conference on Cooperative and Human Aspects of Software engineering (CHASE)

作者： Martins, Luana Campos, Denivan Santana, Railana Mota Junior, Joselito Costa, Heitor Machado, Ivan Fed Univ Bahia UFBA Inst Comp Salvador BA Brazil Fed Univ Lavras UFLA Dept Comp Sci Lavras Brazil

ISBN: (纸本)9798350337341

Refactorings are transformations to improve the code design without changing overall functionality and observable behavior. During the refactoring process of smelly test code, practitioners may struggle to identify refactoring candidates and define and apply corrective strategies. This paper reports on an empirical study aimed at understanding how test smells and test refactorings are discussed on the Stack exchange network. Developers commonly count on Stack exchange to pick the brains of the wise, i.e., to 'look up' how others are completing similar tasks. Therefore, in light of data from the Stack exchange discussion topics, we could examine how developers understand and perceive test smells, the corrective actions they take to handle them, and the challenges they face when refactoring test code aiming to fix test smells. We observed that developers are interested in others' perceptions and hands-on experience handling test code issues. Besides, there is a clear indication that developers often ask whether test smells or anti-patterns are either good or bad testing practices than code-based refactoring recommendations.

关键词： Developer expertise stack exchange mining refactoring test smells

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Benchmarking Ontology Validation Capabilities of LLMs

Benchmarking Ontology Validation Capabilities of LLMs

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2024 Harmonising Generative AI and Semantic Web Technologies, HGAIS 2024

作者： Tsaneva, Stefani Herwanto, Guntur Budi Sabou, Marta Institute of Data Process and Knowledge Management Vienna University of Economics and Business Austria

With the advent of Generative AI, numerous approaches exploring large language models (LLMs) have been proposed for addressing a number of knowledge engineering (KE) tasks. Yet, the status of this research field is rather preliminary and there is, for now, no systematic and comprehensive understanding on how LLMs perform on selected knowledge engineering tasks (e.g., what is their expertise level in understanding ontology modeling concepts). Such insights would be crucial for researchers working in this field to support with selecting the most suitable LLMs during experiment design. This situation is exacerbated by the rapid expansion in the number of available LLMs. We therefore see the need for methodologies and tools that allow (comparatively) assessing LLM capabilities. To address this need, we propose the creation of an assessment test benchmark for evaluating the LLM knowledge engineering skills. We present ongoing work and preliminary results on assessing the expertise of LLMs in terms of a concrete KE task, namely ontology validation. Our experiments highlight the superiority of proprietary models on this task, particularly GPT-4o and Claude-Sonnet-3.5, over open source models. Lastly, we identify the need of a community-driven comparative LLM assessment platform that facilitates resource sharing and experience exchange, while protecting the integrity and privacy of the envisioned benchmark. We share (i) the current version of the qualification tests and (ii) its implementation for assessing LLM capabilities for ontology validation. © 2025 Copyright for this paper by its authors.

关键词： engineering research

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Realization of knowledge Service and Management System Based on data Mining Technology 6

Realization of Knowledge Service and Management System Based...

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6th International workshop on Advanced Algorithms and Control engineering, IWAACE 2022

作者： Yu, Chunli Jianghan University Hubei Wuhan China

ISBN: (纸本)9781510657755

Digital mining technology is a network information processing technology based on the perspective of big data analysis, and its important value in the construction of library knowledge service management system is prominent. This paper starts with the realization of the knowledge service and management system of university library under the digital mining technology, as well as the business flow and composition of the knowledge service and management system, and discusses how to improve its performance design and safety design, and realize the optimization service and management decision-making function of the system, to meet the needs of users for knowledge acquisition in the digital age, and to meet the greatest needs of teaching and research construction in colleges and universities. © 2022 SPIE.

关键词： data mining

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Towards a U.S. National Bridge and Infrastructure data Dictionary: An Introduction 11

Towards a U.S. National Bridge and Infrastructure Data Dicti...

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11th Linked data in Architecture and Construction workshop, LDAC 2023

作者： Costin, Aaron Muller, Marina M. E. Rinker Sr. School of Construction Management University of Florida 323 Rinker Hall P.O. Box 115703 GainesvilleFL32611 United States Stock Development Department of Construction Management Florida Gulf Coast University 10501 FGCU Blvd Fort MyersFL33965 United States

Building Information Modeling (BIM) has been gaining more acceptance outside of the traditional built environment. The U.S. transportation industry has recently adopted IFC as the standard data schema for the exchange of electronic engineering data. This is significant because the transportation agencies are progressing toward BIM as the successor to the standard plan set for highway infrastructure. Unfortunately, as previous studies indicate, IFC is currently limited in modeling the full capacity of bridges and infrastructure data exchange. Utilizing IFC P-Sets and ontology models have been the current workaround to enable the full information exchange. The challenge with properly modeling such ontologies is that the breadth of knowledge needing to be captured, from all the stakeholder perspectives and all bridge and infrastructure elements, is a large undertaking without the direct support from the industry. Additionally, each state agency has their own processes, terminology, and culture that further complicate the challenge. To mitigate these challenges, research has been ongoing to create a national data dictionary to support current US national efforts and promote alignment across the various state agencies. This paper presents an overview of the research and the methodology in creating a bridge and infrastructure data dictionary. Current limitations and open challenges are presented. As this work is still ongoing, the goal is to continue the development of the data dictionary in a collaborative effort to ensure that it can be extended to include other transportation structures. © 2023 Copyright for this paper by its authors.

关键词： Bridges

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Service-based tool lifecycle analysis based on AAS 57

Service-based tool lifecycle analysis based on AAS

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18th IFAC workshop on Time Delay Systems, TDS 2024

作者： Wurm, Steffen Lohrmann, Vincent Wieczorek, Michael Blanke, Philipp Fimmers, Christian Petrovic, Oliver Herfs, Werner RWTH Aachen University Laboratory for Machine Tools and Productioin Engineering Steinbachstr. 19 Aachen52074 Germany Siemens AG Frauenauracher Str. 80 Erlangen91056 Germany

Precise monitoring of production equipment and products is of fundamental importance for efficient and sustainable production. The focus here is not only on comprehensive data acquisition, but also on the interpretation and generation of added value in the form of knowledge and information. Continuous monitoring of machine or tool statuses, for example, enables predictions to be made for needs-based maintenance in order to minimize errors and production downtime. Both the data acquisition and the service applications for such use cases are already available today. One challenge, however, is the integration and consolidation of relevant information from different sources for individual assets such as products, machine tools or tools. The Asset Administration Shell (AAS) offers itself here as an interoperable data interface and semantically unique source of information. By integrating an AAS into service networks, various applications can be supplied with relevant input data. Important data is stored directly in the AAS and is generally accessible and interpretable thanks to the defined exchange format. This paper presents the development of an AAS including a software framework with various different service applications for monitoring tools in machining production. The AAS acts as a central interface between databases, wear analysis tool and visualization program (dashboard). © 2024 The Authors.

关键词： Interoperability

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ShipQuest: A Bottom-Up Approach for Building a Modern Greek Maritime Ontology 18

ShipQuest: A Bottom-Up Approach for Building a Modern Greek ...

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18th International workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2023

作者： Mathe, Eirini Mouratidis, Despoina Voutos, Yorghos Kermanidis, Katia Mylonas, Phivos Kanavos, Andreas Ionian University Department of Informatics Corfu Greece University of West Attica Department of Informatics and Computer Engineering Athens Greece

ISBN: (纸本)9798350327717

The ShipQuest Ontology is a pioneering legal maritime ontology designed for modeling and integrating legal information in the Greek language. This standardized representation of legal concepts within the maritime domain offers a structured approach to managing legal data. By formalizing legal information in Greek, the ShipQuest Ontology ensures semantic interoperability and seamless integration of diverse legal data sources. It encompasses essential classes, subclasses, properties, and relationships pertaining to legal aspects of maritime activities, including legal entities, contracts, regulations, liabilities, and more. The ShipQuest Ontology plays a critical role in stream-lining legal operations within the maritime industry, offering a unified and comprehensive knowledge base for legal practitioners, researchers, and decision-makers. Its adoption fosters collaboration and knowledge exchange within the maritime community, promoting standardized legal terminology and practices. This paper delves into the construction and utilization of the ShipQuest Ontology, detailing its architecture, development process, and implementation. Furthermore, we showcase its practical benefits by illustrating its application in real-world scenarios. By addressing the challenges of legal data heterogeneity and facilitating semantic consistency, the ShipQuest Ontology sets a precedent for enhanced efficiency and effectiveness in the legal domain of maritime activities. © 2023 IEEE.

关键词： Ontology

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