Procedural knowledge management in Industry 5.0: Challenges and opportunities for knowledge graphs

被引:0
作者
Celino, Irene [1 ]
Carriero, Valentina Anita [1 ]
Azzini, Antonia [1 ]
Baroni, Ilaria [1 ]
Scrocca, Mario [1 ]
机构
[1] Cefriel, Viale Sarca 226, I-20126 Milan, Italy
来源
JOURNAL OF WEB SEMANTICS | 2025年 / 84卷
关键词
Procedural knowledge; Industry; 5.0; Knowledge graphs; Artificial Intelligence;
D O I
10.1016/j.websem.2024.100850
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With digital transformation, industrial companies today are facing the challenges to change and innovate their business, by leveraging digital technologies and tools to support their processes and their operations. One of their main challenges is the management of the company knowledge, especially when tacit and owned by industry workers. In this paper, we illustrate how knowledge graphs can be the turning point to allow industry workers digitize and exploit the knowledge about the "what'', the "how"and the "why"of their everyday activities. In particular, we focus on the "how"by illustrating the challenges related to procedural knowledge management, i.e., the knowledge about processes and workflows that employees need to follow, and comply with, to correctly execute their tasks, in order to improve efficiency and effectiveness, to reduce risks and human errors and to optimize operations. We also explain the relationship in this context between knowledge graphs and sub-symbolic AI approaches.
引用
收藏
页数:8
相关论文
共 49 条
  • [1] Ala-Pietila P., 2019, The Assessment List for Trustworthy Artificial Intelligence (ALTAI)
  • [2] Allen B.P., 2024, Trans. Graph Data Knowl, V1, DOI [10.4230/TGDK.2.1.5, DOI 10.4230/TGDK.2.1.5]
  • [3] Ammann L, 2024, Arxiv, DOI arXiv:2407.02106
  • [4] Baroni I., 2022, Human Comput., V9, P1, DOI [10.15346/hc.v9i1.134, DOI 10.15346/HC.V9I1.134]
  • [5] Extracting Business Process Entities and Relations from Text Using Pre-trained Language Models and In-Context Learning
    Bellan, Patrizio
    Dragoni, Mauro
    Ghidini, Chiara
    [J]. ENTERPRISE DESIGN, OPERATIONS, AND COMPUTING, EDOC 2022, 2022, 13585 : 182 - 199
  • [6] Bio2RDF: Towards a mashup to build bioinformatics knowledge systems
    Belleau, Francois
    Nolin, Marc-Alexandre
    Tourigny, Nicole
    Rigault, Philippe
    Morissette, Jean
    [J]. JOURNAL OF BIOMEDICAL INFORMATICS, 2008, 41 (05) : 706 - 716
  • [7] A Lifecycle Framework for Semantic Web Machine Learning Systems
    Breit, Anna
    Waltersdorfer, Laura
    Ekaputra, Fajar J.
    Miksa, Tomasz
    Sabou, Marta
    [J]. DATABASE AND EXPERT SYSTEMS APPLICATIONS, DEXA 2022 WORKSHOPS, 2022, 1633 : 359 - 368
  • [8] Carriero V.A., 2024, P 24 INT C KNOWL ENG
  • [9] ArCo: The Italian Cultural Heritage Knowledge Graph
    Carriero, Valentina Anita
    Gangemi, Aldo
    Mancinelli, Maria Letizia
    Marinucci, Ludovica
    Nuzzolese, Andrea Giovanni
    Presutti, Valentina
    Veninata, Chiara
    [J]. SEMANTIC WEB - ISWC 2019, PT II, 2019, 11779 : 36 - 52
  • [10] Submitting surveys via a conversational interface: An evaluation of user acceptance and approach effectiveness
    Celino, Irene
    Calegari, Gloria Re
    [J]. INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 2020, 139