Procedural Knowledge Ontology (PKO)
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866918232759205888 |
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| author | Carriero, Valentina Anita Scrocca, Mario Baroni, Ilaria Azzini, Antonia Celino, Irene |
| author_facet | Carriero, Valentina Anita Scrocca, Mario Baroni, Ilaria Azzini, Antonia Celino, Irene |
| contents | Processes, workflows and guidelines are core to ensure the correct functioning of industrial companies: for the successful operations of factory lines, machinery or services, often industry operators rely on their past experience and know-how. The effect is that this Procedural Knowledge (PK) remains tacit and, as such, difficult to exploit efficiently and effectively. This paper presents PKO, the Procedural Knowledge Ontology, which enables the explicit modeling of procedures and their executions, by reusing and extending existing ontologies. PKO is built on requirements collected from three heterogeneous industrial use cases and can be exploited by any AI and data-driven tools that rely on a shared and interoperable representation to support the governance of PK throughout its life cycle. We describe its structure and design methodology, and outline its relevance, quality, and impact by discussing applications leveraging PKO for PK elicitation and exploitation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_20634 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Procedural Knowledge Ontology (PKO) Carriero, Valentina Anita Scrocca, Mario Baroni, Ilaria Azzini, Antonia Celino, Irene Artificial Intelligence Processes, workflows and guidelines are core to ensure the correct functioning of industrial companies: for the successful operations of factory lines, machinery or services, often industry operators rely on their past experience and know-how. The effect is that this Procedural Knowledge (PK) remains tacit and, as such, difficult to exploit efficiently and effectively. This paper presents PKO, the Procedural Knowledge Ontology, which enables the explicit modeling of procedures and their executions, by reusing and extending existing ontologies. PKO is built on requirements collected from three heterogeneous industrial use cases and can be exploited by any AI and data-driven tools that rely on a shared and interoperable representation to support the governance of PK throughout its life cycle. We describe its structure and design methodology, and outline its relevance, quality, and impact by discussing applications leveraging PKO for PK elicitation and exploitation. |
| title | Procedural Knowledge Ontology (PKO) |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2503.20634 |