Ontological Prisms: Knowledge Engineering for Enterprise & Agentic Systems
暫譯: 本體棱鏡:企業與智能系統的知識工程
Fannader, Remy
商品描述
Ontological Prisms
The expansion of generative AI has highlighted the limitations of purely neural approaches and the benefits of coupling them with symbolic counterparts epitomized by ontologies. While knowledge graphs emerge as the jack of all trades among agents dealing with language, knowledge, and orchestration, there is little consensus on the sources and roles of ontologies, in other words, knowledge.
The book introduces ontological prisms, a game-changing paradigm that unfolds the geometry of knowledge into a triptych of observed worlds (facts), meanings (concepts), and shared representations (categories).
This approach entails three major breakthroughs with regard to:
- Interoperability: by establishing a principled and actionable distinction between communication (language) and representation (knowledge), ontological prisms provide a blueprint for semantic and conceptual layers set across heterogeneous representations
- Abstraction levels: leveraging its three-pronged paradigm, ontological prisms untangle the abstraction conundrum between upper (or foundational) and lower (or domain-specific) level ontologies. This allows for a smooth, declarative integration of ontological abstractions without imposing unwieldy inheritance hierarchies
- Temporality: the epistemic distinction between worlds (facts), intents (concepts), and representations (categories), combined with differentiated abstraction semantics, enables diachronic knowledge management alongside concurrent engineering processes, regardless of domain overlaps and misaligned life cycles
These advances allow for a seamless integration of knowledge engineering between agentic and enterprise systems: facts, categories, and concepts for the former, mapped to data, information, and knowledge for the latter, respectively. That knowledge-driven integration of cognitive and systems capabilities paves the way to a holistic approach to collective learning weaving together individuals, organizations, and systems.
The book is organized into three parts: principles, foundations, and architecture; cognitive functions: language, reasoning, and judgment; and systems and knowledge engineering. The third part introduces the KEOPS (Knowledge Engineering with Ontological Prisms) methodology, accompanied by a kernel developed with OWL/Prot g .
This organization allows for differentiated readings for graduates, engineers, and consultants, ensuring a comprehensive understanding of agentic cognition, knowledge engineering and ontology development, as well as business intelligence and decision-making systems.
商品描述(中文翻譯)
**本體棱鏡**
生成式人工智慧的擴展突顯了純神經方法的局限性,以及將其與以本體為代表的符號對應物結合的好處。儘管知識圖譜在處理語言、知識和協調的代理中被視為萬能工具,但對於本體的來源和角色,即知識,卻鮮有共識。
本書介紹了本體棱鏡,這是一種顛覆性的範式,將知識的幾何結構展開為觀察世界(事實)、意義(概念)和共享表徵(類別)的三聯畫。
這種方法涉及三個主要突破,具體包括:
- 互操作性:通過建立溝通(語言)和表徵(知識)之間的原則性和可行的區分,本體棱鏡提供了一個語義和概念層的藍圖,這些層次分佈於異質表徵之間。
- 抽象層次:利用其三重範式,本體棱鏡解開了上層(或基礎)本體與下層(或特定領域)本體之間的抽象難題。這使得本體抽象的平滑、聲明式整合成為可能,而不必強加繁瑣的繼承層級。
- 時序性:世界(事實)、意圖(概念)和表徵(類別)之間的認識區分,結合差異化的抽象語義,使得在領域重疊和生命週期不一致的情況下,能夠進行歷時性的知識管理與並行工程過程。
這些進展使得代理系統與企業系統之間的知識工程實現無縫整合:前者的事實、類別和概念,分別映射到後者的數據、信息和知識。這種以知識為驅動的認知與系統能力的整合,為個人、組織和系統之間的集體學習提供了一種整體方法。
本書分為三個部分:原則、基礎和架構;認知功能:語言、推理和判斷;以及系統與知識工程。第三部分介紹了KEOPS(使用本體棱鏡的知識工程)方法論,並附有使用OWL/Protégé開發的核心。
這種組織方式使得畢業生、工程師和顧問能夠進行差異化的閱讀,確保對代理認知、知識工程和本體開發,以及商業智能和決策系統的全面理解。
作者簡介
Rémy Fannader is an IT professional with a background in artificial intelligence and economics, bringing over 35 years of consulting experience across banking, insurance, and software engineering. He has contributed to European Union research projects and published four books and more than two hundred in-depth articles on systems modeling, enterprise architecture, AI, and knowledge management.
作者簡介(中文翻譯)
Rémy Fannader 是一位擁有人工智慧和經濟學背景的 IT 專業人士,擁有超過 35 年的顧問經驗,涵蓋銀行、保險和軟體工程領域。他曾參與歐洲聯盟的研究專案,並出版了四本書籍以及超過兩百篇有關系統建模、企業架構、人工智慧和知識管理的深入文章。