Unified Foundational Ontology

Last updated

The Unified Foundational Ontology (UFO). [1] [2] is an ontological framework developed in the early 2000s with the objective of providing foundational support for conceptual modeling. It synthesizes elements from formal ontology, cognitive science, linguistics, and philosophical logic to inform the structure and semantics of conceptual models. The ontology is utilized to articulate a variety of fundamental notions within conceptual modeling, offering a systematic approach to categorizing entities and delineating their properties.

Contents

Overview

Conceived as a response to the needs for ontological foundations in conceptual modeling, UFO consists of a series of interlinked micro-theories that collectively address a comprehensive range of conceptual modeling topics. These micro-theories cover the taxonomy of objects, the nature of part-whole relationships, the articulation of intrinsic and relational properties, and the classification of events and roles among other subjects. UFO is particularly noted for its application in the creation of OntoUML, a conceptual modeling language that embodies the ontology's theoretical constructs.

UFO's development is deeply rooted in philosophical ontology, integrating insights from formal ontology, cognitive science, linguistics, and philosophical logic. This multidisciplinary approach ensures that UFO not only provides a theoretical framework for conceptual modeling but also aligns closely with human cognitive processes and linguistic structures. This alignment is crucial in ensuring that the ontology is both intuitively understandable and practically applicable in various domains. [3]

Recent discussions in the field, such as those presented by Riichiro Mizoguchi and Stefano Borgo in 'The Role of the Systemic View in Foundational Ontologies', emphasize the significance of incorporating a systemic view within foundational ontologies. This perspective is crucial in understanding how entities, as part of a larger system, interact and function dynamically. The systemic view, which focuses on the roles entities play within a system and how they contribute to the system's overall goals and functions, can provide valuable insights into enhancing UFO's framework, particularly in modeling complex interactions and dynamic processes. [4]

Micro-theories

UFO emerged from an endeavor to harmonize theories from formal ontology with the requisites of ontological foundations for conceptual modeling. It incorporates a four-category ontology dealing with various fundamental conceptual modeling notions. The ontology is divided into several micro-theories covering a wide range of topics, including:

Each theory forms a part of the extensive conceptual framework offered by the ontology, contributing to a deeper understanding and analysis of domain-specific models.

Initially inspired by seminal work on ontological foundations for conceptual modeling, UFO aimed to address the shortcomings of previous approaches by developing a robust ontological theory for conceptual modeling that encompasses both individuals and types. Over the years, UFO has evolved significantly, being applied in the analysis, re-engineering, and integration of various modeling languages and standards across different domains. However, the extensive scope of UFO's micro-theories, though academically robust, presents challenges in terms of usability and comprehension, especially for those without a formal background in ontology.

Notably, UFO has been used in the design of an ontology-driven conceptual modeling language known as OntoUML, [12] which reflects some of the ontological micro-theories comprising UFO.

Principles and Structure of UFO

UFO was established with the goal of supporting domain analysis in conceptual modeling, aiming at developing a "Calculus of Content" for ontological analysis, conceptual clarification, and semantic explicitation of content embedded in representation artifacts.

UFO seeks to describe reality at a mesoscopic level as accounted for by human cognition, acknowledging both cognitive and linguistic aspects in its constituting categories. It is organized into three main fragments:

The ontology distinguishes between endurants and perdurants, with endurants being individuals that exist in time with all their parts, and perdurants being individuals that unfold in time accumulating temporal parts. It also accounts for both independent and dependent endurants, termed substantials and moments, respectively.

UFO further delves into the categorization of endurant types based on the Aristotelian Square, accounting for both substantials and moments, which include intrinsic moments like qualities and modes, and particularized relational properties termed relators.

Key Research Groups

UFO has garnered attention and application across various research groups globally. Prominent among them is the Ontology and Conceptual Modeling Research Group (NEMO) based at the Federal University of Espírito Santo in Brazil. NEMO focuses on developing foundational theories and applying them to complex information systems. [15] The Semantics, Cybersecurity and Services (SCS) group at the University of Twente in the Netherlands employs UFO to address enterprise modeling and the alignment of business and IT systems. [16] Additionally, various interdisciplinary groups, such as those within bioinformatics and healthcare informatics, leverage UFO to develop domain ontologies for more precise data representation and reasoning. These collaborative efforts underscore UFO's prominence in the field of conceptual modeling and ontology engineering.

Ontology Usage and Community Impact

Over the years, UFO has found extensive use in the development of core and domain ontologies across a multitude of domains, in both academic and practical contexts. [1] Its application spans from natural sciences like agriculture and bioinformatics to purely informational domains like telecommunications and game design, as well as practical environmental management problems such as land covering and waste management simulations. Moreover, UFO has been instrumental in analyzing, reengineering, or integrating many modeling languages and standards in different domains.

Since its inception in the early 2000s, UFO has evolved to address the growing complexities and requirements of conceptual modeling. Its influence extends beyond the academic realm, impacting practical applications in various industries. UFO's comprehensive approach to modeling entities, their properties, and interrelations has made it a foundational framework in ontology engineering, influencing the development of other ontologies and modeling languages. [17]

One of the most influential applications of UFO has been in the design of the conceptual modeling language OntoUML and its ecosystem of methodological and computational tools. Studies highlight UFO as a rapidly adopted foundational ontology in conceptual modeling, with OntoUML being among the most used languages in ontology-driven conceptual modeling. Empirical evidence suggests that OntoUML significantly contributes to improving the quality of conceptual models without necessitating additional effort in their production.

The development of UFO-based models through OntoUML is currently facilitated by a microservice-based infrastructure known as OntoUML as a Service (OaaS). This infrastructure decouples model services developed by OntoUML researchers from the modeling tools they support, allowing for independent development and later integration into modeling tools like UML CASE tools.

Besides OntoUML, UFO has also been employed in the design of numerous ontologies in various sub-domains in Software Engineering, forming the Software Engineering Ontology Network (SEON), which addresses problems like application integration, semantic annotation of requirements, software quality assurance, and code interoperability among others.

Furthermore, UFO has made a noticeable impact in domains dealing with legal, social, and economic aspects, including financial accounting, legal relations, and contracts, as well as microeconomic sub-domains. Its robust theory of relations has found to be particularly useful in these domains, catering to the sophisticated modeling of relational aspects required therein. While UFO's role in the development of OntoUML and its application in various domains is notable, discussions continue regarding the extent of its practical impact and adoption in non-academic settings.

The Unified Foundational Ontology (UFO) has been notably discussed in the "Foundational Ontologies in Action" issue of Applied Ontology, highlighting its practical applications and challenges. This discussion is part of the FOUST project, which aims to bridge gaps in applied ontology by bringing together designers of major foundational ontologies, including UFO. The project focuses on concrete use-cases, emphasizing the need for consistent modeling methodologies and the importance of understanding different logical languages and formal consistency in ontological systems. This structured approach underlines UFO's effectiveness in diverse domains, particularly in modeling object properties, social situations, and the representation of artifacts and their components [18]

Criticism

Despite UFO's influence in research and ontology development, its theoretical density and complexity have been identified as barriers to its wider adoption and practical application. Critics have pointed out that UFO, like other ontological frameworks, may suffer from issues of complexity and abstractness that can hinder its practical application. Some argue that the rich theoretical underpinnings, while academically rigorous, can make it difficult for practitioners to adopt without extensive training. This complexity can lead to challenges in implementation, particularly in interdisciplinary projects where stakeholders may not have a background in formal ontology.

The Unified Foundational Ontology's ambitious scope and depth, while contributing significantly to academic discourse, have led to criticisms regarding its abstract nature and the challenges it poses for practical application, particularly in interdisciplinary projects. It stands as a significant academic contribution to conceptual modeling, yet it continues to navigate the challenges of balancing theoretical rigor with practical usability in diverse domains.

Related Research Articles

In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.

<span class="mw-page-title-main">Data model</span> Model that organizes elements of data and how they relate to one another and to real-world entities.

A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner.

A modeling language is any artificial language that can be used to express data, information or knowledge or systems in a structure that is defined by a consistent set of rules. The rules are used for interpretation of the meaning of components in the structure of a programing language.

<span class="mw-page-title-main">Information model</span>

An information model in software engineering is a representation of concepts and the relationships, constraints, rules, and operations to specify data semantics for a chosen domain of discourse. Typically it specifies relations between kinds of things, but may also include relations with individual things. It can provide sharable, stable, and organized structure of information requirements or knowledge for the domain context.

Domain-specific modeling (DSM) is a software engineering methodology for designing and developing systems, such as computer software. It involves systematic use of a domain-specific language to represent the various facets of a system.

The term conceptual model refers to any model that is formed after a conceptualization or generalization process. Conceptual models are often abstractions of things in the real world, whether physical or social. Semantic studies are relevant to various stages of concept formation. Semantics is fundamentally a study of concepts, the meaning that thinking beings give to various elements of their experience.

<span class="mw-page-title-main">Domain model</span> A model in software engineering

In software engineering, a domain model is a conceptual model of the domain that incorporates both behavior and data. In ontology engineering, a domain model is a formal representation of a knowledge domain with concepts, roles, datatypes, individuals, and rules, typically grounded in a description logic.

In information science, an upper ontology is an ontology that consists of very general terms that are common across all domains. An important function of an upper ontology is to support broad semantic interoperability among a large number of domain-specific ontologies by providing a common starting point for the formulation of definitions. Terms in the domain ontology are ranked under the terms in the upper ontology, e.g., the upper ontology classes are superclasses or supersets of all the classes in the domain ontologies.

In computer science and artificial intelligence, ontology languages are formal languages used to construct ontologies. They allow the encoding of knowledge about specific domains and often include reasoning rules that support the processing of that knowledge. Ontology languages are usually declarative languages, are almost always generalizations of frame languages, and are commonly based on either first-order logic or on description logic.

Model-driven engineering (MDE) is a software development methodology that focuses on creating and exploiting domain models, which are conceptual models of all the topics related to a specific problem. Hence, it highlights and aims at abstract representations of the knowledge and activities that govern a particular application domain, rather than the computing concepts.

The general formal ontology (GFO) is an upper ontology integrating processes and objects. GFO has been developed by Heinrich Herre, Barbara Heller and collaborators in Leipzig. Although GFO provides one taxonomic tree, different axiom systems may be chosen for its modules. In this sense, GFO provides a framework for building custom, domain-specific ontologies. GFO exhibits a three-layered meta-ontological architecture consisting of an abstract top level, an abstract core level, and a basic level. Primarily, the ontology GFO:

Executable UML is both a software development method and a highly abstract software language. It was described for the first time in 2002 in the book "Executable UML: A Foundation for Model-Driven Architecture". The language "combines a subset of the UML graphical notation with executable semantics and timing rules." The Executable UML method is the successor to the Shlaer–Mellor method.

In philosophy, the term formal ontology is used to refer to an ontology defined by axioms in a formal language with the goal to provide an unbiased view on reality, which can help the modeler of domain- or application-specific ontologies to avoid possibly erroneous ontological assumptions encountered in modeling large-scale ontologies.

DOGMA, short for Developing Ontology-Grounded Methods and Applications, is the name of research project in progress at Vrije Universiteit Brussel's STARLab, Semantics Technology and Applications Research Laboratory. It is an internally funded project, concerned with the more general aspects of extracting, storing, representing and browsing information.

<span class="mw-page-title-main">ArchiMate</span> Enterprise architecture modeling language

ArchiMate is an open and independent enterprise architecture modeling language to support the description, analysis and visualization of architecture within and across business domains in an unambiguous way.

<span class="mw-page-title-main">Ontology engineering</span> Field that studies the methods and methodologies for building ontologies

In computer science, information science and systems engineering, ontology engineering is a field which studies the methods and methodologies for building ontologies, which encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities of a given domain of interest. In a broader sense, this field also includes a knowledge construction of the domain using formal ontology representations such as OWL/RDF. A large-scale representation of abstract concepts such as actions, time, physical objects and beliefs would be an example of ontological engineering. Ontology engineering is one of the areas of applied ontology, and can be seen as an application of philosophical ontology. Core ideas and objectives of ontology engineering are also central in conceptual modeling.

The triune continuum paradigm is a paradigm for general system modeling published in 2002. The paradigm allows for building of rigorous conceptual frameworks employed for systems modeling in various application contexts.

OntoUML is an ontologically a language for Ontology-driven Conceptual Modeling. OntoUML is built as a UML extension based on the Unified Foundational Ontology (UFO). The foundations of UFO and OntoUML can be traced back to Giancarlo Guizzardi's Ph.D. thesis "Ontological foundations for structural conceptual models". In his work, he proposed a novel foundational ontology for conceptual modeling (UFO) and employed it to evaluate and re-design a fragment of the UML 2.0 metamodel for the purposes of conceptual modeling and domain ontology engineering.

<span class="mw-page-title-main">Menthor Editor</span>

Menthor Editor is a no longer maintained free ontology engineering tool for dealing with OntoUML models. It included OntoUML syntax validation, Alloy simulation, Anti-Pattern verification, and MDA transformations from OntoUML to OWL, SBVR and Natural Language.

<span class="mw-page-title-main">Giancarlo Guizzardi</span> Brazilian–Italian computer scientist

Giancarlo Guizzardi is a Brazilian–Italian computer scientist specializing in conceptual modeling, enterprise modeling, applied ontology and ontology-driven information systems. He is a professor at the University of Twente, in The Netherlands, and a senior researcher and founding member of the Ontology & Conceptual Modeling Research Group (NEMO) in Vitoria, Brazil.

References

  1. 1 2 Guizzardi, Giancarlo; Botti Benevides, Alessander; Fonseca, Claudenir M.; Porello, Daniele; Almeida, João Paulo A.; Prince Sales, Tiago (2022-01-01). "UFO: Unified Foundational Ontology". Applied Ontology. 17 (1): 167–210. doi:10.3233/AO-210256. ISSN   1570-5838. S2CID   244875087.
  2. ↑ Guizzardi, Giancarlo; Wagner, Gerd; Almeida, João Paulo Andrade; Guizzardi, Renata S. S. (2015-01-01). "Towards ontological foundations for conceptual modeling: The unified foundational ontology (UFO) story". Applied Ontology. 10 (3–4): 259–271. doi:10.3233/AO-150157. ISSN   1570-5838.
  3. ↑ Partridge, Chris; Mitchell, Andrew; Cook, Al; Sullivan, Jan; West, Matthew (2020-10-31). "A Survey of Top-Level Ontologies - to inform the ontological choices for a Foundation Data Model".{{cite journal}}: Cite journal requires |journal= (help)
  4. ↑ "CEUR-WS.org/Vol-2969 - The Joint Ontology Workshops 2021". ceur-ws.org. Retrieved 2023-12-11.
  5. ↑ Guizzardi, Giancarlo; Fonseca, Claudenir M.; Almeida, João Paulo A.; Sales, Tiago Prince; Benevides, Alessander Botti; Porello, Daniele (2021-07-01). "Types and taxonomic structures in conceptual modeling: A novel ontological theory and engineering support". Data & Knowledge Engineering. 134: 101891. doi:10.1016/j.datak.2021.101891. ISSN   0169-023X. S2CID   236574719.
  6. ↑ Guizzardi, Giancarlo; Zamborlini, Veruska (2014-12-15). "Using a trope-based foundational ontology for bridging different areas of concern in ontology-driven conceptual modeling". Science of Computer Programming. Selected Papers from the Fifth International Conference on Software Language Engineering (SLE 2012). 96: 417–443. doi: 10.1016/j.scico.2014.02.022 . ISSN   0167-6423.
  7. ↑ Albuquerque, Antognoni; Guizzardi, Giancarlo (2013). An ontological foundation for conceptual modeling datatypes based on semantic reference spaces. pp. 1–12. doi:10.1109/RCIS.2013.6577693. ISBN   978-1-4673-2914-9. S2CID   1358455 . Retrieved 2023-10-06– via ieeexplore.ieee.org.
  8. ↑ Fonseca, Claudenir M.; Porello, Daniele; Guizzardi, Giancarlo; Almeida, João Paulo A.; Guarino, Nicola (2019). "Relations in Ontology-Driven Conceptual Modeling". In Laender, Alberto H. F.; Pernici, Barbara; Lim, Ee-Peng; de Oliveira, José Palazzo M. (eds.). Conceptual Modeling. Lecture Notes in Computer Science. Vol. 11788. Cham: Springer International Publishing. pp. 28–42. doi:10.1007/978-3-030-33223-5_4. ISBN   978-3-030-33223-5. S2CID   204944872.
  9. ↑ "On Weak Truthmaking". bia.unibz.it. Retrieved 2023-10-06.
  10. ↑ Almeida, João Paulo A.; Falbo, Ricardo A.; Guizzardi, Giancarlo (2019). "Events as Entities in Ontology-Driven Conceptual Modeling". In Laender, Alberto H. F.; Pernici, Barbara; Lim, Ee-Peng; de Oliveira, José Palazzo M. (eds.). Conceptual Modeling. Lecture Notes in Computer Science. Vol. 11788. Cham: Springer International Publishing. pp. 469–483. doi:10.1007/978-3-030-33223-5_39. ISBN   978-3-030-33223-5. S2CID   204945554.
  11. ↑ Fonseca, Claudenir M.; Almeida, João Paulo A.; Guizzardi, Giancarlo; Carvalho, Victorio A. (2021-07-01). "Multi-level conceptual modeling: Theory, language and application". Data & Knowledge Engineering. 134: 101894. doi:10.1016/j.datak.2021.101894. ISSN   0169-023X. S2CID   236555246.
  12. 1 2 Guizzardi, Giancarlo (2005-10-27). Ontological foundations for structural conceptual models (PhD Thesis).
  13. ↑ Botti Benevides, Alessander; Bourguet, Jean-Rémi; Guizzardi, Giancarlo; Peñaloza, Rafael; Almeida, João Paulo A. (2019-01-01). "Representing a reference foundational ontology of events in SROIQ". Applied Ontology. 14 (3): 293–334. doi:10.3233/AO-190214. ISSN   1570-5838. S2CID   198314572.
  14. ↑ Bringuente, Ana Christina de Oliveira; Falbo, Ricardo de Almeida; Guizzardi, Giancarlo (2011-10-04). "Using a Foundational Ontology for Reengineering a Software Process Ontology". Journal of Information and Data Management. 2 (3): 511. doi:10.5753/jidm.2011.1424 (inactive 31 January 2024). ISSN   2178-7107.{{cite journal}}: CS1 maint: DOI inactive as of January 2024 (link)
  15. ↑ "Nemo" (in Brazilian Portuguese). Retrieved 2023-11-07.
  16. ↑ "The Foundational Ontology UFO and the OntoUML modeling Language" (PDF). Semantics, Cybersecurity and Services group. University of Twente. Retrieved 2023-11-07.
  17. ↑ Partridge, Chris; Mitchell, Andrew; Cook, Al; Sullivan, Jan; West, Matthew (2020-10-31). "A Survey of Top-Level Ontologies - to inform the ontological choices for a Foundation Data Model".{{cite journal}}: Cite journal requires |journal= (help)
  18. ↑ Borgo, Stefano; Galton, Antony; Kutz, Oliver; Borgo, Stefano; Galton, Antony; Kutz, Oliver (2022-01-01). "Foundational ontologies in action". Applied Ontology. 17 (1): 1–16. doi: 10.3233/AO-220265 . ISSN   1570-5838.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.