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In both applied ontology and engineering, functionality is a well-researched topic, since it is through teleological causal reasoning that domain experts build mental models of engineering systems, giving birth to functions. These mental models are important throughout the whole lifecycle of any product, being used from the design phase up to diagnosis activities. Though a vast amount of work to model functions has already been carried out, the literature has not settled on a shared and well-defined approach due to the variety of concepts involved and the modeling tasks that functional descriptions should satisfy. The work in this paper posits the basis and makes some crucial steps towards a rich ontological description of functions and related concepts, such as behaviour, capability, and capacity. A conceptual analysis of such notions is carried out using the top-level ontology DOLCE as a framework, and the ensuing logical theory is formally described in first-order logic and OWL, showing how ontological concepts can model major aspects of engineering products in applications. In particular, it is shown how functions can be distinguished from the implementation methods to realize them, how one can differentiate between capabilities and capacities of a product, and how these are related to engineering functions. [ABSTRACT FROM AUTHOR]

The development of artificial agents for social interaction pushes to enrich robots with social skills and knowledge about (local) social norms. One possibility is to distinguish the expressive and the functional orders during a human-robot interaction. The overarching aim of this work is to set a framework to make the artificial agent socially-competent beyond dyadic interaction – interaction in varying multi-party social situations – and beyond individual-based user personalization, thereby enlarging the current conception of "culturally-adaptive". The core idea is to provide the artificial agent with the capability to handle different kinds of interactional disruptions, and associated recovery strategies, in microsociology. The result is obtained by classifying functional and social disruptions, and by investigating the requirements a robot's architecture should satisfy to exploit such knowledge. The paper also highlights how this level of competence is achieved by focusing on just three dimensions: (i) social capability, (ii) relational role, and (iii) proximity, leaving aside the further complexity of full-fledged human-human interactions. Without going into technical aspects, End-to-end Data-driven Architectures and Modular Architectures are discussed to evaluate the degree to which they can exploit this new set of social and cultural knowledge. Finally, a list of general requirements for such agents is proposed. [ABSTRACT FROM AUTHOR]

Keywords: Foundational ontologies; upper ontologies; BFO; DOLCE; GFO; GUM; TUpper; UFO; YAMATO EN Foundational ontologies upper ontologies BFO DOLCE GFO GUM TUpper UFO YAMATO 1 16 16 04/07/22 20220101 NES 220101 Understanding foundational ontology through examples 1. The final FOUST template, followed by all contributions, has the following core structure, where we use I O i to denote generically some foundational ontology: Introduction: I An introduction to the ontology, together with some historical background and motivations i . Upper ontologies, BFO, DOLCE, GFO, GUM, TUpper, UFO, YAMATO, Foundational ontologies The TUpper Ontology has developed quite recently since around 2017 (Grüninger et al., [16]) and is designed as a top-level ontology that contains modules from ontologies within existing international standards, extended so as to satisfy the criteria for top level ontologies specified in ISO/IEC 21838-1. In developing ontologies for application to information systems, however, researchers have often taken pains to draw a line between what they are doing and philosophical ontology, on the grounds that the goals of the two enterprises are quite different, with applied ontology answerable to pragmatic concerns supposedly absent from purely philosophical pursuits. [Extracted from the article]

GUM is a linguistically-motivated ontology originally developed to support natural language processing systems by offering a level of representation intermediate between linguistic forms and domain knowledge. Whereas modeling decisions for individual domains may need to be responsive to domain-specific criteria, a linguistically-motivated ontology offers a characterization that generalizes across domains because its design criteria are derived independently both of domain and of application. With respect to this mediating role, the use of GUM resembles (and partially predates) the adoption of upper ontologies as tools for mediating across domains and for supporting domain modeling. This paper briefly introduces the ontology, setting out its origins, design principles and applications. The example cases for this special issue are then described, illustrating particularly some of the principal differences and similarities of GUM to non-linguistically motivated upper ontologies. [ABSTRACT FROM AUTHOR]

yamato sharply distinguishes itself from other existing upper ontologies in the following respects. (1) Most importantly, yamato is designed with both engineering and philosophical minds. (2) yamato is based on a sophisticated theory of roles, given that the world is full of roles. (3) yamato has a tenable theory of functions which helps to deal with artifacts effectively. (4) Information is a 'content-bearing' entity and it differs significantly from the entities that philosophers have traditionally discussed. Taking into account the modern society in which a flood of information occurs, yamato has a sophisticated theory of informational objects (representations). (5) Quality and quantity are carefully organized for the sake of greater interoperability of real-world data. (6) The philosophical contribution of yamato includes a theory of objects, processes, and events. Those features are illustrated with several case studies. These features lead to the intensive application of yamato in some domains such as biomedicine and learning engineering. [ABSTRACT FROM AUTHOR]

dolce, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources (e.g. CIDOC CRM, DBpedia and WordNet). Being a foundational ontology, dolce is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years dolce has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases. [ABSTRACT FROM AUTHOR]

Upper ontologies have traditionally arisen from the approach in which concepts that are common across a set of domains can be axiomatized at a general level. The rationale is that reuse across domains is to be supported through specialization of the general concepts from an upper ontology. Similarly, semantic integration between ontologies is to be achieved through the general concepts they specialize. The TUpper Ontology follows an alternative approach (referred to as the sideways approach) to the conventional upper ontology paradigm. Rather than think of an upper ontology as a monolithic axiomatization centred on a taxonomy, the sideways approach considers an upper ontology to be a modular ontology composed of generic ontologies that cover concepts including those related to time, process, and space. TUpper is therefore composed of a set of generic ontologies, and each generic ontology axiomatizes a particular set of generic concepts (e.g., the classes and relations relevant for time, process, and space). The TUpper Ontology is designed as a top-level ontology that contains modules from the ontologies within existing international standards. [ABSTRACT FROM AUTHOR]

dolce, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources (e.g. CIDOC CRM, DBpedia and WordNet). Being a foundational ontology, dolce is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years dolce has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases. [ABSTRACT FROM AUTHOR]

Basic Formal Ontology (BFO) is a top-level ontology consisting of thirty-six classes, designed to support information integration, retrieval, and analysis across all domains of scientific investigation, presently employed in over 350 ontology projects around the world. BFO is a genuine top-level ontology, containing no terms particular to material domains, such as physics, medicine, or psychology. In this paper, we demonstrate how a series of cases illustrating common types of change may be represented by universals, defined classes, and relations employing the BFO framework. We provide discussion of these cases to provide a template for other ontologists using BFO, as well as to facilitate comparison with the strategies proposed by ontologists using different top-level ontologies. [ABSTRACT FROM AUTHOR]

The General Formal Ontology (GFO) is a top-level ontology that is being developed at the University of Leipzig since 1999. Besides introducing some of the basic principles of the ontology, we expound axiomatic fragments of its formalization and present ontological models of several use cases. GFO is a top-level ontology that integrates objects and processes into a unified framework, in a way that differs significantly from other ontologies. Another unique selling feature of GFO is its meta-ontological architecture, which includes set theory into ontology and which accounts for its specific role in common representation approaches. The second level of that architecture starts from the distinction of categories and individuals, which forms the backbone of the world's structure. Furthermore, GFO comprises several kinds of categories, among them universals and concepts, and it considers several ontological regions and levels. In the context of this special issue paper, we study five pre-determined use cases from the perspective of GFO. The results of these analyses yield insights into how the ontology treats several important notions. Very abridged, this covers material objects and their composition; roles and social entities; properties with their relations to objects and processes, and their changing; changes of processes, including a functional perspective; and, eventually, the nature and changing of concepts as well as terminology. A final part summarizes application projects that use GFO in various contexts. [ABSTRACT FROM AUTHOR]

The Unified Foundational Ontology (UFO) was developed over the last two decades by consistently putting together theories from areas such as formal ontology in philosophy, cognitive science, linguistics, and philosophical logics. It comprises a number of micro-theories addressing fundamental conceptual modeling notions, including entity types and relationship types. The aim of this paper is to summarize the current state of UFO, presenting a formalization of the ontology, along with the analysis of a number of cases to illustrate the application of UFO and facilitate its comparison with other foundational ontologies in this special issue. (The cases originate from the First FOUST Workshop – the Foundational Stance, an international forum dedicated to Foundational Ontology research.) [ABSTRACT FROM AUTHOR]

Standards and ontologies for manufacturing understand resources differently. Because of this heterogeneity, misunderstandings arise concerning the basic features that characterize them. The purpose of the paper is to investigate how to ontologically model resources with the goal of facilitating the development of knowledge representation models for manufacturing. By reviewing the literature, we discuss and compare three approaches for the representation of resources depending on whether they are conceived in connection to either processes, plans or goals. By addressing the advantages and shortcomings of each view, we present a unifying perspective to enable the modeling of resources in an integrated manner. In this way, the intended meanings of the used notions are harmonized and, as a result, one can facilitate multiple experts to interact e.g., via data sharing and/or data integration procedures. Differently, by keeping three separated views, there is no guarantee that data coming from different parties will share common meanings even if the same terms are used. By the end of the paper, we present a case study to show the application of our approach and to compare it with an existing ontology for manufacturing. [ABSTRACT FROM AUTHOR]

Geometric data models form the backbone of virtually all spatial information systems, such as GIS, CAD, and CAM. Yet a lot of spatial information from textual sources, including historical documents or social media, is predominantly of qualitative, especially mereotopological, rather than geometric-quantitative nature. While mereotopological theories have been extensively studied in Logic, Computer Science, Cognitive Science, and Geographic Information Science, most are unidimensional mereotopologies in the sense that only entities of a single dimension are permitted to co-exist. Integrating mereotopological information with geometric data requires a multidimensional mereotopology, which permits entities of different dimensions to co-exist, similarly to how geometric and algebraic topological data models permit points, simple lines, polylines, cells, polygons, and polyhedra to co-exist. It further requires complex spatial objects to be represented as sets of atomic entities such that spatial relations between complex objects can be computed from the relations of the atomic entities in their decomposition. This paper provides a comprehensive study of CODI, a first-order logic ontology of multidimensional mereotopology. An axiomatization of mereological closure operations of intersection, difference, and sums for CODI is proposed in which these operations apply to all pairs of spatial entities regardless of their dimension. It is proved that for atomic models – and thus all finite models – the extended theory is indeed able to decompose all spatial entities into a partition of atomic parts. A full representation of the models as sets of Boolean algebras verifies this. The closure operations are further shown to satisfy important mereological principles from unidimensional mereotopology and to preserve many of the mathematical properties of set intersection and set difference. [ABSTRACT FROM AUTHOR]

Recently, a number of ontology-driven healthcare systems have been leveraged by the Internet-of-Things (IoT) technologies that offer opportunities to improve abnormal situation detection when integrating medical wearables and cloud infrastructure. Usually, these systems rely on standardised IoT ontologies to represent sensor data observations. The ETSI Smart Applications REFerence ontology (SAREF) is an extensible industry-oriented standard. In this paper, we explain the need for interoperability of IoT healthcare applications and the role of standardised ontologies to achieve semantic interoperability. In particular, we discuss the verbosity problem of SAREF when used for real-time electrocardiography (ECG), emphasizing the requirement of representing time series. We compared the main ontologies in this context, according to quality, message size (payload), IoT-orientation and standardisation. Here we describe the first attempt to extend SAREF for specific e-Health use cases related to ECG data, the SAREF4health extension, which tackles the verbosity problem. Ontology-driven conceptual modelling was applied to develop SAREF4health, in which an ECG ontology grounded in the Unified Foundational Ontology (UFO), which plays the role of a reference model. The methodology was enhanced by following a standardisation procedure and considering the RDF implementation of the HL7 Fast Healthcare Interoperability Resources (FHIR) standard. The validation of SAREF4health includes the responses to competency questions, as well as the development and tests of an IoT Early Warning System prototype that uses ECG data and collision identification to detect accidents with truck drivers in a port area. This prototype integrates an existing ECG wearable with a cloud infrastructure, demonstrating the performance impact of SAREF4health considering IoT constraints. Our results show that SAREF4health enables the semantic interoperability of IoT solutions that need to deal with frequency-based time series. Design decisions regarding the trade-off between ontology quality and aggregation representation are also discussed. [ABSTRACT FROM AUTHOR]

Part–whole relations are pervasive throughout domain ontologies and enjoy interest also in, inter alia, NLP and manufacturing, and by philosophers in the scope of mereology. There exist a stable list of part–whole relations that are assumed to be common, yet for isiZulu, among other languages, there were at least linguistic differences. This raises the question whether there are ontological differences, which would imply that the 'common' list is not universal across languages and cultures. We investigated this for 18 part–whole terms in the Zulu language that we selected from an initial list of 81 terms collected. They were formalised and aligned to the well-known part–whole relations, and checked against a corpus. While there is a term for general parthood in Zulu, the main difference observed concerns relation proliferation due to very specific relata that are entities typically represented only in domain ontologies. This poses new questions for ontology engineering on how to manage the plurality of relations and for philosophy to possibly extend mereology. [ABSTRACT FROM AUTHOR]

Quantities and units of measure provide an important means by which intelligent agents interact with the physical world. Although multiple ontologies for quantities and units of measure have been proposed within the Applied Ontology community, they often incorporate questionable ontological commitments. Quantities are combined using notions of dimensional analysis that often conflate the combination of units with algebraic operations on real numbers. In this paper, we present an alternative approach that shifts the focus to the connection between kinds of measurements associated with a unit and the physical objects and processes that are being measured. One of the key features of this approach is that it makes minimal ontological commitments with respect to the TUpper upper ontology – the only new classes that are introduced are the classes for kinds of measures and associated units. We propose axiomatizations of the intended semantics for combining measurements, and the correct axiomatization of the relationship between the quantities and units of measure and the existing upper ontology. [ABSTRACT FROM AUTHOR]

When you meet a delivery robot in a narrow street it stops to let you pass. It was built to give you precedence. What happens if you run into a robot that was not trained by or for humans? The existence in our environment of robots which do not abide by human behavioral rules and social systems might sound odd, but is a case we may encounter in the future. In this paper, self-taught robots are artificial embodied agents that, thanks for instance to AI learning techniques, manage to survive in the environment without embracing behavioral or judgment rules given and used by humans. The paper argues that our ontological systems are not suitable to understand and cope with artificial agents. The arguments are speculative rather than empirical, and the goal is to drive attention to new ontological challenges. [ABSTRACT FROM AUTHOR]

Robots might not act according to human expectations if they cannot anticipate how people make sense of a situation and what behavior they consider appropriate in some given circumstances. In many cases, understanding, expectations and behavior are constrained, if not driven, by culture, and a robot that knows about human culture could improve the quality level of human–robot interaction. Can we share human culture with a robot? Can we provide robots with formal representations of different cultures? In this paper, we discuss the (elusive) notion of culture and propose an approach based on the notion of trait which, we argue, permits us to build formal modules suitable to represent culture (broadly understood) in a robot architecture. We distinguish the types of traits that such modules should contain, namely behavior, knowledge, rule and interpretation traits, and how they could be organized. We identify the interpretation process that maps situations to specific knowledge traits, called scenarios, as a key component of the trait-based culture module. Finally, we describe how culture modules can be integrated in an existing architecture, and discuss three use cases to exemplify the advantages of having a culture module in the robot architecture highlighting surprising potentialities. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPS) and Socio-Technical Systems (STS) are two popular paradigms for the analysis and modeling of engineering and social systems. These paradigms are complementary and particularly apt to model complex adaptive behaviors from both the component and system points of view. Notwithstanding historical and methodological differences, nowadays research in CPS and in STS converge to study similar system characteristics. The integration of expertise from both these domains can help to develop new approaches to study information- and human-centered systems like factories in Industry 4.0 and urban environments. To foster their integration, an overarching framework and a coherent conceptualization of adaptive systems must be put forward. This paper faces the challenge by the introduction of core distinctions, the characterization of the class of Agent-based Cyber-Physical Social System (ACPSS), and the development of an ontology-based framework. The paper builds on the traditional notions of component and interaction here re-elaborated from a domain-neutral viewpoint. The outcome of this analysis is proposed as a foundational basis to model behaviorally adaptive engineering systems. [ABSTRACT FROM AUTHOR]

Background: Today's globalised and interconnected world is characterized by intertwined and quickly evolving relationships between animals, humans and their environment and by an escalating number of accessible data for public health. The public veterinary services must exploit new modeling and decision strategies to face these changes. The organization and control of data flows have become crucial to effectively evaluate the evolution and safety concerns of a given situation in the territory. This paper discusses what is needed to develop modern strategies to optimize data distribution to the stakeholders. Main text: If traditionally the system manager and knowledge engineer have been concerned with the increase of speed of data flow and the improvement of data quality, nowadays they need to worry about data overflow as well. To avoid this risk an information system should be capable of selecting the data which need to be shown to the human operator. In this perspective, two aspects need to be distinguished: data classification vs data distribution. Data classification is the problem of organizing data depending on what they refer to and on the way they are obtained; data distribution is the problem of selecting which data is accessible to which stakeholder. Data classification can be established and implemented via ontological analysis and formal logic but we claim that a context-based selection of data should be integrated in the data distribution application. Data distribution should provide these new features: (a) the organization of situation types distinguishing at least ordinary vs extraordinary scenarios (contextualization of scenarios); (b) the possibility to focus on the data that are really important in a given scenario (data contextualization by scenarios); and (c) the classification of which data is relevant to which stakeholder (data contextualization by users). Short conclusion: Public veterinary services, to efficaciously and efficiently manage the information needed for today's health and safety challenges, should contextualize and filter the continuous and growing flow of data by setting suitable frameworks to classify data, users' roles and possible situations. [ABSTRACT FROM AUTHOR]

Background: Ontologies are widely used both in the life sciences and in the management of public and private companies. Typically, the different offices in an organization develop their own models and related ontologies to capture specific tasks and goals. Although there might be an overall coordination, the use of distinct ontologies can jeopardize the integration of data across the organization since data sharing and reusability are sensitive to modeling choices. Results: The paper provides a study of the entities that are typically found at the reception, analysis and report phases in public institutes in the life science domain. Ontological considerations and techniques are introduced and their implementation exemplified by studying the Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe), a public veterinarian institute with different geographical locations and several laboratories. Different modeling issues are discussed like the identification and characterization of the main entities in these phases; the classification of the (types of) data; the clarification of the contexts and the roles of the involved entities. The study is based on a foundational ontology and shows how it can be extended to a comprehensive and coherent framework comprising the different institute's roles, processes and data. In particular, it shows how to use notions lying at the borderline between ontology and applications, like that of knowledge object. The paper aims to help the modeler to understand the core viewpoint of the organization and to improve data transparency. Conclusions: The study shows that the entities at play can be analyzed within a single ontological perspective allowing us to isolate a single ontological framework for the whole organization. This facilitates the development of coherent representations of the entities and related data, and fosters the use of integrated software for data management and reasoning across the company. [ABSTRACT FROM AUTHOR]

Physical artifacts and biological systems have been studied from a variety of perspectives in different disciplines. These entities show many common characteristics and are investigated using similar notions except for one important aspect: functionality. Notwithstanding many attempts, the search for a unified notion of functionality that could encompass both the functions attributed to natural objects, like biological organisms, as well as those attributed to designed objects, like artifacts, to date has remained an open challenge. Deepening an earlier characterization of engineering functions, this paper starts with an introduction to the notions of behavior and context, which become the basic blocks for the construction of a general framework for a unified definition of function. The approach distinguishes three types of functional contexts (systemic, user and design) and clarifies the role of goals in defining biological and artifact functions. Finally, it shows that the notion of systemic function, as detailed in the paper, succeeds in comprising both biological and artifact functions. The proposal is evaluated against a collection of desiderata and examples taken from the literature. [ABSTRACT FROM AUTHOR]

Humans are always interested in distinguishing natural and artificial entities although there is no sharp demarcation between the two categories. Surprisingly, things do not improve when the second type of entities is restricted to the arguably more constrained realm of physical technical artifacts. This paper helps to clarify the relationship between natural entities and technical artifacts by developing a conceptual landscape within which to analyze these notions. The framework is developed by studying three definitions of technical artifact which arise from different perspectives. All these perspectives share two intuitions: that technical artifacts are physical objects that exist by human intervention; and that technical artifacts are entities to be contrasted to natural entities. Yet the perspectives are different in the way they spell out these intuitions: the relevant human intervention may range from intentional selection to intentional production; and the contrast between technical artifacts and natural entities may be introduced by a constitution relation or by defining properties that set technical artifacts apart. The three perspectives are compared and their similarities and dissimilarities are explored with the help of ontological analysis. [ABSTRACT FROM AUTHOR]

In 1929 Tarski showed how to construct points in a region-based first-order logic for space representation. The resulting system, called the geometry of solids, is a cornerstone for region-based geometry and for the comparison of point-based and region-based geometries. We expand this study of the construction of points in region-based systems using different primitives, namely hyper-cubes and regular simplexes, and show that these primitives lead to equivalent systems in dimension n ≥ 2. The result is achieved by adopting a single set of definitions that works for both these classes of figures. The analysis of our logics shows that Tarski's choice to take sphere as the geometrical primitive might be intuitively justified but is not optimal from a technical viewpoint. [ABSTRACT FROM AUTHOR]

Information technology has embraced the ontological approach to expand its capacity to deal with knowledge of different kinds. The subsequent combination of formal concerns and philosophical considerations has led to the development of new knowledge systems that rely on foundational distinctions of entity type such as object, process, property and role. This change has attracted attention to the distinction between types of entity in the enterprise. The result is a compartmentalisation of the information, which, although well motivated and technically fruitful, is not always optimal for knowledge management (KM) tasks where one aims at an integrated view of information. This paper focuses on the notion of knowledge object understood as a formal construct for knowledge modelling and KM systems. The approach starts from formal and ontological analysis with an eye to modelling knowledge at large. The paper motivates the introduction of a notion of knowledge object as a new type of entity that emerges from the explicit interaction of material entities, information entities and roles within an enterprise. The main goals of this work are: to discuss the capacity of knowledge objects to tie knowledge and roles in an (enterprise) context; to model aspects of enterprise knowledge that escape standard ontological approaches; and to describe knowledge objects as a conceptual tool that can be integrated within existing formal systems. [ABSTRACT FROM AUTHOR]

In this paper, we give formalisations of two engineering concepts of technical function and present in more general terms the project of supporting functional description translation by ontological analysis. The formalisations are given within the foundational dolce ontology and the concepts formalised are as follows: (1) the function as defined in the Functional Representation approach by Chandrasekaran and Josephson and (2) the function as defined in the Functional Basis approach by Stone and Wood. These two concepts represent two main ways of understanding functions in engineering: the first by means of the behaviour of artefacts, and the second by means of operations on flows as performed by artefacts. We analyse the similarities and differences between these concepts by means of the formalisations and show how the formalisations support the automated translation between functional descriptions based on these two concepts. In addition, we compare our strategy of formalising different engineering concepts of function within one foundational ontology with other strategies in the ontology-driven formalisation, such as defining a single formalised concept of function, either for replacing existing engineering concepts, or for use as a reference by which such existing concepts can be related. We compare these strategies and sketch the merits and shortcomings of our strategy. [ABSTRACT FROM AUTHOR]

The article discusses reports published within the issue including, one by Marc Artiga about the organizational account (OA) approach, Ulrich Krohs about functions and fixed types and Carrara et al. on the formalization of the notion of function as used in engineering.

We analyze and compare geometrical theories based on mereology (mereogeometries). Most theories in this area lack in formalization, and this prevents any systematic logical analysis. To overcome this problem, we concentrate on specific interpretations for the primitives and use them to isolate comparable models for each theory. Relying on the chosen interpretations, we introduce the notion of environment structure, that is, a minimal structure that contains a (sub)structure for each theory. In particular, in the case of mereogeometries, the domain of an environment structure is composed of particular subsets of Rn. The comparison of mereogeometrical theories within these environment structures shows dependencies among primitives and provides (relative) definitional equivalences. With one exception, we show that all the theories considered are equivalent in these environment structures. [ABSTRACT FROM AUTHOR]

In this paper we propose that adequate treatments of space need to be multiperspectival and related to sound foundational ontologies. To support this, we show that natural spatial descriptions commonly appeal to diverse theories of space and these need to be formally combined to be fully interpreted. Our account draws particularly on the foundational ontology DOLCE and the algebraic specification language CASL. We show how the structuring mechanisms of CASL suggest mechanisms for both building and combining multiperspectival ontologies of space. We also suggest that these mechanisms provide a natural link both with currently emerging cognitive principles such as blending and with developments in ontology mediation and mapping. [ABSTRACT FROM AUTHOR]

This paper presents a formalization of the notion of function as operation on flowsas advanced in the Functional Basis approach of Stone and Wood. We first analyze the modeling of functions in this approach and identify the notions that are ontological significant for their formalization within the foundational ontology DOLCE. Then, we build the logical system in which this engineering notion of function is formally translated and connected to the ontology. Furthermore, we posit a number of constraints for a correct interpretation of the formal system and also provide a web ontology language version. We conclude with an assessment of our results and a discussion of our larger project aimed at analysing functional descriptions of technical artifacts, and at translating functional descriptions using different engineering notions of function. [ABSTRACT FROM AUTHOR]

Upper ontologies have traditionally arisen from the approach in which concepts that are common across a set of domains can be axiomatized at a general level. The rationale is that reuse across domains is to be supported through specialization of the general concepts from an upper ontology. Similarly, semantic integration between ontologies is to be achieved through the general concepts they specialize. The TUpper Ontology follows an alternative approach (referred to as the sideways approach) to the conventional upper ontology paradigm. Rather than think of an upper ontology as a monolithic axiomatization centred on a taxonomy, the sideways approach considers an upper ontology to be a modular ontology composed of generic ontologies that cover concepts including those related to time, process, and space. TUpper is therefore composed of a set of generic ontologies, and each generic ontology axiomatizes a particular set of generic concepts (e.g., the classes and relations relevant for time, process, and space). The TUpper Ontology is designed as a top-level ontology that contains modules from the ontologies within existing international standards. [ABSTRACT FROM AUTHOR]

Basic Formal Ontology (BFO) is a top-level ontology consisting of thirty-six classes, designed to support information integration, retrieval, and analysis across all domains of scientific investigation, presently employed in over 350 ontology projects around the world. BFO is a genuine top-level ontology, containing no terms particular to material domains, such as physics, medicine, or psychology. In this paper, we demonstrate how a series of cases illustrating common types of change may be represented by universals, defined classes, and relations employing the BFO framework. We provide discussion of these cases to provide a template for other ontologists using BFO, as well as to facilitate comparison with the strategies proposed by ontologists using different top-level ontologies. [ABSTRACT FROM AUTHOR]