Nivel: a metamodelling language with a formal semantics

Much work has been done to clarify the notion of metamodelling and new ideas, such as strict metamodelling, distinction between ontological and linguistic instantiation, unified modelling elements and deep instantiation, have been introduced. However, many of these ideas have not yet been fully developed and integrated into modelling languages with (concrete) syntax, rigorous semantics and tool support. Consequently, applying these ideas in practice and reasoning about their meaning is difficult, if not impossible. In this paper, we strive to add semantic rigour and conceptual clarity to metamodelling through the introduction of Nivel, a novel metamodelling language capable of expressing models spanning an arbitrary number of levels. Nivel is based on a core set of conceptual modelling concepts: class, generalisation, instantiation, attribute, value and association. Nivel adheres to a form of strict metamodelling and supports deep instantiation of classes, associations and attributes. A formal semantics is given for Nivel by translation to weight constraint rule language (WCRL), which enables decidable, automated reasoning about Nivel. The modelling facilities of Nivel and the utility of the formalisation are demonstrated in a case study on feature modelling.

A formalisation of deep metamodelling

Metamodelling is one of the pillars of model-driven engineering, used for language engineering and domain modelling. Even though metamodelling is traditionally based on a two-metalevel approach, several researchers have pointed out limitations of this solution and proposed an alternative deep (also called multi-level) approach to obtain simpler system specifications. However, this approach currently lacks a formalisation that can be used to explain fundamental concepts such as deep characterisation, double linguistic/ontological typing and linguistic extension. This paper provides such a formalisation based on the Diagram Predicate Framework, and discusses its practical realisation in the metaDepth tool.     

Speaking things into existence: Ontological foundations of identity representation and management

Conceptual models capture knowledge about domains of reality. Therefore, conceptual models and their modelling constructs should be based on theories about the world—that is, they should be grounded in ontology. Identity is fundamental to ontology and conceptual modelling because it addresses the very existence of objects and conceptual systems in general. Classification involves grouping objects that share similarities and delineating them from objects that fall under other concepts (qualitative identity). However, among objects that fall under the same concept, we must also distinguish between individual objects (individual identity). In this paper, we analyze the ontological question of identity, focusing specifically on institutional identity, which is the identity of socially constructed institutional objects. An institutional entity is a language construct that is ‘spoken into existence’. We elaborate on how institutional identity changes how we understand conceptual modelling and the models produced. We show that different models result if we base modelling on a property-based conception of identity compared to an institutional one. We use the Bunge-Wand-Weber principles, which embrace a property-based view of identity, as an anchor to the existing literature to point out how this type of ontology sidesteps identity in general and institutional identity in particular. We contribute theoretically by providing the first in-depth ontological analysis of what the notion of institutional identity can bring to conceptual modelling. We also contribute a solid ontological grounding of identity management and the identity of things in digital infrastructures.     

A Unified Modelling Language without referential redundancy

The paper argues that, as a language for representing concrete problem domains, the quality of the UML is compromised by its many referentially redundant modelling constructs. A referential redundancy occurs when several modelling constructs or model elements refer to the same classes, things or properties in the problem domain. Referential redundancy compromises language and model quality because it hampers consistency checking, update reflection and reuse of model content between different diagrams or models. To alleviate this problem, the paper shows how the relevant parts of the UML can be reformulated using faceted metamodelling, so that referential redundancy is eliminated at the language level and potentially reduced at the model level. The discussion contrasts faceted metamodelling with conventional metamodelling using metaobjects, -properties and -relationships and argues that many of the referential redundancies in the UML are introduced by the conventional metamodelling approach used to define it.     

Capturing smart service systems: Development of a domain‐specific modelling language

Over the last years, the nature of service has changed owing to conceptual advances and developments in information technology. These developments have given rise to novel types of service and smart service systems (SSS), ie, resource configurations capable of learning, dynamic adaptation, and decision making. Currently, the internet of things (IoT) is turning physical objects into active smart things, bridging the gap between the physical and the digital world. Smart things advance SSS as they observe the physical environment, access local data, immerse into individuals' everyday lives and organizational routines. In line with the emergent nature of both phenomena, the impact of the IoT on SSS yet needs to be explored. Building the basis for explanatory and design‐led research and for the analysis and design of SSS, a means for the conceptual modelling of SSS that accounts for novel IoT‐enabled concepts is in high need. Hence, we designed, demonstrated, and evaluated a domain‐specific modelling language (DSML) for SSS. We evaluated the DSML by using it in the modelling of real‐world scenarios from all functional IoT domains, by submitting it to the scrutiny of industry experts, by discussing it against generic DSML requirements, and by analysing to what extent it meets domain‐specific design objectives compared with competing artefacts. To demonstrate the DSML, we included a complex real‐world scenario centred around the Nest Learning Thermostat.     

High-level interpretation in virtual environments

As virtual environments applications become more complex, there is a need to interpret user interaction in terms of high-level concepts. In this paper, the relations between conceptual representations of actions and their physical simulation in virtual worlds is investigated. A model inspired fromnatural language processing (NLP) research in the linguistic interpretation of dynamic scenes has been developed. The experiments are based on real-time animation software, which has been enhanced with a symbolic information processing layer, originally developed for NLP-based animation. We report the implementation of a high-level interpretation module that is able to recognize complex actions fromlow-level physical events in the virtual world and discuss its performance as well as directions for further developments.     

Ontologies for Knowledge Management: An Information Systems Perspective

Knowledge management research focuses on concepts, methods, and tools supporting the management of human knowledge. The main objective of this paper is to survey basic concepts that have been used in computer science for the representation of knowledge and summarize some of their advantages and drawbacks. A secondary objective is to relate these techniques to information science theory and practice.The survey classifies the concepts used for knowledge representation into four broad ontological categories. Static ontologies describe static aspects of the world, i.e., what things exist, their attributes and relationships. A dynamic ontology, on the other hand, describes the changing aspects of the world in terms of states, state transitions and processes. Intentional ontologies encompass the world of things agents believe in, want, prove or disprove, and argue about. Finally, social ontologies cover social settings – agents, positions, roles, authority, permanent organizational structures or shifting networks of alliances and interdependencies.     

Constraint programming for type inference in flexible model-driven engineering

Domain experts typically have detailed knowledge of the concepts that are used in their domain; however they often lack the technical skills needed to translate that knowledge into model-driven engineering (MDE) idioms and technologies. Flexible or bottom-up modelling has been introduced to assist with the involvement of domain experts by promoting the use of simple drawing tools. In traditional MDE the engineering process starts with the definition of a metamodel which is used for the instantiation of models. In bottom-up MDE example models are defined at the beginning, letting the domain experts and language engineers focus on expressing the concepts rather than spending time on technical details of the metamodelling infrastructure. The metamodel is then created manually or inferred automatically. The flexibility that bottom-up MDE offers comes with the cost of having nodes in the example models left untyped. As a result, concepts that might be important for the definition of the domain will be ignored while the example models cannot be adequately re-used in future iterations of the language definition process. In this paper, we propose a novel approach that assists in the inference of the types of untyped model elements using Constraint Programming. We evaluate the proposed approach in a number of example models to identify the performance of the prediction mechanism and the benefits it offers. The reduction in the effort needed to complete the missing types reaches up to 91.45% compared to the scenario where the language engineers had to identify and complete the types without guidance.     

A cognitive semantics for the association construct

The unified modelling language (UML), besides its traditional use in describing software artifacts, is increasingly being used for conceptual modelling, the activity of describing an application domain. For models to be clear and unambiguous, every construct of the modelling language must have well-defined semantics, which is its mapping to elements of the semantic domain. When used for conceptual modelling, the semantic domain of UML is the application domain, as perceived by the modeller. Modellers perceive and structure their perceptions using cognitive concepts. This paper proposes a mapping of the UML association construct to those concepts. Implications for the use of the association construct for conceptual modelling are derived, a UML profile for conceptual modelling is presented, along with the results of a case study using the semantics and profile.

Enhancing augmented reality with cognitive and knowledge perspectives: a case study in museum exhibitions

ABSTRACT

In this paper, we present our results related to the definition of a methodology that combines augmented reality (AR) with semantic techniques for the creation of digital stories associated with museum exhibitions. In contrast to traditional AR approaches, we augment real-world elements by supplementing contents of a museum exhibition with additional inputs that provide new and different meanings. In this way we augment a cultural resource with respect to both its presentation and meaning. The methodology is framed in the cultural re-mediation theory and is grounded on a set of ontologies aimed at modelling a cultural resource and correlating it with external multimedia objects and resources. To provide an easy tool for the creation of museum narratives, the methodology makes use of a set of recognised practices widely adopted by museum curators that have been formalised through inference rules. The defined methodology has been experimented in a scenario related to Flemish paintings to validate the augmentation of cultural objects with two different approaches, the first basing on similarities and the second on dissimilarities.     

Abstraction as a basis for the computational interpretation of creative cross-modal metaphor

Various approaches to computational metaphor interpretation are based on pre-existing similarities between source and target domains and/or are based on metaphors already observed to be prevalent in the language. This paper addresses similarity-creating cross-modal metaphoric expressions. It is shown how the “abstract concept as object” (or reification) metaphor plays a central role in a large class of metaphoric extensions. The described approach depends on the imposition of abstract ontological components, which represent source concepts, onto target concepts. The challenge of such a system is to represent both denotative and connotative components which are extensible, together with a framework of general domains between which such extensions can conceivably occur. An existing ontology of this kind, consistent with some mathematic concepts and widely held linguistic notions, is outlined. It is suggested that the use of such an abstract representation system is well adapted to the interpretation of both conventional and unconventional metaphor that is similarity-creating.     

Microplanning with Communicative Intentions: The SPUD System

The process of microplanning in natural language generation (NLG) encompasses a range of problems in which a generator must bridge underlying domain‐specific representations and general linguistic representations. These problems include constructing linguistic referring expressions to identify domain objects, selecting lexical items to express domain concepts, and using complex linguistic constructions to concisely convey related domain facts. In this paper, we argue that such problems are best solved through a uniform, comprehensive, declarative process. In our approach, the generator directly explores a search space for utterances described by a linguistic grammar. At each stage of search, the generator uses a model of interpretation, which characterizes the potential links between the utterance and the domain and context, to assess its progress in conveying domain‐specific representations. We further address the challenges for implementation and knowledge representation in this approach. We show how to implement this approach effectively by using the lexicalized tree‐adjoining grammar (LTAG) formalism to connect structure to meaning and using modal logic programming to connect meaning to context. We articulate a detailed methodology for designing grammatical and conceptual resources which the generator can use to achieve desired microplanning behavior in a specified domain. In describing our approach to microplanning, we emphasize that we are in fact realizing a deliberative process of goal‐directed activity. As we formulate it, interpretation offers a declarative representation of a generator's communicative intent. It associates the concrete linguistic structure planned by the generator with inferences that show how the meaning of that structure communicates needed information about some application domain in the current discourse context. Thus, interpretations are plans that the microplanner constructs and outputs. At the same time, communicative intent representations provide a rich and uniform resource for the process of NLG. Using representations of communicative intent, a generator can augment the syntax, semantics, and pragmatics of an incomplete sentence simultaneously, and can work incrementally toward solutions for the various problems of microplanning.     

Theorem proving for intensional logic

For a number of tasks in knowledge representation, and particularly in natural language semantics, it is useful to be able to treat propositions and properties as objects — as items that can appear as arguments of predicates, as things one can quantify over, and so on. Logics that support such intensional operations are notoriously hard to work with. The current paper presents a theorem prover for one such logic, namely, Turner's property theory.     

FUNCTIONAL MODELS IN PERSPECTIVE: THEIR CHARACTERISTICS AND INTEGRATION IN MULTIPLE MODEL-BASED DIAGNOSIS

Abstract

We analyze Junctional models in the wide spectrum of model types. Our premise is that, in order to identify the merits of model types, their perceptions of reality are important. We classify modeling approaches into two categories, the kernel and the interpretative. The kernel approach, which assumes that the world can be modeled by a composition of predefined primitives, suffers from important drawbacks. The interpretative approach, to which the functional models belong, assumes that we know how things work. We investigate the characteristics of this approach from a diagnostic point of view and show that, although it provides a powerful tool for describing devices, it is hindered by serious disadvantages when used in isolation. We advertise the use of multiple models as a solution and provide an ontological semantic network as a framework for the integration of multiple model types.     

An agent-based model of the emergence and evolution of a language system for boolean coordination

This paper presents an agent-based model of the emergence and evolution of a language system for Boolean coordination. The model assumes the agents have cognitive capacities for invention, adoption, abstraction, repair and adaptation, a common lexicon for basic concepts, and the ability to construct complex concepts using recursive combinations of basic concepts and logical operations such as negation, conjunction or disjunction. It also supposes the agents initially have neither a lexicon for logical operations nor the ability to express logical combinations of basic concepts through language. The results of the experiments we have performed show that a language system for Boolean coordination emerges as a result of a process of self-organisation of the agents’ linguistic interactions when these agents adapt their preferences for vocabulary, syntactic categories and word order to those they observe are used more often by other agents. Such a language system allows the unambiguous communication of higher-order logic terms representing logical combinations of basic properties with non-trivial recursive structure, and it can be reliably transmitted across generations according to the results of our experiments. Furthermore, the conceptual and linguistic systems, and simplification and repair operations of the agent-based model proposed are more general than those defined in previous works, because they not only allow the simulation of the emergence and evolution of a language system for the Boolean coordination of basic properties, but also for the Boolean coordination of higher-order logic terms of any Boolean type which can represent the meaning of nouns, sentences, verbs, adjectives, adverbs, prepositions, prepositional phrases and subexpressions not traditionally analysed as forming constituents, using linguistic devices such as syntactic categories, word order and function words.     

Towards an Ontological Approach to Information System Security and Safety Requirement Modeling and Reuse

ABSTRACT

Misuse cases are currently used to identify safety and security threats and subsequently capture safety and security requirements. There is limited consensus to the precise meaning of the basic terminology used for use/misuse case concepts. This paper delves into the use of ontology for the formal representation of the use-misuse case domain knowledge for eliciting safety and security requirements. We classify misuse cases into different category to reflect different type of misusers. This will allow participants during the requirement engineering stage to have a common understanding of the problem domain. We enhanced the misuse case domain to include abusive misuse case and vulnerable use case in order to boost the elicitation of safety requirements. The proposed ontological approach will allow developer to share and reuse the knowledge represented in the ontology thereby avoiding ambiguity and inconsistency in capturing safety and security requirements. OWL protégé 3.3.1 editor was used for the ontology coding. An illustration of the use of the ontology is given with examples from the health care information system.     

Comparing OPEN and UML: the two third-generation OO development approaches

Recent efforts have been made to coalesce object-oriented methods and object-oriented modelling languages and, at the same time, to put them on a more rigorous footing by the use of metamodelling techniques. Two so-called third-generation approaches, OPEN (a full methodology) and UML (a modelling language) are described and compared here. These two approaches are compared by focusing on two main areas: (1) process and lifecycle support and, predominantly, (2) metamodel and notation.