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12
F.: Exploring multi-paradigm modeling techniques
- SIMULATION
, 2009
"... Multi-Paradigm Modeling (MPM) addresses the necessity of using multiple modeling paradigms when designing complex systems. Because of its multidisciplinary nature, the MPM field involves research teams with technical backgrounds as different as control science, model checking, model-ing language eng ..."
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Cited by 10 (3 self)
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Multi-Paradigm Modeling (MPM) addresses the necessity of using multiple modeling paradigms when designing complex systems. Because of its multidisciplinary nature, the MPM field involves research teams with technical backgrounds as different as control science, model checking, model-ing language engineering or system-on-chip development. In this paper, we propose to explore the MPM domain through a survey of existing techniques from different horizons. Since the heterogene-ity of models is at the heart of MPM, we first identify the sources of this heterogeneity and introduce the problems it raises. Then we show how the different existing techniques address these problems.
Natural Language meets Spatial Calculi
- in Spatial Cognition VI. Learning, Reasoning, and Talking about Space. 6th International Conference on Spatial Cognition
, 2008
"... Abstract. We address the problem of relating natural language descriptions of spatial situations with spatial logical calculi, focusing on projective terms (orientations). We provide a formalism based on the theory of E-connections that connects natural language and spatial calculi. Semantics of lin ..."
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Cited by 8 (5 self)
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Abstract. We address the problem of relating natural language descriptions of spatial situations with spatial logical calculi, focusing on projective terms (orientations). We provide a formalism based on the theory of E-connections that connects natural language and spatial calculi. Semantics of linguistic expressions are specified in a linguistically motivated ontology, the Generalized Upper Model. Spatial information is specified as qualitative spatial relationships, namely orientations from the double-cross calculus. This linguistic-spatial connection cannot be adequately formulated without certain contextual, domain-specific aspects. We therefore extend the framework of E-connections twofold: (1) external descriptions narrow down the class of intended models, and (2) context-dependencies inherent in natural language descriptions feed back into the representation finite descriptions of necessary context information. 1
Heterogeneous Logical Environments for distributed specifications
"... We use the theory of institutions to capture the concept of a heterogeneous logical environment as a number of institutions linked by institution morphisms and comorphisms. We discuss heterogeneous specifications built in such environments, with inter-institutional specification morphisms based on ..."
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Cited by 7 (3 self)
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We use the theory of institutions to capture the concept of a heterogeneous logical environment as a number of institutions linked by institution morphisms and comorphisms. We discuss heterogeneous specifications built in such environments, with inter-institutional specification morphisms based on both institution morphisms and comorphisms. We distinguish three kinds of heterogeneity: (1) specifications in logical environments with universal logic (2) heterogeneous specifications focused at a particular logic, and (3) heterogeneous specifications distributed over a number of logics.
Towards Ontological Blending
- In 14th International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA-2010
, 2010
"... Abstract. We propose ontological blending as a new method for ‘creatively’ combining ontologies. In contrast to other combination techniques that aim at integrating or assimilating categories and relations of thematically closely related ontologies, blending aims at ‘creatively ’ generating new cate ..."
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Cited by 6 (6 self)
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Abstract. We propose ontological blending as a new method for ‘creatively’ combining ontologies. In contrast to other combination techniques that aim at integrating or assimilating categories and relations of thematically closely related ontologies, blending aims at ‘creatively ’ generating new categories and ontological definitions on the basis of in-put ontologies whose domains are thematically distinct but whose specifications share structural or logical properties. As a result, ontological blending can generate new on-tologies and concepts and allows a more flexible technique for ontology combination than existing methods. The approach is inspired by conceptual blending in cognitive science, and draws on methods from ontological engineering, algebraic specification, and computational creativity in general. Well-known techniques directed towards unifying the semantic content of different ontologies, namely techniques based on matching, aligning, or connecting ontologies, are ill-suited for generating new conceptual schemas from existing ontologies as sug-gested by the general methodology of conceptual blending introduced by Fauconnier
Ontological Blending in DOL
"... Abstract. We introduce ontological blending as a method for combining ontologies. Compared with existing combination techniques that aim at integrating or assimilating categories and relations of thematically related ontologies, blending aims at creatively generating (new) categories and ontological ..."
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Cited by 5 (4 self)
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Abstract. We introduce ontological blending as a method for combining ontologies. Compared with existing combination techniques that aim at integrating or assimilating categories and relations of thematically related ontologies, blending aims at creatively generating (new) categories and ontological definitions; this is done on the basis of input ontologies whose domains are thematically distinct but whose specifications share structural or logical properties. As a result, ontological blending can generate new ontologies and concepts and it allows a more flexible technique for ontology combination compared to existing methods. Our approach to computational creativity in conceptual blending is inspired by methods rooted in cognitive science (e.g., analogical reasoning), ontological engineering, and algebraic specification. Specifically, we introduce the basic formal definitions for ontological blending, and show how the distributed ontology language DOL (currently being standardised within the OntoIOp—Ontology Integration and Interoperability—activity of ISO/TC 37/SC 3) can be used to declaratively specify blending diagrams. 1
Heterogeneously Structured Ontologies Integration, Connection, and Refinement
"... This paper systematically applies tools and techniques from the area of algebraic specification theory to corresponding ontology structuring and design tasks. We employ the heterogeneous structuring mechanisms of the heterogeneous algebraic specification language HetCasl for defining an abstract not ..."
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Cited by 3 (0 self)
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This paper systematically applies tools and techniques from the area of algebraic specification theory to corresponding ontology structuring and design tasks. We employ the heterogeneous structuring mechanisms of the heterogeneous algebraic specification language HetCasl for defining an abstract notion of structured heterogeneous ontology. This approach enables the designer to split up a heterogeneous ontology into semantically meaningful parts and employ dedicated reasoning tools to them. In particular, we distinguish three fundamentally different kinds of combining heterogeneous ontologies: integration, connection, and refinement.
E pluribus unum: Formalisation, Use-Cases, and Computational Support for Conceptual Blending
- In Tarek R. Besold, Marco Schorlemmer, and Allain Smaill, editors, Computational Creativity Research: Towards Creative Machines, Thinking Machines. Atlantis/Springer
, 2014
"... Abstract Conceptual blending has been employed very successfully to understand the process of concept invention, studied particularly within cognitive psychology and linguistics. However, despite this influential research, within computational cre-ativity little effort has been devoted to fully form ..."
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Cited by 3 (3 self)
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Abstract Conceptual blending has been employed very successfully to understand the process of concept invention, studied particularly within cognitive psychology and linguistics. However, despite this influential research, within computational cre-ativity little effort has been devoted to fully formalise these ideas and to make them amenable to computational techniques. Unlike other combination techniques, blend-ing aims at creatively generating (new) concepts on the basis of input theories whose domains are thematically distinct but whose specifications share structural similarity based on a relation of analogy, identified in a generic space, the base ontology. We here introduce the basic formalisation of conceptual blending, as sketched by the late Joseph Goguen, and discuss some of its variations. We illustrate the vast array of conceptual blends that may be covered by this approach and discuss the theoret-ical and conceptual challenges that ensue. Moreover, we show how the Distributed Ontology Language DOL can be used to declaratively specify blending diagrams of various shapes, and discuss in detail how the workflow and creative act of generating and evaluating a new, blended concept can be managed and computationally sup-ported within Ontohub, a DOL-enabled theory repository with support for a large number of logical languages and formal linking constructs.
Shapes of Alignments -- Construction, Combination, and Computation
"... We present a general approach for representing and combining alignments and computing these combinations, based on the category theoretic notions of diagram, pushout, and colimit. This generalises the possible ‘shapes’ of alignments that have been introduced previously in similar approaches. We use ..."
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Cited by 1 (1 self)
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We present a general approach for representing and combining alignments and computing these combinations, based on the category theoretic notions of diagram, pushout, and colimit. This generalises the possible ‘shapes’ of alignments that have been introduced previously in similar approaches. We use the theory of institutions to represent heterogeneous ontologies, and show how the tool Hets can be employed to compute the colimit ontology of an alignment diagram.
Shapes of Alignments -- Construction, Composition, and Computation
"... We present a general approach for representing, composing, and computing alignments, based on the category theoretic notions of diagram, pushout, and colimit. This generalises the possible ‘shapes’ of alignments that have been introduced previously in similar approaches. We use the theory of institu ..."
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Cited by 1 (1 self)
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We present a general approach for representing, composing, and computing alignments, based on the category theoretic notions of diagram, pushout, and colimit. This generalises the possible ‘shapes’ of alignments that have been introduced previously in similar approaches. We use the theory of institutions to represent heterogeneous ontologies, and show how the tool Hets can be employed to compute the colimit ontology of an alignment diagram.
Towards a Functional Approach to Modular Ontologies using Institutions
"... We propose a functional view of ontologies that emphasises their role in determining answers to queries, irrespective of the formalism in which they are written. A notion of framework is introduced that captures the situation of a global language into which both an ontology language and a query lang ..."
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We propose a functional view of ontologies that emphasises their role in determining answers to queries, irrespective of the formalism in which they are written. A notion of framework is introduced that captures the situation of a global language into which both an ontology language and a query language can be translated, in an abstract way. We then generalise existing notions of robustness from the literature, and relate these to interpolation properties that support modularisation of ontologies.
