Ontologies In Computational Engineering (original) (raw)

Ontologies for Modeling and Simulation: Issues and Approaches

2004

Ontologies represent the next important phase of the World Wide Web, creating a semantic web which links together disparate pieces of information and knowledge. Creating ontologies within computer simulation can be seen as a logical next phase of the web-based modeling and simulation thrust, where the emphasis is on knowledge and its representation rather than on run-time network characteristics. We introduce the concept of an ontology and then survey two groups performing research in this area at the Universities of Florida and Georgia, respectively.

Ontology for modeling and simulation

Simulation Conference (WSC), …, 2010

This paper establishes what makes an ontology different in Modeling and Simulation (M&S) from other disciplines, vis-a-vis, the necessity to capture a conceptual model of a system in an explicit, unambiguous, and machine readable form. Unlike other disciplines where ontologies are used, such as Information Systems and Medicine, ontologies in M&S do not depart from a set of requirements but from a research question which is contingent on a modeler. Thus, the semiotic triangle is used to present that different implemented ontologies are representations of different conceptual models whose commonality depends on which research question is being asked. Ontologies can be applied to better capture the modeler ¶V perspective. The elicitation of ontological, epistemological, and teleological considerations is suggested. These considerations may lead to better differentiation between conceptualizations, which for a computer are of importance for use, reuse and composability of models and interoperability of simulations. 1 643 978-1-4244-9864-2/10/$26.00 ©2010 IEEE

Ontologies for modeling and simulation: An initial framework

2007

Many fields have or are developing ontologies for their subdomains. The Gene Ontology (GO) is now considered to be a great success in biology, a field that has already developed several extensive ontologies. Similar advantages could accrue to the Modeling and Simulation community. Ontologies provide a way to establish common vocabularies and capture domain knowledge for organizing the domain with a community-wide agreement.

Ontology–based Representation of Simulation Models

Ontologies have been used in a variety of domains for multiple purposes such as establishing common terminology, organizing domain knowledge and describing domain in a machine-readable form. Moreover, ontologies are the foundation of the Semantic Web and often semantic integration is achieved using ontology. Even though simulation demonstrates a number of similar characteristics to Semantic Web or semantic integration, including heterogeneity in the simulation domain, representation and semantics, the application of ontology in the simulation domain is still in its infancy. This paper proposes an ontology-based representation of simulation models. The goal of this research is to facilitate comparison among simulation models, querying, making inferences and reuse of existing simulation models. Specifically, such models represented in the domain simulation engine environment serve as an information source for their representation as instances of an ontology. Therefore, the ontology-based representation is created from existing simulation models in their proprietary file formats, consequently eliminating the need to perform the simulation modeling directly in the ontology. The proposed approach is evaluated on a case study involving the I2Sim interdependency simulator.

Using ontologies for simulation integration

2007 Winter Simulation Conference, 2007

This paper describes the motivations, methods, and solution concepts for the use of ontologies for simulation model integration. Ontological analysis has been shown to be an effective initial step in the construction of intelligent systems.

OSMO: Ontology for Simulation, Modelling, and Optimization

2021

This work describes the ontology OSMO,<em> i.e.</em>, an ontologization and extension of MODA, a workflow metadata standard that constitutes a mandatory requirement within a number of European calls and projects in the context of materials modelling. OSMO was developed within the Horizon 2020 project VIMMP (Virtual Materials Marketplace) and is part of a larger effort in ontology engineering driven by the European Materials Modelling Council, with the European Materials and Modelling Ontology (EMMO) as its core. As such, OSMO provides connections and alignments with other related domain ontologies in computational engineering, including the EMMO itself. This work summarizes the domain, purpose, and design choices underlying OSMO, commenting on the implementation of OSMO and its applications.

From domain ontologies to modeling ontologies to executable simulation models

2007

Ontologies allow researchers, domain experts, and software agents to share a common understanding of the concepts and relationships of a domain. The past few years have seen the publication of ontologies for a large number of domains. The modeling and simulation community is beginning to see potential for using these ontologies in the modeling process. This paper presents a method for using the knowledge encoded in ontologies to facilitate the development of simulation models. It suggests a technique that establishes relationships between domain ontologies and a modeling ontology and then uses the relationships to instantiate a simulation model as ontology instances. Techniques for translating these instances into XML based markup languages and then into executable models for various software packages are also presented.

Guidelines for Developing Ontological Architectures in Modelling and Simulation

Ontology, Epistemology, and Teleology for Modeling and Simulation: Philosophical Foundations for Intelligent M&S Applications

This book is motivated by the belief that “a better understanding of ontology, epistemology, and teleology” is essential for enabling Modelling and Simulation (M&S) systems to reach the next level of ‘intelligence’. This chapter focuses on one broad category of M&S systems where the connection is more concrete; ones where building an ontology – and, we shall suggest, an epistemology – as an integrated part of their design will enable them to reach the next level of ‘intelligence’. Within the M&S community, this use of ontology is at an early stage; so there is not yet a clear picture of what this will look like. In particular, there is little or no guidance on the kind of ontological architecture that is needed to bring the expected benefits. This chapter aims to provide guidance by outlining some major concerns that shape the ontology and the options for resolving them. The hope is that paying attention to these concerns during design will lead to a better quality architecture, and so enable more ‘intelligent’ systems. It is also hoped that understanding these concerns will lead to a better understanding of the role of ontology in M&S.

The Modelica Standard Library as an Ontology for Modeling and Simulation of physical systems

This paper presents the Modelica Standard Library, an ontology used in modeling and simulation of physical systems. The Modelica Standard Library is continuously developed in the Modelica community. We present parts of the Modelica Standard Library and show an example of its usage. Also, in this paper we focus on the comparison of Modelica, the language used to specify the Modelica Standard Library with other ontology languages developed in the Semantic Web community.