77,447 research outputs found
Semantic model-driven development of web service architectures.
Building service-based architectures has become a major area of interest since the advent of Web services. Modelling these architectures is a central activity. Model-driven development is a recent approach to developing software systems based on the idea of making models the central artefacts for design representation, analysis, and code generation.
We propose an ontology-based engineering methodology for semantic model-driven composition and transformation of Web service architectures. Ontology technology as a logic-based knowledge representation and reasoning framework can provide answers to the needs of sharable and reusable semantic models and descriptions needed for service engineering. Based on modelling, composition and code generation techniques for service architectures, our approach provides a methodological framework for ontology-based semantic service architecture
A Model-Driven Engineering Approach for ROS using Ontological Semantics
This paper presents a novel ontology-driven software engineering approach for
the development of industrial robotics control software. It introduces the
ReApp architecture that synthesizes model-driven engineering with semantic
technologies to facilitate the development and reuse of ROS-based components
and applications. In ReApp, we show how different ontological classification
systems for hardware, software, and capabilities help developers in discovering
suitable software components for their tasks and in applying them correctly.
The proposed model-driven tooling enables developers to work at higher
abstraction levels and fosters automatic code generation. It is underpinned by
ontologies to minimize discontinuities in the development workflow, with an
integrated development environment presenting a seamless interface to the user.
First results show the viability and synergy of the selected approach when
searching for or developing software with reuse in mind.Comment: Presented at DSLRob 2015 (arXiv:1601.00877), Stefan Zander, Georg
Heppner, Georg Neugschwandtner, Ramez Awad, Marc Essinger and Nadia Ahmed: A
Model-Driven Engineering Approach for ROS using Ontological Semantic
Model-based Engineering of Autonomous Systems using Ontologies and Metamodels
Our research focuses on engineering processes for autonomous intelligent systems construction with a life-cycle holistic view, by means of a model-based framework. The conceptual core of the framework is ontologically-driven. Our ontological approach consists of two elements. The first one is a domain Ontology for Autonomous Systems (OASys) to capture the autonomous system structure, function and behaviour. The second element is an Ontology-driven Engineering Methodology (ODEM) to develop the target autonomous system. This methodology is based on Model-based Systems Engineering and produces models of the system as core assets. These models are used through the whole system life-cycle, from implementation or validation to operation and maintenance. On the application side, the ontological framework has been used to develop a metacontrol engineering technology for autonomous systems, the OM Engineering Process (OMEP), to improve their runtime adaptivity and resilience. OMEP has been applied to a mobile robot in the form of a metacontroller built on top of the robot's control architecture. It exploits a functional model of the robot (TOMASys Model) to reconfigure its control if required by the situation at runtime. The functional model is based on a metamodel about controller function and structure using concepts form the ontology. The metacontroller was developed using the ontology-driven methodology and a robot control reference architecture
The consistent representation of scientific knowledge : investigations into the ontology of karyotypes and mitochondria
PhD ThesisOntologies are widely used in life sciences to model scienti c knowledge. The engineering
of these ontologies is well-studied and there are a variety of methodologies
and techniques, some of which have been re-purposed from software engineering
methodologies and techniques. However, due to the complex nature of bio-ontologies,
they are not resistant to errors and mistakes. This is especially true for more expressive
and/or larger ontologies.
In order to improve on this issue, we explore a variety of software engineering techniques
that were re-purposed in order to aid ontology engineering. This exploration
is driven by the construction of two light-weight ontologies, The Mitochondrial Disease
Ontology and The Karyotype Ontology. These ontologies have speci c and
useful computational goals, as well as providing exemplars for our methodology.
This thesis discusses the modelling decisions undertaken as well as the overall success
of each ontological model. Due to the added knowledge capture steps required
for the mitochondrial knowledge, The Karyotype Ontology is further developed than
The Mitochondrial Disease Ontology.
Speci cally, this thesis explores the use of a pattern-driven and programmatic approach
to bio-medical ontology engineering. During the engineering of our biomedical
ontologies, we found many of the components of each model were similar
in logical and textual de nitions. This was especially true for The Karyotype Ontology.
In software engineering a common technique to avoid replication is to abstract
through the use of patterns. Therefore we utilised localised patterns to model
these highly repetitive models. There are a variety of possible tools for the encoding
of these patterns, but we found ontology development using Graphical User
Interface (GUI) tools to be time-consuming due to the necessity of manual GUI
interaction when the ontology needed updating. With the development of Tawny-
OWL, a programmatic tool for ontology construction, we are able to overcome this
issue, with the added bene t of using a single syntax to express both simple and
- i -
patternised parts of the ontology.
Lastly, we brie
y discuss how other methodologies and tools from software engineering,
namely unit tests, di ng, version control and Continuous Integration (CI) were
re-purposed and how they aided the engineering of our two domain ontologies.
Together, this knowledge increases our understanding in ontology engineering techniques.
By re-purposing software engineering methodologies, we have aided construction,
quality and maintainability of two novel ontologies, and have demonstrated
their applicability more generally
An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry
This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term
Towards a meaningful manufacturing enterprise metamodel: a semantic driven framework
This paper presents a deep investigation and an interdisciplinary analysis of the collaborative networked enterprise engineering issues and modelling approaches related to the relevant aspects of the semantic web technology and knowledge strategies. The paper also suggests a novel framework based on ontology metamodelling, knowledge model discovery, and semantic web infrastructures, architectures, languages, and systems. The main aim of the research enclosed in this paper is to bridge the gaps between enterprise engineering, modelling, and especially networking by intensively applying semantic web technology based on ontology conceptual representations and knowledge discovery. The ontological modelling approaches together with knowledge strategies such as discovery (data mining) have become promising for future enterprise computing systems. The related reported research deals with the conceptual definition of a semantic-driven framework and a manufacturing enterprise metamodel (ME_M) using ontology, knowledge-driven object models, standards, and architectural approaches applied to collaborative networked enterprises. The conceptual semantic framework and related issues discussed in this paper may contribute towards new approaches of enterprise systems engineering and networking as well as applied standard and referenced ontological models
Model Driven Combat Effectiveness Simulation Systems Engineering
Model-driven engineering has become popular in the combat effectiveness simulation systems engineering during these last years. It allows to systematically develop a simulation model in a composable way. However, implementing a conceptual model is really a complex and costly job if this is not guided under a well-established framework. Hence this study attempts to explore methodologies for engineering the development of simulation models. For this purpose, we define an ontological metamodelling framework. This framework starts with ontology-aware system conceptual descriptions, and then refines and transforms them toward system models until they reach final executable implementations. As a proof of concept, we identify a set of ontology-aware modelling frameworks in combat systems specification, then an underwater targets search scenario is presented as a motivating example for running simulations and results can be used as a reference for decision-making behaviors
A cost model for ontology engineering
In this report we propose a methodology for cost estimation for ontologies and
analyze cost factors implied in the engineering process. We examine the
appropriateness of a COCOMO-like parametric approach to ontology cost
estimation and propose a non-calibrated ontology cost model, which is to be
continuously refined along with the collection of empiric data on person month
efforts invested in developing ontologies in real-world projects. We further
describe the human-driven evaluation of the cost drivers described in the
parametric model on the basis of the cost models’ quality framework by
Boehm[5
Automatizing the Evaluation of Model Matching Systems
International audienceModel-Driven Engineering (MDE) and the Semantic Web are valuable paradigms. This paper sketches how to use a scientific and technical result around MDE in the Semantic Web. The work proposes a mechanism to automatize the evaluation of model matching algorithms. The mechanism involves megamodeling and a Domain Specific Language named AML (AtlanMod Matching Language). AML allows to implement matching algorithms in a straightforward way. We present how to adapt the mechanism to the ontology context, for example, to the Ontology Alignment Evaluation Initiative (OAEI)
- …