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The development of increasingly complex systems with improved quality levels becomes more and more challenging. Engineering data frameworks with integrated system models have been developed to manage such systems. This paper presents the experiences that have been made in digital systems engineering in the aerospace domain and focuses on the roadmap that has been taken to establish a knowledge engineering...
Medical search technologies are crucial to enable the user to rapidly and effectively discover useful information from massive medical and clinical data. Because of the complexity of medical terminology, traditional information search methods have not fully expressed the intention of the query request and explored the potential semantic knowledge in the document. In this paper, we propose a multi-analysis...
Model-based Systems Engineering requires an intuitive semantically strong data model to enable precise data specification and provide the foundation for fruitful data analyses during data evolution. This paper presents an approach to use the Web Ontology Language (OWL) for specifying a Conceptual Data Model (CDM) being transformed into a format understandable by the Eclipse Modeling Framework (EMF)...
Biomedical information systems (BIS) require consideration of three types of variability: data variability induced by new high throughput technologies, schema or model variability induced by large scale studies or new fields of research, and knowledge variability resulting from new discoveries. Beyond data heterogeneity, managing variabilities in the context of BIS requires extensible and dynamic...
Big Data Era brings two main dimensions, which are heterogeneity and contextual data. The heterogeneity may occur at syntax and semantic levels. Ontologies are largely used to reduce these heterogeneities. Data has limited value if not paired with its context. Usually the internal data of companies are not connected to the rest of data universe including news, weather, user profiles, etc. In Engineering...
The complexity of systems like Systems of Systems leads to very time-consuming modeling tasks. Standards such as modeling languages, frameworks, etc. have been developed by organizations to master this complexity. Although they are useful, almost mandatory, having them systematically as the entry point of modeling adds new complexity challenges causing additional costs in Systems Engineering activities...
Modelling and model transformation are regarded as two pillars of model-driven engineering; they have been used together to solve practical problems. For instance, since different models (e.g. data model) are used by heterogeneous partners involved in a specific collaborative situation, there is an urgent need for model transformations to exchange information among the heterogeneous partners. To quickly...
The design and development of aerospace product is a collaborative multi-discipline project. The integrated and consistent information modeling of all the information, models, documents and other product data generated during design and development is critical to success. An integrated information model, defined as EDPS (Engineering Digital Prototyping for Satellite) is proposed. Aiming at modeling...
Nowadays, ontology as a knowledge sharing approach plays an important role in semantic interoperability of enterprise applications (EAs). However, the manual process of ontology construction requires deep understanding of the domain. This approach is difficult, expensive and time-consuming. To overcome the knowledge acquisition bottleneck, ontology learning field aims to provide automatic and semi-automatic...
Information integration, interoperability and adaptation to evolving data are the key components of clinical information system with high potential impact. Most existing systems accomplish integration and interoperability by employing specific data model standards with static mapping rules that makes system inflexible and inextensible. In response to this drawback, we present Health-Connect system...
This paper describes a way to better navigate in an ever increasing number of standards in the field of ITS. Short overview about fundamental ITS models is presented, the principle of related knowledge system is described. Ontology approach is used, especially as domain oriented ITS ontology, where a new hybrid method is explained.
This paper presents a method toward building semantic enriched product model. It can be applied to different stages throughout product lifecycle and mainly comprised of two steps: semantics extracting and semantics enhancing. Semantics extracting is performed based on fully utilizing preexisting product data models and explicates implicit characteristics and the meanings behind modeling elements....
The financial services industry presents some unique challenges in data integration, both within firms and across the securities trading process. This paper describes how the industry came to an awareness of the need to define semantics as an industry wide standard, and the methods and processes used to realize that requirement in the form of an industry Semantics Repository. The repository is described...
The main reason why conceptual modeling is still considered an "art" rather than a mature engineering discipline is that the quality evaluation system of conceptual model has not been well established. In order to address this problem, based on ISO/IEC 25012, 25020 standards, and combined with extensive research and experiences of experts, we propose the preliminary ontology for classifying...
In the process of data integration, the traditional methods are difficult to solve the problems, what are the large amounts of data redundancy, faintness of Information representation, heterogeneous data and so on. The combination of emerging technology and XML-DTD technology can solve the above problem better. This paper analyzes the characteristics of gas accident of the coalfield, creating an OWL...
Ontologies are put forward to resolve the problem of information integration and heterogeneous knowledge sharing. Aiming at the issue of data redundancy and inefficient sharing, we propose a data sharing framework of microscopic traffic simulation and GIS based on ontology driven. The building process of requirement, analysis, design and implementation of the microscopic traffic simulation ontology...
Scientific digital libraries serve complex and evolving research communities. Justifications for the development of scientific digital libraries include the desire to preserve science data and the promises of information interconnectedness, correlative science, and system interoperability. Shared ontologies are fundamental to fulfilling these promises. We present a tool framework, a set of principles,...
Most service and network management applications are developed to use vendor- and device-specific management data. These data are produced from different languages, and hence can have different representations of the same concept. We define a novel knowledge representation and mapping mechanism that uses ontological concepts and relations to generate a formal description for the Directory Enabled...
The paper analyzes the current situation of business environment and business intelligence systems (BIS) framework at first, and studies the theoretics and methods about the business intelligence system based on ontology. Based on ontology, this paper proposes an integration framework for business intelligence systems. A service resource based-ontology is proposed in this research, including the data...
Seamless mobility has been described as providing collaborative mechanisms that enable a user to accomplish his or her tasks without regard to technology, type of media, or device. This paper examines how the FOCALE autonomic architecture, in conjunction with a novel understanding of the environment based on the integration of information models and ontologies, can realize these challenges.
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