• Journal of the Korea Society of Computer and Information
• /
• v.17 no.8
• /
• pp.71-80
• /
• 2012

Much research has been recently accomplished for standardization in cloud computing. However, little research on standardization of data sharing and exchanging has been studied. Most of all, the corresponding standardization organization suggests no specific standardization items and reference model. This paper defines the current standardization problems and proposes a set of specific standardization items and a reference model for supporting the semantic interoperability. To achieve the goal of this paper, the overall standardization trend in cloud computing is first analyzed. Especially, this paper describes the status of standard development for addressing the semantic interoperability of data. This paper also defines the potential standardization items based on the concepts of standards in the data exchanging and management field, which are used for developing standards in various fields. Finally, the reference model is describe to show the relationships between items and overall semantic interoperability process. This paper can be used as a guideline for development of standards and also can facilitate standardization of cloud computing.

• IE interfaces
• /
• v.24 no.3
• /
• pp.248-257
• /
• 2011

The amount of Meta-data to be managed increases with development of information technology. However, when trying to integrate and share product information of heterogeneous systems within or between companies, sharing of information is impossible if product information classification systems are different. Due to the situation mentioned above, engineers judge the product information classification system and maps corresponding Meta-data for document-based sharing. Judging exponentially increasing amount of data by engineers and sharing product information using documents create great amount of time delay and errors in data handling. Therefore, construction of a system for integrated management and interoperability between product information based on semantic information similar to engineer's judgment is required. This paper proposes a methodology and necessity of a system for interoperability of product information based on semantic web, and also designs a system to integrate heterogeneous systems with different product information using rule based reasoning. This paper also suggests a system base for interoperability and integration of product information between heterogeneous systems by integrating the product information classification system semantically.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.05a
• /
• pp.1449-1452
• /
• 2004

It is necessary to resolve the syntax, structure and semantic heterogeneity for sharing information resources. And the representative technologies are XML and Metadata. XML has been used to represent the syntax and structure, and metadata has been used to represent the semantic meaning of information resources. However, various metadata sets in one or more domains that have been developed by each independent organizations without any standards or guidelines, make it difficult to share their information resource. In this paper, we propose an interoperability framework (FSMI, Framework for Sharable Metadata Interoperability) on MDR (Metadata Registry) to increase the interoperability of XML encoded information resources between systems using different metadata sets.

• Korean Journal of Computational Design and Engineering
• /
• v.9 no.2
• /
• pp.167-174
• /
• 2004

As the networks connect the world, enterprises tend to move manufacturing activities into virtual spaces. Since different applications use different data terminology, it becomes a problem to interoperate, interchange, and manage electronic data among different systems. According to RTI, approximately one billion dollar has been being spent yearly for product data exchange and interoperability. As commercial CAD systems have brought in the concept of design feature for the sake of interoperability, terminologies of design feature need to be harmonized. In order to define design feature terminology for integration, knowledge about feature definitions of different CAD systems should be considered. STEP (Standard for the Exchange of Product model data) have attempted to solve this problem, but it defines only syntactic data representation so that semantic data integration is unattainable. In this paper, we utilize the ontology concept to build a data model of design feature which can be a semantic standard of feature definitions of CAD systems. Using feature ontology, we implement an integrated virtual database and a simple system which searches and edits design features in a semantic way. This paper proposes a methodology for integrating modeling features of CAD systems.

• The Journal of Society for e-Business Studies
• /
• v.13 no.1
• /
• pp.1-20
• /
• 2008

Ontologies are expected in various areas as promising tools to improve communication among people and to achieve interoperability among systems. For communications between different business domains, building an ontology through integrating existing ontologies is more efficient way than building the ontology without them. However, integration of ontologies is very struggling work since languages, domains, and structures of ontologies are different from each other. In this paper, we suggest an Ontology Architecture which solves this problem by providing a systematic framework to classify ontologies from three kinds of viewpoints : language, domain range, constructs. The Ontology Architecture consists of 3 axes according to the 3 viewpoints : Ontology Meta Layer axis, Semantic Domain Layer axis, and Ontology Constructs Layer axis. Because 3 axes in Ontology Architecture are designed to improve the syntactic and semantic interoperability among ontologies, the integration of ontologies can be readily achieved.

• Journal of Internet Computing and Services
• /
• v.13 no.1
• /
• pp.107-115
• /
• 2012

In recent Information Environment, various Multimedia contents are getting noticed. But, since these contents have various formats of representation and very wide range of information, it was difficult to retrieve contents that user wanted and to utilize it. To solve these problems, many studies presented draft standards for adding metadata to contents, and then, semantic search for contents had become available. Unfortunately, as the number of metadata standards and contents increased, the lack of interoperability between contents was begun and users are faced with difficulty of search contents again. To improve these problems, this paper supports interoperability between metadata standards and expands the semantic relationship between elements and proposes an ontology which is named TOFIC(The Ontology For Imagery Contents) for enhanced semantic search. In TOFIC, the semantic relationships between MPEG-7 and TV-Anytime are classified, and extended new semantics are defined. As a result, semantic search for multimedia contents is enhanced and it is possible to retrieve most of the multimedia contents that exist on the current information environment consistently. In addition, it supports enhanced content-based search for multimedia contents.

• Journal of the Korean Society for information Management
• /
• v.27 no.2
• /
• pp.75-94
• /
• 2010

In the current information environment, metadata interoperability has become the predominant way of organizing and managing resources. However, current approaches to metadata interoperability focus on the superficial mapping between labels of metadata elements without considering semantics of each element. This research applied facet analysis to address these difficulties in achieving metadata interoperability. By categorizing metadata elements according to these semantic and functional similarities, this research identified different types of facets: basic, conceptual, and relational. Through these different facets, a faceted framework was constructed to mediate semantic, syntactical, and structural differences across heterogeneous metadata standards.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.97-99
• /
• 2011

As interoperability between systems in distributed environment has been important, it has been possible for various organizations to share resources and exchange relevant information. However, semantic heterogeneity between the systems and organizations causes the problem of making their interoperability impossible. Thereby, in this paper, we propose an ontology matching-based knowledge management system which can automatically discover semantic correspondences between ontologies. Moreover, even though there have been many existing ontology matchers, it is still difficult to directly apply them to the proposed system. To deal with the problems, we want to discover matching patterns (MP) which they discover from two given ontologies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.4
• /
• pp.881-902
• /
• 2024

Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy-hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.

• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.834-851
• /
• 2017

The amount of sources of information available on the web using ontologies as support continues to increase and is often heterogeneous and distributed. Ontology alignment is the solution to ensure semantic interoperability. In this paper, we describe a new ontology alignment approach, which consists of combining structure-based and reasoning-based approaches in order to discover new semantic correspondences between entities of different ontologies. We used the biblio test of the benchmark series and anatomy series of the Ontology Alignment Evaluation Initiative (OAEI) 2012 evaluation campaign to evaluate the performance of our approach. We compared our approach successively with LogMap and YAM++ systems. We also analyzed the contribution of our method compared to structural and semantic methods. The results obtained show that our performance provides good performance. Indeed, these results are better than those of the LogMap system in terms of precision, recall, and F-measure. Our approach has also been proven to be more relevant than YAM++ for certain types of ontologies and significantly improves the structure-based and reasoningbased methods.