• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.173-181
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• 2009

This paper proposes an algorithm to transform RDF(Resource Description Framework) models for ontology into CPN(Colored Petri Net) models. The algorithm transforms the semantics of the RDF model into the topology of the CPN by mapping the classes and the properties of the RDF onto the places of the CPN model then reflects the RDF statements on the CPN by representing the relationships between them as token transitions on the CPN. The basic idea of reflecting the RDF statements on the CPN is to generate a token, which is an ordered pair consisting of two tokens (one from the place mapped into the subject and the other one from the place mapped into the object) and transfer it to the place mapped into the predicate. We have actually built CPN models for given RDF models on the CNPTools and inferred and extracted answers to the RDF queries on the CPNTools.

• The Journal of Society for e-Business Studies
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• v.12 no.2
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• pp.291-304
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• 2007

The Resource Description Framework(RDF) utilized for the representation and storage of information in various application, plays an important role in the Semantic Web, the next generation web. A number of RDF systems have been implemented for retrieval of RDF metadata. However, they do not provide the sufficient performance for the querying function of practical application system. In this paper we describe the design and implementation of RDF system, SMARTTriple, which has a RDF storage structures using index map and provides the better performance than the previous systems. We present a performance comparison results with the well-known RDF systems. SMARTTriple will be a great contribution to the research and development of Semantic Web application.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.112-124
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• 2008

RDF and OWL are the primary base technologies for implementing Semantic Web. Recently, many researches related with them, or applying them into the other application domains, have been introduced. However, relatively little work has been done for securing the RDF and OWL data. In this article, we briefly introduce an RDF triple based model for specifying RDF access authorization related with RDF security. Next, to efficiently find the authorization conflict by RDF inference, we introduce a method using prime number graph labeling in detail. The problem of authorization conflict by RDF inference is that although the lower concept is permitted to be accessed, it can be inaccessible due to the disapproval for the upper concept. Because by the RDF inference, the lower concept can be interpreted into the upper concept. Some experimental results show that the proposed method using the prime number graph labeling has better performance than the existing simple method for the detection of the authorization conflict.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.422-433
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• 2009

As an effort to secure Semantic Web, in this paper, we introduce an RDF access authorization model based on an ontology hierarchy and an RDF triple pattern. In addition, we apply the authorization model to RDF query validation for approved access authorizations. A subscribed SPARQL or RQL query, which has RDF triple patterns, can be denied or granted according to the corresponding access authorizations which have an RDF triple pattern. In order to efficiently perform the query validation process, we first analyze some primary authorization conflict conditions under RDF subsumption inference, and then we introduce an efficient query validation algorithm using the conflict conditions and Dewey graph labeling technique. Through experiments, we also show that the proposed validation algorithm provides a reasonable validation time and when data and authorizations increase it has scalability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.487-494
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• 2022

With the recent demand for analysis using data, the size of the knowledge graph, which is the data to be analyzed, gradually increased, reaching about 82 billion edges when extracted from the web as a knowledge graph. A lot of knowledge graphs are represented in the form of Resource Description Framework (RDF), which is a standard of W3C for representing metadata for web resources. Because of the characteristics of RDF, existing RDF storages have the limitations of processing time overhead when converting and storing large amounts of RDF data. To resolve these limitations, in this paper, we propose a method of compressing and converting large amounts of RDF data into integer IDs using MapReduce, and vertically partitioning and storing them. Our proposed method demonstrated a high performance improvement of up to 25.2 times compared to RDF-3X and up to 3.7 times compared to H2RDF+.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.11-16
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• 2008

본 논문은 온톨로지(ontology) 작성에 사용되는 RDF(Resource Description Framework) 모델을 CPN(Colored Petri Net) 모델로 변환하여 표현하는 방법을 제안하고, 페트리 넷 시뮬레이션으로 RDF의 의미를 해석하여 RDF 질의문에 답할 수 있음을 보인다. 또한, 어떠한 RDF 모델도 CPN 모델로의 변환이 가능하다는 제안 방법의 완전성과 무결성을 소개하고, 제안한 방법으로 구축된 CPN 모델에서 RDF 질의에 대해 정확하게 결과를 구하는 방법을 제시한다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.29-40
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• 2000

With increasing amounts of information on the web and needs to access accurately them, it is very important to standardize metadata and to store and manage system. The RDF(Rdsource Description Framework) is a framework for representing exchanging, and reusing metadata. And, it can be processing uniformly the standardized metadata, because it uses XML(eXtensible Markup Language) syntax. The RDF schema provides a basic type system for use RDF models. In this paper, we propose rules and an algorithm to convert the RDF schema into an UML(Unified Modeling Language) class diagram and formal models to represent an object-oriented schema for the RDF schema. The proposed rules and algorithm are useful for natural mapping and the object modeling of RDF schema can be easily converted into the object-oriented schema, and the formal models supports an efficient environment for retrieving and processing object-oriented documents.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.158.1-158.1
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• 2010

국내 최초의 생활폐기물고형연료(RDF) 생산플랜트인 원주시 RDF플랜트의 2009년도 운영실적을 정리하여 폐기물 처리단가를 분석하였으며 에너지 생산 효과도 분석하였다. 실적분석에 사용된 자료는 원주 RDF플랜트 위탁운영업체가 운영비를 청구 및 정산하기 위해서 원주시에 상시 측정 및 보고하는 항목으로서, 내용은 트럭으로 플랜트에 반입되는 폐기물 전체량, RDF생산 전체량, 불순물 매립 전체량, 건조 및 탈취용 연료사용 전체량, 전기사용 전체량 등이다. 2009년도 원주시 RDF플랜트에 반입된 폐기물 량은 총 17,504톤이었고, RDF를 총 7,044톤 생산하였으며, 4,120톤의 불연물을 선별하였다. 1년간 사용한 건조 및 탈취용 연료는 총 596,268 리터였으며 연료인 부생유의 가격은 리터 당 평균 864.6원이었다. 사용한 전기량은 총 2,435,397 kWh였고, 이 중에서 성형공정에 사용된 전기량은 총 사용량의 19%였다. 이상의 기록자료들을 분석해 본 결과, 폐기물 1톤을 처리하는데 전기 비용이 14,334원이었고, 연료비가 29,452원이었다. 여기에 폐기물 1톤당 불연물 매립비 6,573원과 위탁인건비를 합하면 폐기물 1톤당 처리비용은 약 116,573원으로 나타났다. 현재 원주시 RDF는 톤당 25,000원에 판매되고 있으므로 이 비용을 감안하면 폐기물 1톤당 처리비용은 105,298원으로 산출되었다. 현재 알려진 유사 규모의 소각로 운영비가 폐기물 1톤당 136,736원인데, 이것은 RDF기술보다 31,438원/톤-폐기물 정도 처리비용이 비싸다. 따라서 100톤 이하 규모의 폐기물처리시설 설치를 할 경우에는 RDF 시설이 경제적으로 타당함을 나타낸다. 원주시 RDF플랜트의 물질수지를 분석해 본 결과, RDF생산 수율은 40.2%였으며 총 투입된 에너지는 8,0587 Gcal였다. 생산된 에너지 총량은 RDF발열량 4,500 kcal/kg으로 했을 때 31,699 Gcal로 나타났다. 투입대비 생산에너지 비율은 25.4%로 계산되었고, 전기의 발전효율을 40%로 감안했을 경우에는 35.3%로 계산되었다. 성형하는데 사용되는 총 에너지는 전체 투입에너지의 4.9%로 나타났고, 비용으로는 폐기물 1톤당 2,723원 이었다.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.518-527
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• 2007

It is an important issue to find out the difference between RDF documents, because RDF documents are changed frequently. When RDF documents contain blank nodes, we need a matching technique for blank nodes in the change detection. Blank nodes have a nested form and they are used in most RDF documents. A RDF document can be modeled as a graph and it will contain many subtrees. We can consider a change detection problem as a minimum cost tree matching problem. In this paper, we propose a change detection technique for RDF documents using the labeling scheme for blank nodes. We also propose a method for improving the efficiency of general triple matching, which used predicate grouping and partitioning. In experiments, we showed that our approach was more accurate and faster than the previous approaches.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.197-202
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• 2010

Recent studies on change detection for RDF data are focused on not only the structural difference but also the semantic-aware difference by computing the closure of RDF models. However, since these techniques which take into account the semantics of RDF model require both RDF models to be memory resident, or they use a forward-chaining strategy which computes the entire closure in advance, it is not efficient to apply them directly to detect changes in large RDF data. In this paper, we propose a scalable change detection technique for RDF data, which uses a backward-chaining inference based on relational database. Proposed method uses a new approach for RDF reasoning that computes only the relevant part of the closure for change detection in a relational database. We show that our method clearly outperforms the previous works through experiment using the real RDF from the bioinformatics domain.