The Experts below are selected from a list of 12774 Experts worldwide ranked by ideXlab platform
Wesley W Chu - One of the best experts on this subject based on the ideXlab platform.
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Schema conversion methods between xml and Relational models
Knowledge Transformation for the Semantic Web, 2003Co-Authors: Dongwon Lee, Murali Mani, Wesley W ChuAbstract:In this chapter, three semantics-based Schema conversion methods are presented: 1) CPI converts an XML Schema to a Relational Schema while preserving semantic constraints of the original XML Schema, 2) NeT derives a nested structured XML Schema from a flat Relational Schema by repeatedly applying the nest operator so that the resulting XML Schema becomes hierarchical, and 3) CoT takes a Relational Schema as input, where multiple tables are interconnected through inclusion dependencies and generates an equivalent XML Schema as output.
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effective Schema conversions between xml and Relational models
2002Co-Authors: Dongwon Lee, Murali Mani, Wesley W ChuAbstract:As Extensible Markup Language (XML) is emerging as the data format of the Internet era, there is an increasing need to efficiently store and query XML data. At the same time, as requirements change, we expect a substantial amount of conventional Relational data to be converted or published as XML data. One path to accommodate these changes is to transform XML data into Relational format (and vice versa) to use the mature Relational database technology. In this paper, we present three semantics-based Schema transformation algorithms towards this goal: 1) CPI converts an XML Schema to a Relational Schema while preserving semantic constraints of the original XML Schema, 2) NeT derives a nested structured XML Schema from a flat Relational Schema by repeatedly applying the nest operator so that the resulting XML Schema becomes hierarchical, and 3) CoT takes a Relational Schema as input, where multiple tables are interconnected through inclusion dependencies and generates an equivalent XML Schema as output.
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cpi constraints preserving inlining algorithm for mapping xml dtd to Relational Schema
Data and Knowledge Engineering, 2001Co-Authors: Dongwon Lee, Wesley W ChuAbstract:Abstract As Extensible Markup Language (XML) is emerging as the data format of the Internet era, there are increasing needs to efficiently store and query XML data. One path to this goal is transforming XML data into Relational format in order to use Relational database technology. Although several transformation algorithms exist, they are incomplete in the sense that they focus only on structural aspects and ignore semantic aspects. In this paper, we present the semantic knowledge that needs to be captured during transformation to ensure a correct Relational Schema. Further, we show an algorithm that can (1) derive such semantic knowledge from a given XML Document Type Definition (DTD) and (2) preserve the knowledge by representing it as semantic constraints in Relational database terms. By combining existing transformation algorithms and our constraints-preserving algorithm, one can transform XML DTD to Relational Schema where correct semantics and behaviors are guaranteed by the preserved constraints. Experimental results are also presented.
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constraints preserving transformation from xml document type definition to Relational Schema
Lecture Notes in Computer Science, 2000Co-Authors: Dongwon Lee, Wesley W ChuAbstract:As Extensible Markup Language (XML) [5] is emerging as the data format of the internet era, there are increasing needs to efficiently store and query XML data. One way towards this goal is using Relational database by transforming XML data into Relational format. In this paper, we argue that existing transformation algorithms are not complete in the sense that they focus only on structural aspects and ignoring semantic aspects. We present the semantic knowledge that needs to be captured during the transformation to ensure a correct Relational Schema. Further, we show a simple algorithm that can 1) derive such semantic knowledge from the given XML Document Type Definition (DTD) and 2) preserve the knowledge by representing them in terms of semantic constraints in Relational database terms. By combining the existing transformation algorithms and our constraints-preserving algorithm, one can transform XML DTD to Relational Schema where correct semantics and behaviors are guaranteed by the preserved constraints. Experimental results are also presented.
Dongwon Lee - One of the best experts on this subject based on the ideXlab platform.
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Schema conversion methods between xml and Relational models
Knowledge Transformation for the Semantic Web, 2003Co-Authors: Dongwon Lee, Murali Mani, Wesley W ChuAbstract:In this chapter, three semantics-based Schema conversion methods are presented: 1) CPI converts an XML Schema to a Relational Schema while preserving semantic constraints of the original XML Schema, 2) NeT derives a nested structured XML Schema from a flat Relational Schema by repeatedly applying the nest operator so that the resulting XML Schema becomes hierarchical, and 3) CoT takes a Relational Schema as input, where multiple tables are interconnected through inclusion dependencies and generates an equivalent XML Schema as output.
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effective Schema conversions between xml and Relational models
2002Co-Authors: Dongwon Lee, Murali Mani, Wesley W ChuAbstract:As Extensible Markup Language (XML) is emerging as the data format of the Internet era, there is an increasing need to efficiently store and query XML data. At the same time, as requirements change, we expect a substantial amount of conventional Relational data to be converted or published as XML data. One path to accommodate these changes is to transform XML data into Relational format (and vice versa) to use the mature Relational database technology. In this paper, we present three semantics-based Schema transformation algorithms towards this goal: 1) CPI converts an XML Schema to a Relational Schema while preserving semantic constraints of the original XML Schema, 2) NeT derives a nested structured XML Schema from a flat Relational Schema by repeatedly applying the nest operator so that the resulting XML Schema becomes hierarchical, and 3) CoT takes a Relational Schema as input, where multiple tables are interconnected through inclusion dependencies and generates an equivalent XML Schema as output.
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cpi constraints preserving inlining algorithm for mapping xml dtd to Relational Schema
Data and Knowledge Engineering, 2001Co-Authors: Dongwon Lee, Wesley W ChuAbstract:Abstract As Extensible Markup Language (XML) is emerging as the data format of the Internet era, there are increasing needs to efficiently store and query XML data. One path to this goal is transforming XML data into Relational format in order to use Relational database technology. Although several transformation algorithms exist, they are incomplete in the sense that they focus only on structural aspects and ignore semantic aspects. In this paper, we present the semantic knowledge that needs to be captured during transformation to ensure a correct Relational Schema. Further, we show an algorithm that can (1) derive such semantic knowledge from a given XML Document Type Definition (DTD) and (2) preserve the knowledge by representing it as semantic constraints in Relational database terms. By combining existing transformation algorithms and our constraints-preserving algorithm, one can transform XML DTD to Relational Schema where correct semantics and behaviors are guaranteed by the preserved constraints. Experimental results are also presented.
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constraints preserving transformation from xml document type definition to Relational Schema
Lecture Notes in Computer Science, 2000Co-Authors: Dongwon Lee, Wesley W ChuAbstract:As Extensible Markup Language (XML) [5] is emerging as the data format of the internet era, there are increasing needs to efficiently store and query XML data. One way towards this goal is using Relational database by transforming XML data into Relational format. In this paper, we argue that existing transformation algorithms are not complete in the sense that they focus only on structural aspects and ignoring semantic aspects. We present the semantic knowledge that needs to be captured during the transformation to ensure a correct Relational Schema. Further, we show a simple algorithm that can 1) derive such semantic knowledge from the given XML Document Type Definition (DTD) and 2) preserve the knowledge by representing them in terms of semantic constraints in Relational database terms. By combining the existing transformation algorithms and our constraints-preserving algorithm, one can transform XML DTD to Relational Schema where correct semantics and behaviors are guaranteed by the preserved constraints. Experimental results are also presented.
Chengfei Liu - One of the best experts on this subject based on the ideXlab platform.
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holistic constraint preserving transformation from Relational Schema into xml Schema
Database Systems for Advanced Applications, 2008Co-Authors: Rui Zhou, Chengfei LiuAbstract:In this paper, we propose a holistic scheme of transforming a Relational Schema into an XML Schema with integrity constraints preserved. This scheme facilitates constructing a Schema for the published XML views of Relational data. With this Schema, users are able to issue qualified queries against XML views, and discover update anomalies in advance before propagating the view updates into Relational database. Compared to the previous work which splits the transformation process into two steps, we establish a holistic solution to directly transform a Relational Schema into an XML Schema without building a reference graph. We achieve this by classifying the underlying relations in a more concise and effective way, and applying the converting rules wisely. The rules are also devised to be more compact and less complicated in contrast to those in our previous work. Finally, we manage to crack another hard nut which was seldom touched before, i.e. converting circularly referenced relations into recursive XML Schema.
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constraint preserving transformation from Relational Schema to xml Schema
World Wide Web, 2006Co-Authors: Chengfei Liu, Millist W Vincent, Jixue LiuAbstract:XML has become the standard for publishing and exchanging data on the Web. However, most business data is managed and will remain to be managed by Relational database management systems. As such, there is an increasing need to efficiently and accurately publish Relational data as XML documents for Internet-based applications. One way to publish Relational data is to provide virtual XML documents for Relational data via an XML Schema which is transformed from the underlying Relational database Schema such that users can access the Relational database through the XML Schema. In this paper, we discuss issues in transforming a Relational database Schema into the corresponding XML Schema. We aim to preserve all integrity constraints defined in a Relational database Schema, to achieve high level of nesting and to avoid introducing data redundancy in the transformed XML Schema. In the paper, we first propose a basic transformation algorithm which introduces no data redundancy, then we improve the algorithm by exploring further nesting of the transformed XML Schema.
Joseph Fong - One of the best experts on this subject based on the ideXlab platform.
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translating Relational Schema with constraints into xml Schema
International Journal of Software Engineering and Knowledge Engineering, 2006Co-Authors: Joseph Fong, Anthony S Fong, Hing Kwok Wong, Y U PhilipAbstract:With XML adopted as the technology trend on the Internet, and with investment in the current Relational database systems, companies must convert their Relational data into XML documents for data transmission on the Internet. In the process, to preserve the users' Relational data requirements of data constraints into the converted XML documents, we must define a meaningful root element for each XML document. The construction of an XML document is based on the root element and its relevant elements. The root element can be selected from a Relational entity table in the existing Relational database, which depends on the requirements to present the business behind. The relevant elements are mapped from the related entities, based on the navigability of the chosen entity. The derived root and relevant elements can form a Data Type Definition Graph (DTD-graph) of an XML conceptual Schema diagram which can be mapped into a Data Type Definition (DTD) of an XML Schema. The result is a translated XML Schema with semantic constraints transferred from a Relational conceptual Schema of an Extended Entity Relationship (EER) model. The data conversion from Relational data to the XML documents can be done after the Schema translation. The Relational data are loaded into XML documents according to the translated DTD.
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translating Relational Schema into xml Schema definition with data semantic preservation and xsd graph
Information & Software Technology, 2005Co-Authors: Joseph Fong, San Kuen CheungAbstract:Many legacy systems have been created by using Relational database operating not for the Internet expression. Since the Relational database is not an efficient way for data explosion, electronic transfer of data, and electronic business on the Web, we introduce a methodology in which a Relational Schema will be translated to an Extensible Markup Language (XML) Schema definition for creating an XML database that is a simple and efficient format on the Web. We apply the Indirect Schema Translation Method that is a semantic-based methodology in this project. The mechanism is that the Relational Schema will be translated into the conceptual model, an Extended Entity Relationship (EER) Model using Reverse Engineering. Afterward, the EER model will be mapped to an XML Schema Definition Language (XSD) Graph as an XML conceptual Schema using Semantic Transformation. Finally, the XSD Graph will be mapped into the XSD as an XML logical Schema in the process of Forward Engineering, and the data semantics of participation, cardinality, generalization, aggregation, categorization, N-ary and U-ary relationship are preserved in the translated XML Schema definition.
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converting Relational to object oriented databases
International Conference on Management of Data, 1997Co-Authors: Joseph FongAbstract:As object-oriented model becomes the trend of database technology, there is a need to convert Relational to object-oriented database system to improve productivity and flexibility. The changeover includes Schema translation, data conversion and program conversion. This paper describes a methodology for integrating Schema translation and data conversion. Schema translation involves semantic reconstruction and the mapping of Relational Schema into object-oriented Schema. Data conversion involves unloading tuples of relations into sequential files and reloading them into object-oriented classes files. The methodology preserves the constraints of the Relational database by mapping the equivalent data dependencies.
Steven Phillips - One of the best experts on this subject based on the ideXlab platform.
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a reconstruction theory of Relational Schema induction
PLOS Computational Biology, 2021Co-Authors: Steven PhillipsAbstract:Learning transfer (i.e. accelerated learning over a series of structurally related learning tasks) differentiates species and age-groups, but the evolutionary and developmental implications of such differences are unclear. To this end, the Relational Schema induction paradigm employing tasks that share algebraic (group-like) structures was introduced to contrast stimulus-independent (Relational) versus stimulus-dependent (associative) learning processes. However, a theory explaining this kind of Relational learning transfer has not been forthcoming beyond a general appeal to some form of structure-mapping, as typically assumed in models of analogy. In this paper, we provide a theory of Relational Schema induction as a "reconstruction" process: the algebraic structure underlying transfer is reconstructed by comparing stimulus relations, learned within each task, for structural consistency across tasks-formally, the theory derives from a category theory version of Tannakian reconstruction. The theory also applies to non-human studies of Relational concepts, thereby placing human and non-human transfer on common ground for sharper comparison and contrast. As the theory and paradigm do not depend on linguistic ability, we also have a way for pinpointing where aspects of human learning diverge from other species without begging the question of language.
