136 research outputs found

    Error propagation metrics from XMI

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    This work describes the production of an application Error Propagation Metrics from XMI which can extract process and display software design metrics from XMI files. The tool archives these design metrics in a standard XML format defined by a metric document type definition.;XMI is a flavour of XML allowing the description of UML models. As such, the XMI representation of a software design will include information from which a variety of software design metrics can be extracted. These metrics are potentially useful in improving the software design process, either throughout the early stages of design if a suitable XMI-enabled modelling tool is deployed, or to enable the comparison of completed software projects, by extracting design metrics from UML models reverse engineered from the implemented source code.;The tool is able to derive the error propagation of metrics from test XMI files created from UML sequence and state diagrams and from reverse engineered Java source code. However, variation was observed between the XMI representations generated by different software design tools, limiting the ability of the tool to process XMI from all sources. Furthermore, it was noted that subtle differences between UML design representations might have a marked effect on the quality of metrics derived.;In conclusion in order to validate the usefulness of these metrics that can be extracted from XMI files it would be useful to follow well-documented design projects throughout the total design and implementation process. Alternatively, the tool might be used to compare metrics from well-matched design implementations. In either case design metrics will only be of true value to software engineers if they can be associated empirically with a validated measure of system quality

    A Survey on Mapping Semi-Structured Data and Graph Data to Relational Data

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    The data produced by various services should be stored and managed in an appropriate format for gaining valuable knowledge conveniently. This leads to the emergence of various data models, including relational, semi-structured, and graph models, and so on. Considering the fact that the mature relational databases established on relational data models are still predominant in today's market, it has fueled interest in storing and processing semi-structured data and graph data in relational databases so that mature and powerful relational databases' capabilities can all be applied to these various data. In this survey, we review existing methods on mapping semi-structured data and graph data into relational tables, analyze their major features, and give a detailed classification of those methods. We also summarize the merits and demerits of each method, introduce open research challenges, and present future research directions. With this comprehensive investigation of existing methods and open problems, we hope this survey can motivate new mapping approaches through drawing lessons from eachmodel's mapping strategies, aswell as a newresearch topic - mapping multi-model data into relational tables.Peer reviewe

    Modeling views in the layered view model for XML using UML

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    In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

    X-Databases - The Integration of XML into Enterprise Database Management Systems

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    An examination of how the eXtensible Markup Language (XML) and database management systems (DBMS) fit together, and current approaches to providing database technologies that support XML. Analysis of how XML is being deployed in four classes of XML Database (X-Database) applications provides a basis for understanding the direction of X-Database technology and associated standards. In a simple implementation, an XML Document Type Definition (DTD) is mapped to relational structures, and XML data are stored in a DBMS (Oracle8i). Sample queries are presented to retrieve XML from the database. A middleware tool (XSQL Java Servlet) is used to transform query results into records on a Web page. The results demonstrate that relational databases require data to be rigidly mapped to relational structures. The paper concludes by exploring future challenges to integrating XML and DTDs with X-Databases, which establishes the need for a more "native" integration approach

    Electronic Medical Records

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    Electronic Medical Record (EMR) relational database is considered to be a major component of any medical care information system. A major problem for researchers in medical informatics is finding the best way to use these databases to extract valued useful information to and about the patient’s diseases and treatments. Integrating different EMR databases is a great achievement that will improve health care systems. This paper presents an AI approach to extract generic EMR from different resources and transfer them to clinical cases. The utilized approach is based on retrieving different relationships between patients’ different data tables (files) and automatically generating EMRs in XML format, then building frame based medical cases to form a case repository that can be used in medical diagnostic systems

    Migrating relational databases into object-based and XML databases

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    Rapid changes in information technology, the emergence of object-based and WWW applications, and the interest of organisations in securing benefits from new technologies have made information systems re-engineering in general and database migration in particular an active research area. In order to improve the functionality and performance of existing systems, the re-engineering process requires identifying and understanding all of the components of such systems. An underlying database is one of the most important component of information systems. A considerable body of data is stored in relational databases (RDBs), yet they have limitations to support complex structures and user-defined data types provided by relatively recent databases such as object-based and XML databases. Instead of throwing away the large amount of data stored in RDBs, it is more appropriate to enrich and convert such data to be used by new systems. Most researchers into the migration of RDBs into object-based/XML databases have concentrated on schema translation, accessing and publishing RDB data using newer technology, while few have paid attention to the conversion of data, and the preservation of data semantics, e.g., inheritance and integrity constraints. In addition, existing work does not appear to provide a solution for more than one target database. Thus, research on the migration of RDBs is not fully developed. We propose a solution that offers automatic migration of an RDB as a source into the recent database technologies as targets based on available standards such as ODMG 3.0, SQL4 and XML Schema. A canonical data model (CDM) is proposed to bridge the semantic gap between an RDB and the target databases. The CDM preserves and enhances the metadata of existing RDBs to fit in with the essential characteristics of the target databases. The adoption of standards is essential for increased portability, flexibility and constraints preservation. This thesis contributes a solution for migrating RDBs into object-based and XML databases. The solution takes an existing RDB as input, enriches its metadata representation with the required explicit semantics, and constructs an enhanced relational schema representation (RSR). Based on the RSR, a CDM is generated which is enriched with the RDB's constraints and data semantics that may not have been explicitly expressed in the RDB metadata. The CDM so obtained facilitates both schema translation and data conversion. We design sets of rules for translating the CDM into each of the three target schemas, and provide algorithms for converting RDB data into the target formats based on the CDM. A prototype of the solution has been implemented, which generates the three target databases. Experimental study has been conducted to evaluate the prototype. The experimental results show that the target schemas resulting from the prototype and those generated by existing manual mapping techniques were comparable. We have also shown that the source and target databases were equivalent, and demonstrated that the solution, conceptually and practically, is feasible, efficient and correct

    A Flexible Schema-Aware Mapping of XML Data into Relational Models

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    In the last several years, substantial contributions have been made in the development of techniques to transform and store eXtensible Markup Language (XML) data into relational database models. Although there exists rich literature in this field, none of the existing procedures provides a complete solution in a single framework as many of the existing solutions propose automating the conversion. However, a purely automated approach has limitations. Due to the heterogeneous and hierarchical nature of XML for a given input, there can be numerous reasonable relational schemas and automated systems may not be able to address all the possible schemas. Providing Human guidance can help to identify appropriate relational schema in complex XML documents for use in highly structured data applications. We propose an integrated system that provides an end-to-end solution for the user-guided mapping of XML into relational data. Our system accomplishes the translation in three stages: (1)Parse an XML Schema Definition (XSD) file to suggest relational schema; (2) allow users to alter the schema using the user interface to determine appropriate schema; and (3) populate relational tables using an input XML document. The system extracts key information from the input file and introduces new constraints wherever required as keys are crucial for a good database design. The User Interface is the key component of our system, enables users to perform certain operations on the suggested schema to achieve a reliable relational schema. The Digital Latin Library (DLL) is a joint project with a vision to introduce an open collaborative environment that allows users to explore latin texts critical editions and engage them in intellectual conversations. Here, visualizations are chosen for enabling scholarly conversations. Text Encoding Initiative (TEI) is often used for the representation of critical editions. TEI is a markup language to create digital versions of texts and its structure is similar to XML. To achieve DLL objectives, we devised a supporting system to read XML structure into a relational data model. This data model, in turn, supports the development of a variety of visualization queries
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