Converting relational databases into object relational databases

This paper proposes an approach for migrating existing Relational DataBases (RDBs) into Object-Relational DataBases (ORDBs). The approach is superior to existing proposals as it can generate not only the target schema but also the data instances. The solution takes an existing RDB as input, enriches its metadata representation with required semantics, and generates an enhanced canonical data model, which captures essential characteristics of the target ORDB, and is suitable for migration. A prototype has been developed, which migrates successfully RDBs into ORDBs (Oracle 11g) based on the canonical model. The experimental results were very encouraging, demonstrating that the proposed approach is feasible, efficient and correct

ARDI: automatic generation of RDFS models from heterogeneous data sources

The current wealth of information, typically known as Big Data, generates a large amount of available data for organisations. Data Integration provides foundations to query disparate data sources as if they were integrated into a single source. However, current data integration tools are far from being useful for most organisations due to the heterogeneous nature of data sources, which represents a challenge for current frameworks. To enable data integration of highly heterogeneous and disparate data sources, this paper proposes a method to extract the schema from semi-structured (such as JSON and XML) and structured (such as relational) data sources, and generate an equivalent RDFS representation. The output of our method complements current frameworks and reduces the manual workload required to represent the input data sources in terms of the integration canonical data model. Our approach consists of production rules at the meta-model level that guarantee the correctness of the model translations. Finally, a tool for implementing our approach has been developed.Peer ReviewedPostprint (author's final draft

Generating natural language specifications from UML class diagrams

Early phases of software development are known to be problematic, difficult to manage and errors occurring during these phases are expensive to correct. Many systems have been developed to aid the transition from informal Natural Language requirements to semistructured or formal specifications. Furthermore, consistency checking is seen by many software engineers as the solution to reduce the number of errors occurring during the software development life cycle and allow early verification and validation of software systems. However, this is confined to the models developed during analysis and design and fails to include the early Natural Language requirements. This excludes proper user involvement and creates a gap between the original requirements and the updated and modified models and implementations of the system. To improve this process, we propose a system that generates Natural Language specifications from UML class diagrams. We first investigate the variation of the input language used in naming the components of a class diagram based on the study of a large number of examples from the literature and then develop rules for removing ambiguities in the subset of Natural Language used within UML. We use WordNet,a linguistic ontology, to disambiguate the lexical structures of the UML string names and generate semantically sound sentences. Our system is developed in Java and is tested on an independent though academic case study

Modeling views in the layered view model for XML using UML

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

A Model Driven Approach to Model Transformations

The OMG's Model Driven Architecture (MDA) initiative has been the focus of much attention in both academia and industry, due to its promise of more rapid and consistent software development through the increased use of models. In order for MDA to reach its full potential, the ability to manipulate and transform models { most obviously from the Platform Independent Model (PIM) to the Platform Specific Models (PSM) { is vital. Recognizing this need, the OMG issued a Request For Proposals (RFP) largely concerned with finding a suitable mechanism for trans- forming models. This paper outlines the relevant background material, summarizes the approach taken by the QVT-Partners (to whom the authors belong), presents a non-trivial example using the QVT-Partners approach, and finally sketches out what the future holds for model transformations

Exploiting Visual Languages Generation and UML Meta Modeling to Construct Meta-CASE Workbenches

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A messaging system to handle semantic dissonance

Enterprises have been compelled to share their data internally and externally, but creating a consistent view of enterprise data has been challenging. Within a typical enterprise, each division uses its own domain specific data model and schema, and different enterprises obviously use their own data models and schema. Integrating these diverse data models and schemas, which have both syntactic and semantic differences, tends to be complex, slow, and inaccurate. Syntactic differences, i.e., differences in names or layout, have received substantial attention in research. Semantic dissonance simply means that the structure may be similar (or even the same) but the meaning associated with the attributes that define each structure are different, has received less attention in the world of practical software development. A practical messaging system for handling semantic dissonance has been developed. The system utilizes the Resource Description Framework (RDF) and SOAP XML Messaging Specification. It is implemented using Jena, a Java API for RDF, and the Apache SOAP, an Open Source SOAP server and client. This report describes the messaging system, its implementation, its strengths and limitations in handling semantic dissonance

Design and Implementation of a Conceptual Modeling Assistant (CMA)

This Master's Thesis de nes an architecture for a Conceptual Modeling Assistant (CMA) along with an implementation of a running prototype. Our CMA is a piece of software that runs on top of current modeling tools whose purpose is to collaborate with the conceptual modelers while developing a conceptual schema. The main functions of our CMA are to actively criticize the state of a conceptual schema, to suggest actions to do in order to improve the conceptual schema, and to o er new operations to automatize building a schema. On the one hand, the presented architecture assumes that the CMA has to be adapted to a modeling tool. Thus, the CMA permits the inclusion of new features, such as the detection of new defects to be criticized and new operations a modeler can execute, in a modeling tool. As a result, all modeling tools to which the CMA is adapted bene t of all these features without further work. On the other hand, the construction of our prototype involves three steps: the de nition of a simple, custom modeling tool; the implementation of the CMA; and the adaptation of the CMA to the custom modeling tool. Furthermore, we also present and implement some examples of new features that can be added to the CMA