A layered view model for XML with conceptual and logical extensions, and its applications

University of Technology, Sydney. Faculty of Information Technology.EXtensible Markup Language (XML) is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems (EIS), web repositories and databases. With this increasing reliance on such self-describing, schema-based, semi-structured data language XML, there exists a need to model, design, and manipulate XML and associated semantics at a higher level of abstraction than at the instance level. However, existing OO conceptual modelling languages provide insufficient modelling constructs for utilizing XML structures, descriptions and constraints, and XML and associated schema languages lack the ability to provide higher levels of abstraction, such as conceptual models that are easily understood by humans. To this end, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data modelling. In particular we note that there is a strong need to model views of XML repositories at the conceptual level. This is in contrast to the situation for views for the relational model which are generally defined at the implementation level. In this research, we use XML view and introduce the Layered View Model (LVM, for short), a declarative conceptual framework for specifying and defining views at a higher level of abstraction. The views in the LVM are specified using explicit conceptual, logical and instance level semantics and provide declarative transformation between these levels of abstraction. For such a task, an elaborated and enhanced OO based modelling and transformation methodology is employed. The LVM framework leads to a number of interesting problems that are studied in this research. First we address the issue of conceptualizing the notion of views: the clear separation of conceptual concerns from the implementation and data language concerns. Here, the LVM views are considered as first-class citizens of the conceptual model. Second we provide formal semantics and definitions to enforce representation, specification and definition of such views at the highest level of abstraction, the conceptual level. Third we address the issue of modelling and transformation of LVM views to the required level of abstraction, namely to the schema and instance levels. Finally, we apply LVM to real-world data modelling scenarios to develop other architectural frameworks in the domains such as dimensional XML data modelling, ontology views in the Semantic Web paradigm and modelling user-centred websites and web portals

Alternative representations for visual constrainst specification in the layered view model

Extensible Markup Language (XML), with its rich set of semantics and constraints, is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems (EIS) and databases. With the increased reliance on such semi-structured data and schemas, there exists a requirement to model, design, and constrain semi-structured data and the associated semantics at a higher level of abstraction than at the instance or data level. But most semi-structured schema languages lack the ability to provide higher levels of abstraction, such as visual constraints, that are easily understood by humans. Conversely, though Object-Oriented (OO) conceptual models offers the power in describing and modelling real-world data semantics, constraints and their inter-relationships in a form that is precise and comprehensible to users, they provide insufficient modelling constructs for utilizing XML schema like data descriptions and constraints. Therefore, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data engineering. In this paper, we present a visual constraint specification model for an XML layered view model. First we briefly outline the view model and then provide a detailed discussion on modelling issues related to view constraint specification using two OO modelling languages, namely OMG's UML/OCL and XML Semantics (XSemantic) nets. To demonstrate our concepts, we also provide an illustrative case study example based on a real-world application

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database

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

UML Class Diagram or Entity Relationship Diagram : An Object Relational Impedance Mismatch

It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model –towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to ithave been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram forconceptual modeling for relational databases, and several popular course text books use UMLnotation to some degree [2] [3]. However Object and Relational technology are based on different paradigms. In the paper we argue that the UML class diagram is more of a logical model (implementation specific). ER Diagrams on theother hand, are at a conceptual level of database design dealing with the main items and their relationships and not with implementation specific detail. UML focuses on OOAD (Object Oriented Analysis and Design) and is navigational and program dependent whereas the relational model is set based and exhibits data independence. The ER model provides a well-established set of mapping rules for mapping to a relational model. In this paper we look specifically at the areas which can cause problems for the novice databasedesigner due to this conceptual mismatch of two different paradigms. Firstly, transferring the mapping of a weak entity from an Entity Relationship model to UML and secondly the representation of structural constraints between objects. We look at the mixture of notations which students mistakenly use when modeling. This is often the result of different notations being used on different courses throughout their degree. Several of the popular text books at the moment use either a variation of ER,UML, or both for teaching database modeling. At the moment if a student picks up a text book they could be faced with either; one of the many ER variations, UML, UML and a variation of ER both covered separately, or UML and ER merged together. We regard this problem as a conceptual impedance mismatch. This problem is documented in [21] who have produced a catalogue of impedance mismatch problems between object-relational and relational paradigms. We regard the problems of using UML class diagrams for relational database design as a conceptual impedance mismatch as the Entity Relationship model does not have the structures in the model to deal with Object Oriented concepts Keywords: EERD, UML Class Diagram, Relational Database Design, Structural Constraints, relational and object database impedance mismatch. The ER model was originally put forward by Chen [1] and subsequently extensions have been added to add further semantics to the original model; mainly the concepts of specialisation, generalisation and aggregation. In this paper we refer to an Entity-Relationship model (ER) as the basic model and an extended or enhanced entity-relationship model (EER) as a model which includes the extra concepts. The ER and EER models are also often used to aid communication between the designer and the user at the requirements analysis stage. In this paper when we use the term “conceptual model” we mean a model that is not implementation specific.ISBN: 978-84-616-3847-5 3594Peer reviewe

XML views, part III: An UML based design methodology for XML views

Object-Oriented (OO) conceptual models have the power in describing and modelling real-world data semantics and their inter-relationships in a form that is precise and comprehensible to users. Today UML has established itself as the language of choice for modelling complex enterprises information systems (EIS) using OO techniques. Conversely, the eXtensible Markup Language (XML) is fast emerging as the dominant standard for storing, describing and interchanging data among various enterprises systems and databases. With the introduction of XML Schema, which provides rich facilities for constraining and defining XML content, XML provides the ideal platform and the flexibility for capturing and representing complex enterprise data formats. Yet, UML provides insufficient modelling constructs for utilising XML schema based data description and constraints, while XML Schema lacks the ability to provide higher levels of abstraction (such as conceptual models) that are easily understood by humans. Therefore to enable efficient business application development of large-scale enterprise systems, we need UML like models with rich XML schema like semantics. To address such issue, in this paper, we proposed a generic, semantically rich view mechanism to conceptually model and design (using UML) XML domains to support data modelling of complex domains such as data warehousing and e-commerce systems. Our approach is based on UML and UML stereotypes to design and transform XML views

Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models