24 research outputs found

    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

    IMMACCS: A Multi-Agent Decision-Support System

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    This report describes work performed by the Collaborative Agent Design Research Center for the US Marine Corps Warfighting Laboratory (MCWL), on the IMMACCS experimental decision-support system. IMMACCS (Integrated Marine Multi-Agent Command and Control System) incorporates three fundamental concepts that distinguish it from existing (i.e., legacy) command and control applications. First, it is a collaborative system in which computer-based agents assist human operators by monitoring, analyzing, and reasoning about events in near real-time. Second, IMMACCS includes an ontological model of the battlespace that represents the behavioral characteristics and relationships among real world entities such as friendly and enemy assets, infrastructure objects (e.g., buildings, roads, and rivers), and abstract notions. This object model provides the essential common language that binds all IMMACCS components into an integrated and adaptive decision-support system. Third, IMMACCS provides no ready made solutions that may not be applicable to the problems that will occur in the real world. Instead, the agents represent a powerful set of tools that together with the human operators can adjust themselves to the problem situations that cannot be predicted in advance. In this respect, IMMACCS is an adaptive command and control system that supports planning, execution and training functions concurrently. The report describes the nature and functional requirements of military command and control, the architectural features of IMMACCS that are designed to support these operational requirements, the capabilities of the tools (i.e., agents) that IMMACCS offers its users, and the manner in which these tools can be applied. Finally, the performance of IMMACCS during the Urban Warrior Advanced Warfighting Experiment held in California in March, 1999, is discussed from an operational viewpoint

    IDEAS-1997-2021-Final-Programs

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    This document records the final program for each of the 26 meetings of the International Database and Engineering Application Symposium from 1997 through 2021. These meetings were organized in various locations on three continents. Most of the papers published during these years are in the digital libraries of IEEE(1997-2007) or ACM(2008-2021)

    An Adaptive Integration Architecture for Software Reuse

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    The problem of building large, reliable software systems in a controlled, cost-effective way, the so-called software crisis problem, is one of computer science\u27s great challenges. From the very outset of computing as science, software reuse has been touted as a means to overcome the software crisis issue. Over three decades later, the software community is still grappling with the problem of building large reliable software systems in a controlled, cost effective way; the software crisis problem is alive and well. Today, many computer scientists still regard software reuse as a very powerful vehicle to improve the practice of software engineering. The advantage of amortizing software development cost through reuse continues to be a major objective in the art of building software, even though the tools, methods, languages, and overall understanding of software engineering have changed significantly over the years. Our work is primarily focused on the development of an Adaptive Application Integration Architecture Framework. Without good integration tools and techniques, reuse is difficult and will probably not happen to any significant degree. In the development of the adaptive integration architecture framework, the primary enabling concept is object-oriented design supported by the unified modeling language. The concepts of software architecture, design patterns, and abstract data views are used in a structured and disciplined manner to established a generic framework. This framework is applied to solve the Enterprise Application Integration (EM) problem in the telecommunications operations support system (OSS) enterprise marketplace. The proposed adaptive application integration architecture framework facilitates application reusability and flexible business process re-engineering. The architecture addresses the need for modern businesses to continuously redefine themselves to address changing market conditions in an increasingly competitive environment. We have developed a number of Enterprise Application Integration design patterns to enable the implementation of an EAI framework in a definite and repeatable manner. The design patterns allow for integration of commercial off-the-shelf applications into a unified enterprise framework facilitating true application portfolio interoperability. The notion of treating application services as infrastructure services and using business processes to combine them arbitrarily provides a natural way of thinking about adaptable and reusable software systems. We present a mathematical formalism for the specification of design patterns. This specification constitutes an extension of the basic concepts from many-sorted algebra. In particular, the notion of signature is extended to that of a vector, consisting of a set of linearly independent signatures. The approach can be used to reason about various properties including efforts for component reuse and to facilitate complex largescale software development by providing the developer with design alternatives and support for automatic program verification

    A cooperative framework for molecular biology database integration using image object selection.

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    The theme and the concept of 'Molecular Biology Database Integration’ and the problems associated with this concept initiated the idea for this Ph.D research. The available technologies facilitate to analyse the data independently and discretely but it fails to integrate the data resources for more meaningful information. This along with the integration issues created the scope for this Ph.D research. The research has reviewed the 'database interoperability' problems and it has suggested a framework for integrating the molecular biology databases. The framework has proposed to develop a cooperative environment to share information on the basis of common purpose for the molecular biology databases. The research has also reviewed other implementation and interoperability issues for laboratory based, dedicated and target specific database. The research has addressed the following issues: - diversity of molecular biology databases schemas, schema constructs and schema implementation -multi-database query using image object keying -database integration technologies using context graph - automated navigation among these databases This thesis has introduced a new approach for database implementation. It has introduced an interoperable component database concept to initiate multidatabase query on gene mutation data. A number of data models have been proposed for gene mutation data which is the basis for integrating the target specific component database to be integrated with the federated information system. The proposed data models are: data models for genetic trait analysis, classification of gene mutation data, pathological lesion data and laboratory data. The main feature of this component database is non-overlapping attributes and it will follow non-redundant integration approach as explained in the thesis. This will be achieved by storing attributes which will not have the union or intersection of any attributes that exist in public domain molecular biology databases. Unlike data warehousing technique, this feature is quite unique and novel. The component database will be integrated with other biological data sources for sharing information in a cooperative environment. This/involves developing new tools. The thesis explains the role of these new tools which are: meta data extractor, mapping linker, query generator and result interpreter. These tools are used for a transparent integration without creating any global schema of the participating databases. The thesis has also established the concept of image object keying for multidatabase query and it has proposed a relevant algorithm for matching protein spot in gel electrophoresis image. An object spot in gel electrophoresis image will initiate the query when it is selected by the user. It matches the selected spot with other similar spots in other resource databases. This image object keying method is an alternative to conventional multidatabase query which requires writing complex SQL scripts. This method also resolve the semantic conflicts that exist among molecular biology databases. The research has proposed a new framework based on the context of the web data for interactions with different biological data resources. A formal description of the resource context is described in the thesis. The implementation of the context into Resource Document Framework (RDF) will be able to increase the interoperability by providing the description of the resources and the navigation plan for accessing the web based databases. A higher level construct is developed (has, provide and access) to implement the context into RDF for web interactions. The interactions within the resources are achieved by utilising an integration domain to extract the required information with a single instance and without writing any query scripts. The integration domain allows to navigate and to execute the query plan within the resource databases. An extractor module collects elements from different target webs and unify them as a whole object in a single page. The proposed framework is tested to find specific information e.g., information on Alzheimer's disease, from public domain biology resources, such as, Protein Data Bank, Genome Data Bank, Online Mendalian Inheritance in Man and local database. Finally, the thesis proposes further propositions and plans for future work

    A cooperative framework for molecular biology database integration using image object selection

    Get PDF
    The theme and the concept of 'Molecular Biology Database Integration' and the problems associated with this concept initiated the idea for this Ph.D research. The available technologies facilitate to analyse the data independently and discretely but it fails to integrate the data resources for more meaningful information. This along with the integration issues created the scope for this Ph.D research. The research has reviewed the 'database interoperability' problems and it has suggested a framework for integrating the molecular biology databases. The framework has proposed to develop a cooperative environment to share information on the basis of common purpose for the molecular biology databases. The research has also reviewed other implementation and interoperability issues for laboratory based, dedicated and target specific database. The research has addressed the following issues: diversity of molecular biology databases schemas, schema constructs and schema implementation multi-database query using image object keying, database integration technologies using context graph, automated navigation among these databases. This thesis has introduced a new approach for database implementation. It has introduced an interoperable component database concept to initiate multidatabase query on gene mutation data. A number of data models have been proposed for gene mutation data which is the basis for integrating the target specific component database to be integrated with the federated information system. The proposed data models are: data models for genetic trait analysis, classification of gene mutation data, pathological lesion data and laboratory data. The main feature of this component database is non-overlapping attributes and it will follow non-redundant integration approach as explained in the thesis. This will be achieved by storing attributes which will not have the union or intersection of any attributes that exist in public domain molecular biology databases. Unlike data warehousing technique, this feature is quite unique and novel. The component database will be integrated with other biological data sources for sharing information in a cooperative environment. This involves developing new tools. The thesis explains the role of these new tools which are: meta data extractor, mapping linker, query generator and result interpreter. These tools are used for a transparent integration without creating any global schema of the participating databases. The thesis has also established the concept of image object keying for multidatabase query and it has proposed a relevant algorithm for matching protein spot in gel electrophoresis image. An object spot in gel electrophoresis image will initiate the query when it is selected by the user. It matches the selected spot with other similar spots in other resource databases. This image object keying method is an alternative to conventional multidatabase query which requires writing complex SQL scripts. This method also resolve the semantic conflicts that exist among molecular biology databases. The research has proposed a new framework based on the context of the web data for interactions with different biological data resources. A formal description of the resource context is described in the thesis. The implementation of the context into Resource Document Framework (RDF) will be able to increase the interoperability by providing the description of the resources and the navigation plan for accessing the web based databases. A higher level construct is developed (has, provide and access) to implement the context into RDF for web interactions. The interactions within the resources are achieved by utilising an integration domain to extract the required information with a single instance and without writing any query scripts. The integration domain allows to navigate and to execute the query plan within the resource databases. An extractor module collects elements from different target webs and unify them as a whole object in a single page. The proposed framework is tested to find specific information e.g., information on Alzheimer's disease, from public domain biology resources, such as, Protein Data Bank, Genome Data Bank, Online Mendalian Inheritance in Man and local database. Finally, the thesis proposes further propositions and plans for future work

    Where have all the flowers gone?: a modular systems perspective of IT infrastructure design and productivity

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    Assessing value of IT infrastructure investments has been both difficult and ambiguous. This research develops and tests a conceptual framework to understand the productivity process. A lagged and recursive framework is used to trace the relationship between IT infrastructure investments, infrastructure design, and organizational productivity along with contingencies of IT management and the environment. A major contribution of this study is the use of the systems perspective to disaggregate the concepts of IT infrastructure and productivity into collectively exhaustive types. Findings reveal that IT investments do not significant affect productivity but do so when used to develop an IT infrastructure design. IT management is seen to strongly influence IT infrastructure design. Similarly, organizational environment appears to significantly influence the type of productivity focus for a firm. The study adds to the existing body of knowledge through a holistic investigation of the multi-level relationship between IT infrastructure configurations, contingencies, and productivity

    Spatial ontologies for architectural heritage

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    Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications
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