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

Ontology-based patterns for the integration of business processes and enterprise application architectures

Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data. Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their applicability in business process-driven application integration is demonstrated

Querying Large Physics Data Sets Over an Information Grid

Optimising use of the Web (WWW) for LHC data analysis is a complex problem and illustrates the challenges arising from the integration of and computation across massive amounts of information distributed worldwide. Finding the right piece of information can, at times, be extremely time-consuming, if not impossible. So-called Grids have been proposed to facilitate LHC computing and many groups have embarked on studies of data replication, data migration and networking philosophies. Other aspects such as the role of 'middleware' for Grids are emerging as requiring research. This paper positions the need for appropriate middleware that enables users to resolve physics queries across massive data sets. It identifies the role of meta-data for query resolution and the importance of Information Grids for high-energy physics analysis rather than just Computational or Data Grids. This paper identifies software that is being implemented at CERN to enable the querying of very large collaborating HEP data-sets, initially being employed for the construction of CMS detectors.Comment: 4 pages, 3 figure

A Comparison of Big Data Frameworks on a Layered Dataflow Model

In the world of Big Data analytics, there is a series of tools aiming at simplifying programming applications to be executed on clusters. Although each tool claims to provide better programming, data and execution models, for which only informal (and often confusing) semantics is generally provided, all share a common underlying model, namely, the Dataflow model. The Dataflow model we propose shows how various tools share the same expressiveness at different levels of abstraction. The contribution of this work is twofold: first, we show that the proposed model is (at least) as general as existing batch and streaming frameworks (e.g., Spark, Flink, Storm), thus making it easier to understand high-level data-processing applications written in such frameworks. Second, we provide a layered model that can represent tools and applications following the Dataflow paradigm and we show how the analyzed tools fit in each level.Comment: 19 pages, 6 figures, 2 tables, In Proc. of the 9th Intl Symposium on High-Level Parallel Programming and Applications (HLPP), July 4-5 2016, Muenster, German

Knowledge management, innovation and big data: Implications for sustainability, policy making and competitiveness

This Special Issue of Sustainability devoted to the topic of “Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness” attracted exponential attention of scholars, practitioners, and policy-makers from all over the world. Locating themselves at the expanding cross-section of the uses of sophisticated information and communication technology (ICT) and insights from social science and engineering, all papers included in this Special Issue contribute to the opening of new avenues of research in the field of innovation, knowledge management, and big data. By triggering a lively debate on diverse challenges that companies are exposed to today, this Special Issue offers an in-depth, informative, well-structured, comparative insight into the most salient developments shaping the corresponding fields of research and policymaking

A Service Component-based Accounting and Charging Architecture to Support Interim Mechanisms across Multiple Domains

Today, telematics services are often compositions of different chargeable service components offered by different service providers. To enhance component-based accounting and charging, the service composition information is used to match with the corresponding charging structure of a service session. This enables the sharing of revenues among the service providers, and calculation of the total cost for the end-user. When multiple independent service providers are involved, it is a great challenge to apply interim accounting and charging during a service session in order to minimize financial risks between business partners. Another interesting development is the trend towards outsourcing accounting and charging processes to specialized business partners. This requires a decoupling between provisioning and accounting and charging processes. In this paper, we propose a comprehensive component-based accounting and charging architecture to support service session provisioning across multiple domains. The architecture, modeled in UML, incorporates an interim accounting and charging mechanism to enable the processing and exchange of accounting information needed to update intermediate charges for separate service components and the user's credit, even during the service provisioning phase

Semantic model-driven development of service-centric software architectures

Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context

Aspect-oriented interaction in multi-organisational web-based systems

Separation of concerns has been presented as a promising tool to tackle the design of complex systems in which cross-cutting properties that do not fit into the scope of a class must be satisfied. Unfortunately, current proposals assume that objects interact by means of object-oriented method calls, which implies that they embed interactions with others into their functional code. This makes them dependent on this interaction model, and makes it difficult to reuse them in a context in which another interaction model is more suited, e.g., tuple spaces, multiparty meetings, ports, and so forth. In this paper, we show that functionality can be described separately from the interaction model used, which helps enhance reusability of functional code and coordination patterns. Our proposal is innovative in that it is the first that achieves a clear separation between functionality and interaction in an aspect-oriented manner. In order to show that it is feasible, we adapted the multiparty interaction model to the context of multiorganisational web-based systems and developed a class framework to build business objects whose performance rates comparably to handmade implementations; the development time, however, decreases significantly.Comisión Interministerial de Ciencia y Tecnología TIC2000-1106-C02-0