XML is the W3C standard document format for writing and exchanging information on the Web. RDF is the W3C standard model for describing the semantics and reasoning about information on the Web. Unfortunately, RDF and XML---although very close to each other---are based on two different paradigms. We argue that in order to lead the Semantic Web to its full potential, the syntax and the semantics of information needs to work together. To this end, we develop a model theory for the XML XQuery 1.0 and XPath 2.0 Data Model, which provides a unified model for both XML and RDF. This unified model can serve as the basis for Web applications that deal with both data and semantics. We illustrate the use of this model on a concrete information integration scenario. Our approach enables each side of the fence to benefit from the other, notably, we show how the RDF world can take advantage of XML query languages, and how the XML world can take advantage of the reasoning capabilities available for RDF.

The design of multi-agent systems is different from similar problems because the concept of agent involves the notions of autonomy and intelligence. As a consequence agentbased software engineering approaches must learn from classical design approaches but should go further introducing an explicit representation of the previous cited notions as well as of ontology, communications, mobility and other agents related issues.

Model transformation (MT) is a key technology in the model-driven development approach of software engineering that provides automated means to capture the evolution of models and mappings between modeling languages. The pattern and rule-based paradigm of graph transformation is considered a very popular approach for specifying such model transformations. While the expressiveness of different MT specification techniques is frequently compared on well-known transformation problems (e.g. UMLto-XMI, or UML-to-EJB mappings), no such benchmarks exist currently for comparing the performance of different model transformation tools. In the paper, we propose a systematic method for quantitative benchmarking in order to assess the performance of graph transformation tools. Typical features of the graph transformation paradigm and various optimization strategies exploited in different tools are identified and categorized. Moreover, the performance of several popular graph transformation tools is measured and compared on a well-known distributed mutual exclusion problem.

XML is the W3C standard document format for writing and exchanging information on the Web. RDF is the W3C standard model for describing the semantics and reasoning about information on the Web. Unfortunately, RDF and XML -- although very close to each other -- are based on two different paradigms. We argue that in order to lead the Semantic Web to its full potential, the syntax and the semantics of information need to work together. To this end, we develop a model theory for the XML XQuery 1.0 and XPath 2.0 Data Model, which provides a unified model for both XML and RDF. This unified model can serve as the basis for Web applications that deal with both data and semantics. We illustrate the use of this model on a concrete information integration scenario. Our approach enables each side of the fence to benefit from the other, notably, we show how the RDF world can take advantage of XML Schema description and XML query languages, and how the XML world can take advantage of the reasoning capabilities available for RDF. Our approach can also serve as a foundation for the next layer of the Semantic Web, the ontology layer, and we present a layering of an ontology language on top of our approach.

This paper presents an overview of a neutral reference architecture and data model for integrating distributed manufacturing simulation systems with each other, with other manufacturing software applications, and with manufacturing data repositories. Other manufacturing software applications include, but are not limited to systems used to: 1) design products, 2) specify processes, 3) engineer manufacturing systems, and 4) manage production. The architecture identifies the software building blocks and interfaces that will facilitate the integration of distributed simulation systems and enable the integration of those systems with other manufacturing software applications. The architecture builds on the High Level Architecture (HLA) standard for simulation (IEEE 2001). NIST and its collaborators have created several implementations of portions of the architecture using commercial off-the-shelf (COTS) simulators. These implementations demonstrated the feasibility of the architecture, and highlighted the need for a neutral data model for exchanging manufacturing data between simulations. Subsequent projects have focused on the development of a neutral information model for integrating machine shop software applications with simulation. The information model provides mechanisms for describing data about organizations, calendars, work, resources, schedules, parts, process plans, and layouts within a machine shop environment. The model has been developed using the Unified Modeling Language (UML) and the Extensible Markup Language (XML). The initial work on the architecture was undertaken as a part of the international Intelligent Manufacturing Systems (IMS) MISSION project. The neutral information model and interface specification activity was initiated under the Technology Insertion

Because of its success, XML is increasingly used in many different application areas, and is moving towards the center of applications, evolving from an exchange format to the native data format of application components. These developments suggest that similar to other core areas of application design, XML should be designed conceptually before the implementation tasks of designing markup and writing schemas are approached. In this paper, we describe why conceptual modeling will become an important part of the XML landscape, what issues need to be addressed, and what the requirements for a conceptual modeling language for XML are.

Despite the extensive and solid research literature on Object-Oriented Design Metrics (OOD Metrics), a recent survey that was conducted to assess the exploitation of metrics collection and analysis in the design phase within the software industry in Sweden [1], indicated that only 21 % of the survey respondents collect metrics in the design phase. 55 % of the respondents to the same survey said that they consider metrics collection as a difficult process. A major reason of the difficulty of collecting design metrics is the lack of a common syntax or a common language to express OOD metrics. This lack resulted in shortage of tools that automate collecting design metrics. Researchers who propose OOD metrics express them in plain English or as mathematical formulas. Plain English allows different interpretations for the same metric. Mathematical formulas should be based on a mathematical model, which does not exist for Object-Oriented designs. In this paper, we propose expressing metrics as XQuery expressions that targets XMI documents. XMI documents offer a standard way for representing object-oriented designs, specifically UML diagrams. Also, we present Design-Metrics Crawler, which is a software tool that applies our proposal.

Today, XML is primarily regarded as a syntax for exchanging structured data, and therefore the question of how to develop well-designed XML models has not been studied extensively. As applications are increasingly penetrated by XML technologies, and because query and programming languages provide native XML support, it would be beneficial to use these features to work with well-designed XML models. In order to better focus on XML-oriented technologies in systems engineering and programming languages, an XML modeling language should be used, which is more focused on modeling and structure than typical XML schema languages. In this paper, we examine the current state of the art in XML schema languages and XML modeling, and present a list of requirements for a XML conceptual modeling language. 1

We describe a simple component architecture for the development of tools for mathematically based semantic transformations of scientific software. This architecture consists of a compiler-based, language-specific front-end for source transformation, loosely coupled with one or more language-independent “plug-in” transformation modules. The coupling mechanism between the front-end and transformation modules is provided by the XML Abstract Interface Form (XAIF). XAIF provides an abstract, language-independent representation of language constructs common in imperative languages, such as C and Fortran. We describe the use of this architecture in the construction of tools for automatic differentiation (AD) of programs written in Fortran 77 and ANSI C. The XAIF is particularly well suited for performing the source transformations needed for AD. Differentiation modules typically operate within the scope of statements or basic blocks, working at a level where procedural languages are very similar. Thus, it is possible to specify a common interface format for mathematically-based semantic transformations that need not represent the union of all languages.

Abstract: XML is an effective universal data-interchange format, and XML Schema has become the preeminent mechanism for describing valid XML document structures. Generalization/specialization and its constraints are fundamental concepts in system modeling and design, but are difficult to express and enforce with XML Schema. This mismatch leads to unnecessary complexity and uncertainty in XML-based models. In this paper we describe how to translate various aspects of generalization/specialization from a conceptual model into XML Schema. We also explore what needs to be added to XML Schema to handle the other aspects of this fundamental modeling construct. If XML Schema were to include our proposed constructs, it would be fully capable of faithfully representing generalization/specialization, thus reducing the complexity of the XML models that rely on generalization/specialization. 1