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Automating the discovery of mappings between structured data sources is a long standing and important problem in data management. We discuss the rich history of the problem and the variety of technical solutions advanced in the database community over the previous four decades. Based on this discussion, we develop a basic statement of the data mapping problem and a general framework for reasoning about the design space of system solutions to the problem. We then concretely illustrate the framework with the Tupelo system for data mapping discovery, focusing on the important common case of relational data sources. Treating mapping discovery as example-driven search in a space of transformations, Tupelo generates queries encompassing the full range of structural and semantic heterogeneities encountered in relational data mapping. Hence, Tupelo is applicable in a wide range of data mapping scenarios. Finally, we present the results of extensive empirical validation, both on synthetic and real world datasets, indicating that the system is both viable and effective.

The Unified Modelling Language (UML) is a well-known family of notations for software modelling. Recently, a new version of UML has been released. In this paper we examine the Activity Diagrams notation of this latest version of UML in terms of a collection of patterns developed for assessing control-flow capabilities of languages used in the area of process-aware information systems. The purpose of this analysis is to assess relative strengths and weaknesses of control-flow specification in Activity Diagrams and to identify ways of addressing potential deficiencies. In addition, the pattern-based analysis will yield typical solutions to practical process modelling problems and expose some of the ambiguities in the current UML 2.0 specification [9].

Workflow systems seek to provide an implementation vehicle for complex, recurring business processes. Notwithstanding this common objective, there are a variety of distinct features offered by commercial workflow management systems. These differences result in significant variations in the ability of distinct tools to represent and implement the plethora of requirements that may arise in contemporary business processes. Many of these requirements recur quite frequently during the requirements analysis activity for workflow systems and abstractions of these requirements serve as a useful means of identifying the key components of workflow languages. Previous work has identified a number of Workflow Control Patterns which characterise the range of control flow constructs that might be encountered when modelling and analysing workflow. In this paper, we describe a series of Workflow Data Patterns that aim to capture the various ways in which data is represented and utilised in workflows. By delineating these Patterns in a form that is independent of specific workflow technologies and modelling languages, we are able to provide a comprehensive treatment of the workflow data perspective and we subsequently use these Patterns as the basis for a detailed comparison of a number of commercially available workflow management systems and business process modelling languages.

Virtual Reality (VR) allows creating interactive three-dimen sional computer worlds in which objects have a sense of spatial and physical presence and can be manipulated by the user as such. Different software tools have been developed to build virtual worlds. However, most tools require considerable background knowledge about VR and the virtual world needs to be expressed in low-level VR primitives. This is one of the reasons why developing a virtual world is complex, time-consuming and expensive. Introducing a conceptual design phase in the development process will reduce the complexity and provides an abstraction layer to hide the VR implementation details. However, virtual worlds contain features not present in classical software. Therefore, new modeling concepts, currently not available in classical conceptual modeling languages, such as ORM or UML, are required. Next to introducing these new modeling concepts, it is also necessary to define their semantics to ensure unambiguousness and to allow code generation. In this paper, we introduce conceptual modeling concepts to specify complex connected 3D objects. Their semantics are defined using F-logic, a full-fledged logic following the object-oriented paradigm. F-logic will allow applying reasoners to check the consistency of the specifications and to investigate properties before the application is actually built.

Since the early software models, abstraction and conceptual semantics have proven their importance in software engineering methodologies. For example, Object-Oriented conceptual modeling offers the power in describing and modeling real-world data semantics and their inter-relationships in a form that is precise and comprehensible to users. Conversely, XML is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems and databases. With the increased reliance on such self-describing, schema-based, semi-structured data language/(s), there exists a requirement to model, design, and manipulate XML data and associated semantics at a higher level of abstraction than at the instance level. But, existing Object-Oriented conceptual modeling languages provide insufficient modeling constructs for utilizing XML schema like data descriptions and constraints, and most semi-structured 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 engineering. In this paper, we use XML view as a case in point and present a three-layered view model with illustrated examples taken from a real-world application domain. We focus on conceptual and schema view definitions, view constraints, and the conceptual query operators.