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Database-driven information systems provide, by definition, a good level of integration for the various data representations corresponding to heterogeneous information requirements, generated by users with different business perspectives. However, current technologies provide little support for the integration of the system specifications. This paper identifies the key factors which contribute to the semantic integration of the information system metadata, and proposes a possible architecture for an integrated metadata repository.

Model driven engineering approaches can be used to handle the complexity in the development of modern mechatronic systems, containing a multitude of mechanical, electrical/electronic and software components. However, up to now SysML, as standard systems engineering language, is not wide spread in industry yet. Reasons therefore are missing adequate guidelines for the modeling process as well as an unclear benefit of the created SysML-models. A well-created system model however poses enormous time advantages during the analysis of change influences in later lifecycle phases of the system and makes an interdisciplinary reuse of modules in the development of new systems possible. A prerequisite therefore is the efficient traceability of all information within the system model. Thus, in this paper a SysML based process for the high-level development of mechatronic systems is applied, reaching from requirements specification to the detailed modeling of the element-connections (discipline specific as well as interdisciplinary). Our approach shows how the information from the different levels of abstraction and the different development phases can be connected, including a functional modularization of the mechatronic system. In this way, developers can trace change influences more easily. The functional modules can be used during the development of new systems, resulting in significant shortened development cycles. The proposed design pattern is shown at the example of a bench-scale model of a production plant.

New application domains in data-processing environments pose new requirements on the methodologies, techniques and tools used to design them. The applications’ semantics should be fully represented at an increasingly high level, and the representation should be subject to rigorous validation and verification. We present a semantic representation framework (including the language, methods and tools) for design of data-processing applications. The new features of the framework include a small number of precisely defined domain-independent concepts, high-level possibilities for describing behavioural semantics (methods and constraints) and the validation and verification tools included in the framework. We present examples of the use of the framework, including the use of its tools.

The paper deal with a deep analysis and application of object-oriented methodologies for the design process of industrial machine controllers. The process pass thought the phases of (1) conceptual model development of the software artifacts, and (2) model code deployment for the automation system target, which is in general a Programmable Logic Controller (PLC) compliant with the international standard IEC 61131-3 for programming languages. The paper describes a design pattern for the software conceptual model deployment, with a particular emphasis on practical requirements enforced by PLC of different brands. In fact, IEC 61131-3 compliance provides a common “look-and-feel” for programming languages, but does not guarantee straightforward code portability between different PLC vendors. The paper has a great focus on applications and provides an example, based on a generic flow-pack machine, to better explain the proposed methodology.

Case based reasoning (CBR) is a methodology where new problems are solved by investigating, adapting and reusing solutions to a previously solved, similar problem. Hereby knowledge is deduced from the characteristics of a collection of past cases, rather than induced from a set of knowledge rules that are stored in a knowledge base. In this paper we describe how fuzzy CBR techniques can be used to enhance the accessibility of relational databases, more specifically, flexible querying of regular relational databases. Two approaches are discussed: an approach where a database system is extended with a standalone instance- based prediction facility and an approach where such a prediction facility is embedded as an extension of the relational algebra. In both approaches, fuzzy set theory is used for the gradual modelling of similarity. Furthermore, its related possibility theory is used for the modelling of query satisfaction and for the handling of the inevitable uncertainty that occurs when predictions are made.

CNRS 2, FNEGE 1, HCERES A; International audience; Data warehouses are a major component of data-driven decision support systems (DSS). They rely on multidimensional models. The latter provide decision makers with a business-oriented view to data, thereby easing data navigation and analysis via On-Line Analytical Processing (OLAP) tools. They also determine how the data are stored in the data warehouse for subsequent use, not only by OLAP tools, but also by other decision support tools. Data warehouse design is a complex task, which requires a systematic method. Few such methods have been proposed to date. This paper presents a UML-based data warehouse design method that spans the three design phases (conceptual, logical and physical). Our method comprises a set of metamodels used at each phase, as well as a set of transformations that can be semi-automated. Following our object orientation, we represent all the metamodels using UML, and illustrate the formal specification of the transformations based on OMG's Object Constraint Language (OCL). Throughout the paper, we illustrate the application of our method to a case study.

Since XML has become a standard for data exchange over the Internet, especially in B2B and B2C communication, there is an increasing need of integrating XML data into data warehousing systems. In this paper we propose a methodology for data warehouse design, when data sources are XML Schemas and conforming XML documents. Particular relevance is given to the conceptual and logical multidimensional design. A prototype tool has been developed to verify and support our methodology. Because of the semi-structured nature of XML data, not all the information needed for design can be safely derived from XML Schema. In these situations, XQuery statements are generated by the tool to examine XML documents. The functionality of the tool is explained on a real-life XML Schema that describes purchase orders.

Data warehouse is a database that collects and integrates data from heterogeneous sources in order to support a decision making process. Data exchanged over the Internet and intranets has recently become an important data source, having XML as a standard format for exchange. The possibility of integrating available XML data into data warehouses plays an important role in providing enterprise managers with up-to-date and relevant information about their business domain. We have developed a methodology for data warehouse design from the source XML Schemas and conforming XML documents. As XML data is semi-structured, data warehouse design from XML brings many particular challenges. In this paper the final steps of deriving a conceptual multidimensional scheme are described, followed by the logical design, where a set of tables is created according to the derived conceptual scheme. A prototype tool has been developed to test and verify the proposed methodology. Data warehousing system is a set of technologies and tools that enable decision-makers (managers and analysts) to acquire, integrate and flexibly analyze information coming from different sources. The central part of the system is a large database specialized for complex analysis of historical data, called a data warehouse. The process of building a data warehousing system includes analysis of the data sources, design of a warehouse model that can successfully integrate them and later the construction of the warehouse according to the proposed model. Decision-makers use OLAP (OnLine Analytical Processing) tools to put queries against the warehouse in a quick, intuitive and interactive way. OLAP tools use the multidimensional data model, which enables focusing on small pieces of data, generally a few numerical parameters, that are most interesting for the decision making process. Other data in the warehouse are organized hierarchically into several independent groups, called dimensions, and used to perform calculations with the few important parameters. Data warehouses, owned by big enterprises and organizations, integrate data from heterogeneous sources: relational databases or other legacy database models, semi-structured data and different file formats. Recently, the World Wide Web, Web services and different information systems for exchanging data over the Internet and private networks have become an important data source.

ASSO is a formal methodology for conceptual databases design which uses aspects of the B method. In this paper, we discuss the formal relationship between specification in ASSO and in B, defined in terms of a translation which we prove to be sound. Further we go onto discuss refinement in ASSO, which separates behavioural and data refinement, their formal relationship and their relation to refinement in B. In this manner we can use B theory and tools to support database development in ASSO.