8,419 research outputs found

    Data integration through service-based mediation for web-enabled information systems

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    The Web and its underlying platform technologies have often been used to integrate existing software and information systems. Traditional techniques for data representation and transformations between documents are not sufficient to support a flexible and maintainable data integration solution that meets the requirements of modern complex Web-enabled software and information systems. The difficulty arises from the high degree of complexity of data structures, for example in business and technology applications, and from the constant change of data and its representation. In the Web context, where the Web platform is used to integrate different organisations or software systems, additionally the problem of heterogeneity arises. We introduce a specific data integration solution for Web applications such as Web-enabled information systems. Our contribution is an integration technology framework for Web-enabled information systems comprising, firstly, a data integration technique based on the declarative specification of transformation rules and the construction of connectors that handle the integration and, secondly, a mediator architecture based on information services and the constructed connectors to handle the integration process

    XML Matchers: approaches and challenges

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    Schema Matching, i.e. the process of discovering semantic correspondences between concepts adopted in different data source schemas, has been a key topic in Database and Artificial Intelligence research areas for many years. In the past, it was largely investigated especially for classical database models (e.g., E/R schemas, relational databases, etc.). However, in the latest years, the widespread adoption of XML in the most disparate application fields pushed a growing number of researchers to design XML-specific Schema Matching approaches, called XML Matchers, aiming at finding semantic matchings between concepts defined in DTDs and XSDs. XML Matchers do not just take well-known techniques originally designed for other data models and apply them on DTDs/XSDs, but they exploit specific XML features (e.g., the hierarchical structure of a DTD/XSD) to improve the performance of the Schema Matching process. The design of XML Matchers is currently a well-established research area. The main goal of this paper is to provide a detailed description and classification of XML Matchers. We first describe to what extent the specificities of DTDs/XSDs impact on the Schema Matching task. Then we introduce a template, called XML Matcher Template, that describes the main components of an XML Matcher, their role and behavior. We illustrate how each of these components has been implemented in some popular XML Matchers. We consider our XML Matcher Template as the baseline for objectively comparing approaches that, at first glance, might appear as unrelated. The introduction of this template can be useful in the design of future XML Matchers. Finally, we analyze commercial tools implementing XML Matchers and introduce two challenging issues strictly related to this topic, namely XML source clustering and uncertainty management in XML Matchers.Comment: 34 pages, 8 tables, 7 figure

    Design of the shared Environmental Information System (SEIS) and development of a web-based GIS interface

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    Chapter 5The Shared Environmental Information System (SEIS) is a collaborative initiative of the European Commission (EC) and the European Environment Agency (EEA) aimed to establish an integrated and shared EU-wide environmental information system together with the Member States. SEIS presents the European vision on environmental information interoperability. It is a set of high-level principles & workflow-processes that organize the collection, exchange, and use of environmental data & information aimed to: • Modernise the way in which information required by environmental legislation is made available to member states or EC instruments; • Streamline reporting processes and repeal overlaps or obsolete reporting obligations; • Stimulate similar developments at international conventions; • Standardise according to INSPIRE when possible; and • Introduce the SDI (spatial database infrastructure) principle EU-wide. SEIS is a system and workflow of operations that offers technical capabilities geared to meet concept expectations. In that respect, SEIS shows the way and sets up the workflow effectively in a standardise way (e.g, INSPIRE) to: • Collect Data from Spatial Databases, in situ sensors, statistical databases, earth observation readings (e.g., EOS, GMES), marine observation using standard data transfer protocols (ODBC, SOS, ft p, etc). • Harmonise collected data (including data check/data integrity) according to best practices proven to perform well, according to the INSPIRE Directive 2007/2/EC (1) Annexes I: II: III: plus INSPIRE Implementation Rules for data not specified in above mentioned Annexes. • Harmonise collected data according to WISE (Water Information System from Europe) or Ozone-web. • Process, aggregate harmonise data so to extract information in a format understandable by wider audiences (e.g., Eurostat, enviro-indicators). • Document information to fulfi l national reporting obligations towards EU bodies (e.g., the JRC, EEA, DGENV, Eurostat) • Store and publish information for authorised end-users (e.g., citizens, institutions). This paper presents the development and integration of the SEIS-Malta Geoportal. The first section outlines EU Regulations on INSPIRE and Aarhus Directives. The second covers the architecture and the implementation of SEIS-Malta Geoportal. The third discusses the results and successful implementation of the Geoportal.peer-reviewe

    HUDDL for description and archive of hydrographic binary data

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    Many of the attempts to introduce a universal hydrographic binary data format have failed or have been only partially successful. In essence, this is because such formats either have to simplify the data to such an extent that they only support the lowest common subset of all the formats covered, or they attempt to be a superset of all formats and quickly become cumbersome. Neither choice works well in practice. This paper presents a different approach: a standardized description of (past, present, and future) data formats using the Hydrographic Universal Data Description Language (HUDDL), a descriptive language implemented using the Extensible Markup Language (XML). That is, XML is used to provide a structural and physical description of a data format, rather than the content of a particular file. Done correctly, this opens the possibility of automatically generating both multi-language data parsers and documentation for format specification based on their HUDDL descriptions, as well as providing easy version control of them. This solution also provides a powerful approach for archiving a structural description of data along with the data, so that binary data will be easy to access in the future. Intending to provide a relatively low-effort solution to index the wide range of existing formats, we suggest the creation of a catalogue of format descriptions, each of them capturing the logical and physical specifications for a given data format (with its subsequent upgrades). A C/C++ parser code generator is used as an example prototype of one of the possible advantages of the adoption of such a hydrographic data format catalogue

    HepData and JetWeb: HEP data archiving and model validation

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    The CEDAR collaboration is extending and combining the JetWeb and HepData systems to provide a single service for tuning and validating models of high-energy physics processes. The centrepiece of this activity is the fitting by JetWeb of observables computed from Monte Carlo event generator events against their experimentally determined distributions, as stored in HepData. Caching the results of the JetWeb simulation and comparison stages provides a single cumulative database of event generator tunings, fitted against a wide range of experimental quantities. An important feature of this integration is a family of XML data formats, called HepML.Comment: 4 pages, 0 figures. To be published in proceedings of CHEP0
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