435 research outputs found

    Extracting Knowledge Bases from table-structured Web resources applied to the semantic-based requirements engineering methodology softwiki

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    Projecte realitzat mitjançant programa de mobilitat. Universität Leipzig. Fakultät für Mathematik und Informatik Institut für Informatik Betriebliche InformationsssystemeOver the last years the use of the Internet by users has evolved drastically from just consulting to publishing, sharing and modifying contents, turning the Internet into a social net in which the possibilities to collaborate and communicate grow every day bigger. A good example are the Wiki systems, which are collaborative, content-focused platforms in which the work of a community is the key to its good performance. Another of the biggest web technology developments of the Internet nowadays is the so-called Semantic Web, a Web in which every piece of data has its context clearly specified and machines are able to understand it. The OntoWiki project merges both Semantic Web and Wiki technology, enabling the definition, modification and visualization of agile, distributed knowledge engineering scenarios. Profiting from the complex extension system of OntoWiki, the SoftWiki platform was born. Thanks to this tool and the associated Agile Requirements Engineering methodology, potentially very large and spatially separate stakeholder groups are able to gather, semantically enrich, classify and aggregate software requirements in an easy manner. Originally created from the desire to import non-semantic requirement data from the Google Code Issues platform to SoftWiki, the CSVLoad extension for OntoWiki enables importing plain data out of CSV table files into OntoWiki with the help of an administrator-defined RDF semantic template, defined with a modified subset of the Turtle (N3) language with support of input and mapping values. The use of CSVLoad and the already defined Google Code Issues Template makes importing the requirements of a project hosted in Google Code into SoftWiki (in other words, into a SWORE ontology) very easy. Some platforms permit exporting only a part (or in some cases none) of their information in standard formats like CSV or RDF. Instead they just show their data in HTML documents, which makes creating general, effective plain-to-semantic importing tools an extremely difficult (and in some cases impossible) task, forcing developers to build custom-made tools. The Gcode extension is a tool specifically built to extract additional requirements information from the Google Code Issues platform HTML code and, together with the CSVLoad tool, it turns importing all the requirements information from Google Code Issues into SoftWiki into an easy, automatic process. By comparing both extensions, their input data and features, the advantages of using structured, view-independent data compared to view-representation-embedded data (e.g. data in a HTML document) become clear. But this data needs a next step, the semantic mark-up, so that computers are able to know the context of the information in an expandable, flexible environment

    DEDUCTIVE EXTENSION OF A RELATIONAL DATABASE SYSTEM

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    Logic based knowledge processing systems such as PROLOG based expert systems have shown obvious drawbacks in performing conventional database tasks. Knowledge processing by deduction on a large set of given facts can be better performed by a deductive database system based on Horn logic and relational database theory. A concept is presented to extend an existing relational database system to make feasible the deduction of intensional data from a given extensional database. The deductive extension provides an extended view mechanism and the integration of integn\u27ly constraints and leads to an enhanced quety mechanism. Thus, the conventional database becomes more expressive, shows a higher degree of consistency, and is evaluated more efficiently

    A metric to represent the evolution of CAD/analysis models in collaborative design

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    Computer Aided Design (CAD) and Computer Aided Engineering (CAE) models are often used during product design. Various interactions between the different models must be managed for the designed system to be robust and in accordance with initially defined specifications. Research published to date has for example considered the link between digital mock-up and analysis models. However design/analysis integration must take into consideration the important number of models (digital mock-up and simulation) due to model evolution in time, as well as considering system engineering. To effectively manage modifications made to the system, the dependencies between the different models must be known and the nature of the modification must be characterised to estimate the impact of the modification throughout the dependent models. We propose a technique to describe the nature of a modification which may be used to determine the consequence within other models as well as a way to qualify the modified information. To achieve this, a metric is proposed that allows the qualification and evaluation of data or information, based on the maturity and validity of information and model
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