5,971 research outputs found

    A method for mapping XML-based specifications between development methodologies

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    The Unified Modeling Language (UML) is widely used by software engineers as the basis of analysis and design in software development. However, UML ignores human factors in the course of software development because of its strong emphasis on the internal structure and functionality of the application. This thesis presents a method of mapping human-computer interaction (HCI) requirement specifications generated by usability engineering (UE) methodologies (e.g. Putting Usability First (PUF)) into UML specifications. These two sets of requirement specification are specified, using Extensible Markup Language (XML) so that HCI requirement specifications can be integrated into UML ones. A Mapping Tool was developed to facilitate the creation of mappings between PUF XML tags and XMI tags. The Mapping Tool was used to create mappings between PUF and UML requirement specifications. This mapping process and its outputs were evaluated to demonstrate that the tool worked. The results of the evaluation show that the HCI requirement specification represented by the PUF XML tags can improve the UML specification by adding them into the XMI tags

    Generating collaborative systems for digital libraries: A model-driven approach

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    This is an open access article shared under a Creative Commons Attribution 3.0 Licence (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2010 The Authors.The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework

    Automated UML-based ontology generation in OSLOÂČ

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    In 2015, Flanders Information started the OSLO2 project, aimed at easing the exchange of data and increasing the interoperability of Belgian government services. RDF ontologies were developed to break apart the government data silos and stimulate data reuse. However, ontology design still encounters a number of difficulties. Since domain experts are generally unfamiliar with RDF, a design process is needed that allows these experts to efficiently contribute to intermediate ontology prototypes. We designed the OSLO2 ontologies using UML, a modeling language well known within the government, as a single source specification. From this source, the ontology and other relevant documents are generated. This paper describes the conversion tooling and the pragmatic approaches that were taken into account in its design. While this tooling is somewhat focused on the design principles used in the OSLO2 project, it can serve as the basis for a generic conversion tool. All source code and documentation are available online

    Design and evaluation of the FAMILIAR tool

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    2014 Spring.Includes bibliographical references.Software Product Line Engineering (SPLE) aims to efficiently produce multiple software products, on a large scale, that share a common set of core development features. Feature Modeling is a popular SPLE technique used to describe variability in a product family. FAMILIAR (FeAture Model scrIpt Language for manipulation and Automatic Reasoning) is a Domain-Specific Modeling Language (DSML) for manipulating Feature Models (FMs). One of the strengths of the FAMILIAR language is that it provides rich semantics for FM composition operators (aggregate, merge, insert) as well as decomposition operators (slice). The main contribution of this thesis is to provide an integrated graphical modeling environment that significantly improves upon the initial FAMILIAR framework that was text-based and consisted of loosely coupled parts. As part of this thesis we designed and implemented a new FAMILIAR Tool that provides (1) a fast rendering framework for the graphically representing feature models, (2) a configuration editor and (3) persistence of feature models. Furthermore, we evaluated the usability of our new FAMILIAR Tool by performing a small experiment primarily focusing on assessing quality aspects of newly authored FMs as well as user effectiveness and efficiency

    Specification and implementation of mapping rule visualization and editing : MapVOWL and the RMLEditor

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    Visual tools are implemented to help users in defining how to generate Linked Data from raw data. This is possible thanks to mapping languages which enable detaching mapping rules from the implementation that executes them. However, no thorough research has been conducted so far on how to visualize such mapping rules, especially if they become large and require considering multiple heterogeneous raw data sources and transformed data values. In the past, we proposed the RMLEditor, a visual graph-based user interface, which allows users to easily create mapping rules for generating Linked Data from raw data. In this paper, we build on top of our existing work: we (i) specify a visual notation for graph visualizations used to represent mapping rules, (ii) introduce an approach for manipulating rules when large visualizations emerge, and (iii) propose an approach to uniformly visualize data fraction of raw data sources combined with an interactive interface for uniform data fraction transformations. We perform two additional comparative user studies. The first one compares the use of the visual notation to present mapping rules to the use of a mapping language directly, which reveals that the visual notation is preferred. The second one compares the use of the graph-based RMLEditor for creating mapping rules to the form-based RMLx Visual Editor, which reveals that graph-based visualizations are preferred to create mapping rules through the use of our proposed visual notation and uniform representation of heterogeneous data sources and data values. (C) 2018 Elsevier B.V. All rights reserved

    End-User Programming of Mobile Services: Empowering Domain Experts to Implement Mobile Data Collection Applications

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    The widespread use of smart mobile devices (e.g., in clinical trials or online surveys) offers promising perspectives with respect to the controlled collection of high-quality data. The design, implementation and deployment of such mobile data collection applications, however, is challenging in several respects. First, various mobile operating systems need to be supported, taking the short release cycles of vendors into account as well. Second, domain-specific requirements need to be flexibly aligned with mobile application development. Third, usability styleguides need to be obeyed. Altogether, this turns both programming and maintaining mobile applications into a costly, time-consuming, and error-prone endeavor. To remedy these drawbacks, a model-driven framework empowering domain experts to implement robust mobile data collection applications in an intuitive way was realized. The design of this end-user programming framework is based on experiences gathered in real-life mobile data collection projects. Facets of various stakeholders involved in such projects are discussed and an overall architecture as well as its components are presented. In particular, it is shown how the framework enables domain experts (i.e., end users) to flexibly implement mobile data collection applications on their own. Overall, the framework allows for the effective support of mobile services in a multitude of application domains
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