Logo des Repositoriums

Auflistung nach Autor:in "Thiele, Michael"

1 - 2 von 2
  • Konferenzbeitrag
    SaferWeb - Community-Driven Collection Of Suitable Websites For Children
    (SIGSAND-EUROPE 2008: Proceedings of the Third AIS SIGSAND European Symposium on Analysis, Design, Use and Societal Impact of Information Systems, 2008) Richly, Sebastian; Goethlich, Anne; Mauermeister, Ines; Thiele, Michael
    Regardless of what you might think about the Internet and its communities, it is an undeniable fact that their importance and the number of users have grown significantly over the last years. They have also come to manage rather complex tasks, as illustrated by tagging communities and similar applications. In our SaferWeb approach, we use a community platform to collect suitable websites for children. Current webfilters for children use blacklist or whitelist approaches. However, blacklists only block already known websites and thus, finding and adding new sites is a time-consuming manual effort. Similarly, whitelists only allow known websites suitable for children, and again, the effort required to find and manage adequate sites is immense as well. SaferWeb uses a community to manage a whitelist and thus distributes the effort to many shoulders. In this paper, we present our SaferWeb community and its whole architecture also containing a proxy and a browser toolbar.
  • Konferenzbeitrag
    A scalable approach to annotate arbitrary modelling languages
    (Modellierung 2010, 2010) Fritzsche, Mathias; Gilani, Wasif; Thiele, Michael; Spence, Ivor; Brown, T. John; Kilpatrick, Peter
    Refinement via annotations is a common practice in Model-Driven Engineering (MDE). For instance, in the case of our Model-Driven Performance Engineering (MDPE) architecture, we are required to annotate different types of process models with performance objectives, constraints and other information. This is used to enable domain experts, such as business analysts, to benefit from an automated performance prediction based decision support. Currently, the process models are annotated manually, element by element. This approach is not scalable, for instance, in the case where numerous model elements in large model repositories need to be annotated with the same information. Thus, a scalable annotation mechanism is needed which can be used for arbitrary modelling languages. In this paper we propose an architecture which uses a specialized modelling language to express annotations in an efficient way. This language is transformed to model transformation scripts in order to generate annotation models, which separate the annotated information from the target models and, therefore, supports scalable model annotations for modelling languages of choice.