Browsing by Author "Lenti, Simone"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    CrossWidget: a D3.js Plugin to Support Multiple Scented Cross Filtering Activities
    (The Eurographics Association, 2019) Blasilli, Graziano; Lenti, Simone; Palleschi, Alessia; Madeiras Pereira, João and Raidou, Renata Georgia
    Filtering is one of the basic interaction techniques in information visualization. To better support a filtering activity, the visualization should be enriched by selectors composed of different visual elements and data distribution (i.e., scented widgets), in order to improve the navigation of information spaces and the comprehension of the filtering result. Thus, we propose CrossWidget, an open source JavaScript D3.js plugin, aimed at supporting cross filtering activities. To better perform multiple selections, to understand their result, and to better investigate the relationships among attributes of the dataset, this plugin proposes a set of ''multiple scented widgets'' that can be easily customized and integrated into Web visualization systems.
  • Thumbnail Image
    Item
    EuroVis 2022 Posters: Frontmatter
    (The Eurographics Association, 2022) Krone, Michael; Lenti, Simone; Schmidt, Johanna; Krone, Michael; Lenti, Simone; Schmidt, Johanna
  • Thumbnail Image
    Item
    Lessons learned while supporting Cyber Situational Awareness
    (The Eurographics Association, 2021) Blasilli, Graziano; Paoli, Emiliano De; Lenti, Simone; Picca, Sergio; Vrotsou, Katerina and Bernard, Jürgen
    The increasing number of cyberattacks against critical infrastructures has pushed researchers to develop many Visual Analytics solutions to provide valid defensive approaches and improve the situational awareness of the security operators. Applying such solutions to complex infrastructures is often challenging, and existing tools can present limitations and exhibit various issues. In this paper, supported by cybersecurity experts of a world leader company in the military domain, we apply an existing Visual Analytics solution, MAD, to a complex network of a critical infrastructure, highlighting its limitations in this scenario and proposing further solutions to improve the cyber situational awareness in both proactive and reactive risk analyses. The results of this research contribute to characterize the activities performed by domain experts in this domain and their implications for the design of Visual Analytics solutions that aim at supporting them.