Conference paper Open Access

A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts

Dirk Burkhardt; Kawa Nazemi; Arjan Kuijper; Egils Ginters


JSON-LD (schema.org) Export

{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design.</p>", 
  "license": "", 
  "creator": [
    {
      "affiliation": "Human-Computer Interaction & Visual Analytics Research Group, Darmstadt University of Applied Sciences", 
      "@id": "https://orcid.org/0000-0002-6507-7899", 
      "@type": "Person", 
      "name": "Dirk Burkhardt"
    }, 
    {
      "affiliation": "Human-Computer Interaction & Visual Analytics Research Group, Darmstadt University of Applied Sciences", 
      "@id": "https://orcid.org/0000-0002-2907-2740", 
      "@type": "Person", 
      "name": "Kawa Nazemi"
    }, 
    {
      "affiliation": "Department of Computer Science, TU Darmstadt, Darmstadt, Germany", 
      "@id": "https://orcid.org/0000-0002-6413-0061", 
      "@type": "Person", 
      "name": "Arjan Kuijper"
    }, 
    {
      "affiliation": "Riga Technical University, Riga, Latvia", 
      "@id": "https://orcid.org/0000-0003-2394-6109", 
      "@type": "Person", 
      "name": "Egils Ginters"
    }
  ], 
  "headline": "A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2019-09-18", 
  "url": "https://zenodo.org/record/3473041", 
  "version": "v1", 
  "@type": "ScholarlyArticle", 
  "keywords": [
    "Mobile Visual Analytics", 
    "Visual Trend Analysis", 
    "Decision Support Systems", 
    "Business Analytics", 
    "Human-Computer Interaction", 
    "Information Visualization", 
    "Mobile Devices"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3473041", 
  "@id": "https://doi.org/10.5281/zenodo.3473041", 
  "workFeatured": {
    "url": "http://www.msc-les.org/conf/vare2019/", 
    "alternateName": "VARE2019", 
    "location": "Lisbon, Portugal", 
    "@type": "Event", 
    "name": "The 5th International Conference of the Virtual and Augmented Reality in Education"
  }, 
  "name": "A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts"
}
140
68
views
downloads
All versions This version
Views 140140
Downloads 6868
Data volume 144.5 MB144.5 MB
Unique views 119119
Unique downloads 5757

Share

Cite as