• Medientyp: Sonstige Veröffentlichung; E-Artikel
  • Titel: Beyond the horizon: immersive developments for animal ecology research
  • Beteiligte: Zhang, Ying [VerfasserIn]; Klein, Karsten [VerfasserIn]; Schreiber, Falk [VerfasserIn]; Safi, Kamran [VerfasserIn]
  • Erschienen: KOPS - The Institutional Repository of the University of Konstanz, 2023-06-20
  • Erschienen in: Visual Computing for Industry, Biomedicine, and Art. Springer Science and Business Media LLC. 2023, 6(1), 11. eISSN 2524-4442. Available under: doi:10.1186/s42492-023-00138-3
  • Sprache: Englisch
  • DOI: https://doi.org/10.1186/s42492-023-00138-3
  • Schlagwörter: Interactive data visualization ; Immersive analytics ; Animal ecology ; Collaboration
  • Entstehung:
  • Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Beschreibung: More diverse data on animal ecology are now available. This “data deluge” presents challenges for both biologists and computer scientists; however, it also creates opportunities to improve analysis and answer more holistic research questions. We aim to increase awareness of the current opportunity for interdisciplinary research between animal ecology researchers and computer scientists. Immersive analytics (IA) is an emerging research field in which investigations are performed into how immersive technologies, such as large display walls and virtual reality and augmented reality devices, can be used to improve data analysis, outcomes, and communication. These investigations have the potential to reduce the analysis effort and widen the range of questions that can be addressed. We propose that biologists and computer scientists combine their efforts to lay the foundation for IA in animal ecology research. We discuss the potential and the challenges and outline a path toward a structured approach. We imagine that a joint effort would combine the strengths and expertise of both communities, leading to a well-defined research agenda and design space, practical guidelines, robust and reusable software frameworks, reduced analysis effort, and better comparability of results. ; published
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Namensnennung (CC BY)