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Beyond the horizon: immersive developments for animal ecology research
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 f...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10281911/ https://www.ncbi.nlm.nih.gov/pubmed/37338732 http://dx.doi.org/10.1186/s42492-023-00138-3 |
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author | Zhang, Ying Klein, Karsten Schreiber, Falk Safi, Kamran |
author_facet | Zhang, Ying Klein, Karsten Schreiber, Falk Safi, Kamran |
author_sort | Zhang, Ying |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10281911 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Nature Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-102819112023-06-22 Beyond the horizon: immersive developments for animal ecology research Zhang, Ying Klein, Karsten Schreiber, Falk Safi, Kamran Vis Comput Ind Biomed Art Perspective 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. Springer Nature Singapore 2023-06-20 /pmc/articles/PMC10281911/ /pubmed/37338732 http://dx.doi.org/10.1186/s42492-023-00138-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Perspective Zhang, Ying Klein, Karsten Schreiber, Falk Safi, Kamran Beyond the horizon: immersive developments for animal ecology research |
title | Beyond the horizon: immersive developments for animal ecology research |
title_full | Beyond the horizon: immersive developments for animal ecology research |
title_fullStr | Beyond the horizon: immersive developments for animal ecology research |
title_full_unstemmed | Beyond the horizon: immersive developments for animal ecology research |
title_short | Beyond the horizon: immersive developments for animal ecology research |
title_sort | beyond the horizon: immersive developments for animal ecology research |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10281911/ https://www.ncbi.nlm.nih.gov/pubmed/37338732 http://dx.doi.org/10.1186/s42492-023-00138-3 |
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