超越地平线:动物生态学研究的沉浸式发展。

4区 计算机科学 Q1 Arts and Humanities
Ying Zhang, Karsten Klein, Falk Schreiber, Kamran Safi
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引用次数: 0

摘要

现在有了更多关于动物生态学的数据。这种“数据洪流”给生物学家和计算机科学家都带来了挑战;然而,它也为改进分析和回答更全面的研究问题创造了机会。我们的目标是提高人们对动物生态学研究人员和计算机科学家之间跨学科研究的当前机会的认识。沉浸式分析(IA)是一个新兴的研究领域,研究如何使用沉浸式技术,如大型显示墙、虚拟现实和增强现实设备,来改善数据分析、结果和沟通。这些调查有可能减少分析工作,并扩大可以解决的问题范围。我们建议生物学家和计算机科学家共同努力,为动物生态学研究中的人工智能奠定基础。我们讨论了潜力和挑战,并概述了通往结构化方法的路径。我们设想,联合的努力将结合两个社区的优势和专业知识,导致定义良好的研究议程和设计空间、实用指南、健壮和可重用的软件框架、减少分析工作,以及更好的结果可比性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Beyond the horizon: immersive developments for animal ecology research.

Beyond the horizon: immersive developments for animal ecology research.

Beyond the horizon: immersive developments for animal ecology research.

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 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.

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来源期刊
Visual Computing for Industry, Biomedicine, and Art
Visual Computing for Industry, Biomedicine, and Art Arts and Humanities-Visual Arts and Performing Arts
CiteScore
5.60
自引率
0.00%
发文量
28
审稿时长
5 weeks
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