Microbial Bebop: Creating Music from Complex Dynamics in Microbial Ecology

Microbial Bebop: Creating Music from Complex Dynamics in Microbial Ecology
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DOI:
10.1371/journal.pone.0058119
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发表时间:
2013-03-06
期刊:
影响因子:
3.7
通讯作者:
Gilbert, Jack
Gilbert, Jack
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Larsen, Peter;Gilbert, Jack

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为了让社会就复杂且影响深远的主题做出有效的政策决策,例如适当应对全球气候变化,科学家必须有效地将复杂的结果传达给非科学专业的公众。然而,将高度复杂的科学数据转换为一般社区参与的格式的方法很少。从自然界观察到的模式和爵士乐bebop即兴创作的一些原则中获得灵感,我们产生了微生物Bebop,一种将微生物环境数据转化为音乐的方法。Microbial Bebop使用节拍,音高,持续时间和和声来突出复杂生物数据集中多种数据类型之间的关系。我们使用一个全面的微生物生态学,时间过程数据集收集在L4海洋监测站在西英吉利海峡作为一个例子的微生物生态数据,可以转化为音乐。生成了四种组合物(www.bio.anl.gov/MicrobialBebop.htm.)使用微生物Bebop的L4站数据。每种组合物虽然来自同一数据集,但都是为了突出环境条件和微生物群落结构之间的不同关系而创建的。这里提出的方法可以应用于各种复杂的生物数据集。
In order for society to make effective policy decisions on complex and far-reaching subjects, such as appropriate responses to global climate change, scientists must effectively communicate complex results to the non-scientifically specialized public. However, there are few ways however to transform highly complicated scientific data into formats that are engaging to the general community. Taking inspiration from patterns observed in nature and from some of the principles of jazz bebop improvisation, we have generated Microbial Bebop, a method by which microbial environmental data are transformed into music. Microbial Bebop uses meter, pitch, duration, and harmony to highlight the relationships between multiple data types in complex biological datasets. We use a comprehensive microbial ecology, time course dataset collected at the L4 marine monitoring station in the Western English Channel as an example of microbial ecological data that can be transformed into music. Four compositions were generated (www.bio.anl.gov/MicrobialBebop.htm.) from L4 Station data using Microbial Bebop. Each composition, though deriving from the same dataset, is created to highlight different relationships between environmental conditions and microbial community structure. The approach presented here can be applied to a wide variety of complex biological datasets.