作者: SL LaDeau , BA Han , EJ Rosi-Marshall , KC Weathers , None
DOI: 10.1007/S10021-016-0075-Y
关键词: Scale (chemistry) 、 Ecology 、 Variety (cybernetics) 、 Data type 、 Big data 、 Data stream mining 、 Data science 、 Analytics 、 Exploit 、 Computer science 、 Network science
摘要: Ecosystem scientists will increasingly be called on to inform forecasts and define uncertainty about how changing planet conditions affect human well-being. We should prepared leverage the best tools available, including big data. Use of term ‘big data’ implies an approach that includes capacity aggregate, search, cross-reference, mine large volumes data generate new understanding can decision-making emergent properties complex systems. Although big-data approaches are not a panacea, there large-scale environmental questions for which well suited, even necessary. Ecosystems biophysical systems easily defined by any one type, location, or time. Understanding ecosystem is intensive along axes volume (size data), velocity (frequency variety (diversity types). have employed impressive technology generating high-frequency, large-volume streams. Yet important challenges remain in both theoretical infrastructural development support visualization analysis diverse The way forward greater network science approaches, infrastructure integrated products. Likewise, paradigm cross-disciplinary training professional evaluation needed increase capital fully exploit analytics sustainable adaptable emerging disciplinary needs.