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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2017
عنوان انگلیسی مقاله:
MERRA Analytic Services: Meeting the Big Data challenges of climate science through cloud-enabled Climate Analytics-as-a-Service
ترجمه فارسی عنوان مقاله:
خدمات تحلیلی MERRA: برآورده کردن چالش های داده های بزرگ علمی آب و هوایی از طریق تجزیه و تحلیل آب و هوا به عنوان یک سرویس یکپارچه شده توسط ابر
منبع:
Sciencedirect - Elsevier - Computers, Environment and Urban Systems 61 (2017) 198–211
نویسنده:
John L. Schnase a,⁎, Daniel Q. Duffy b, Glenn S. Tamkin a, Denis Nadeau a, John H. Thompson b, Cristina M. Grieg c, Mark A. McInerney a, William P. Webster a
چکیده انگلیسی:
Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big
Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We
focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce
societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a
specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and
SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however,
we see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a
service. These elements are essential because in the aggregate they lead to generativity, a capacity for self
assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Ser
vices (MERRA/AS) is an example of cloud-enabled CAaaS built on this principle. MERRA/AS enables MapReduce
analytics over NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection.
The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and
spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing
importance to scientists doing climate change research and a wide range of decision support applications.
MERRA/AS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capa
bilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance
virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRA/AS has
been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to
organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides
the agility required to meet our customers’ increasing and changing needs. Cloud Computing is providing a
new tier in the data services stack that helps connect earthbound, enterprise-level data and computational re
sources to new customers and new mobility-driven applications and modes of work. For climate science,
Cloud Computing’s capacity to engage communities in the construction of new capabilities is perhaps the most
important link between Cloud Computing and Big Data.
Keywords:MapReduce|Hadoop|Data analytics|Data services|Cloud Computing|Generativity|iRODS|MERRA|ESGF|BAER
قیمت: رایگان
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