Liping Fu
Research Center of Public Resource of Management, Tianjin University, China
Yifang Liu
College of Management and Economics, Tianjin University, China
Yong Liu
College of Management and Economics, Tianjin University, China
ABSTRACT
The ability to manage big data and turn it into actionable information that can improve the research methodologies of low carbon campus management is a significant success factor in achieving validity and reliability of research. Big data refers not only to data itself but also to the methods employed to mine and analyze large collections of information to solve complex problems. The above mentioned characteristics pose challenges for the low carbon campus management researchers who want to take advantage of big data and employ it to better research method. Traditional methods and data management technologies were not designed to accommodate high volumes of data that are dynamic, furthermore, they were also not designed to collect and provide access to real-time data, as well as managing heterogeneous data from multiple sources that include both structured and unstructured data. Therefore, in order to take advantage of big data, researchers should corporate with technology partners that understand big data, employing interdisciplinary methods to manage, normalize and analyze it. Employing psychological measurement, system dynamics and complex system methods, as well as agent-based simulation platform, the present paper put forward the conceptual protocol for describing the methodologies based on big data, which can be adopted in the research of low carbon campus management and helps to understand the complexity and betters the management of low carbon campus and establishes a solid foundation for further research.
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How to cite this article
Liping Fu, Yifang Liu and Yong Liu, 2013. Study on the Big Data Method for Low Carbon Campus Governance. Journal of Applied Sciences, 13: 4936-4942.
DOI: 10.3923/jas.2013.4936.4942
URL: https://scialert.net/abstract/?doi=jas.2013.4936.4942
DOI: 10.3923/jas.2013.4936.4942
URL: https://scialert.net/abstract/?doi=jas.2013.4936.4942
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