Building Open Environments to Meet Big Data Challenges in Earth Sciences

Abstract

Big Data, a popular term emerged with the trend to larger datasets, refers to a collection of datasets so large or complex that it becomes difficult to process using regular database management tools or traditional data processing applications (IDC, 2011; White, 2012; MIKE 2.0). Big Data is posing big challenges and opportunities for every field of the human societies as the Big Data era has arrived with the exponential growth, availability, and use of data and information (The Economist, 2010; Reichman, 2011). Big Data does not have to be necessarily big in data size. Big Data issues can be raised either as data volume gets so large and varied (big size of data), or datasets come in all types of formats and from many different sources (high-degree complexity of data), or data are produced and must be processed fast (e.g., near real-time data producing and processing) to meet the demand of information (high velocity of data). The recent discussions on Big Data and how to utilize it as the basis for innovation, differentiation, and growth reflect a wide recognition of Big Data opportunities and challenges.