While "big data" in general is characterized by 3 V, i.e., the volume, the velocity and the variety of the target data set and/or data stream, by 4V, adding the veracity of data, or by 5V, adding the value of the analysis result, "big data" in applications, especially in cutting-edge science, symbolizes the paradigm shift from mission-driven research to data-driven research, where the volume may not be the major property of the target data set in the current situation. Recent development of big data core technologies including analysis algorithms and high performance data management and analysis platform technologies, together with the development of automatic measurement instruments and/or large-scale high-performance computer simulation technologies, are currently strongly promoting this paradigm shift to data-driven research in varieties of domain sciences, which is gradually allowing us to conduct scientific research studies completely in cyber worlds after having obtained all the required data sets, or through the real-time receiving of data streams. This trend will further allow us to easily share and exchange not only data sets but also analysis and visualization tools and services, analysis scenarios, and meta knowledge about them, and will definitely lead us to what we call open science.
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