The eScience Cloud: Observations About Streaming Data Analytics for Science
Most scientific data analysis involves “data at rest”: data that was generated by a physical experiment or simulation and saved in files in some storage system. That data is then analyzed, visualized and summarized by various researchers over a period of time. The sizes of scientific data archives are growing and the number of disciplines creating new ones is expanding. New organizations like the Research Data Alliance have been created to help coordinate the development and sharing of scientific data collections. However not all data is “at rest” in this sense. Sometimes data takes the form of an unbounded stream of information. For example, the continuous stream of live instrument data from on-line sensors or other “internet of things” (IoT) devices. Even computer system logs can produce large continuous streams. Other examples include data from continuously running experiments or automated observatories such as radio telescopes or the output of DNA sequencers.
Read the full article here: https://esciencegroup.com/2016/05/23/observations-about-streaming-data-analytics-for-science/