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When data were generated easily and rapidly with mobile services and computing power can increase on demand with the cloud computation service, data scientists who work with huge data can solve challenging problems. Smart intelligent applications such as Go, healthcare and self-driving vehicles show great improvement recently. In addition to those problems, there are still more complex problem such as weather impacts analysis, financial crisis prediction and crime prevention and so on. To overcome those challenging problems, many crossdisciplinarity or interdisciplinary experts have to collaborate for the solutions. In the paper, we propose a collaboration platform and a system design for data scientists to share data, write analytic scripts and discuss topics related with those problems. In current status, eleven dataset were collect ed such as spam mail, malware data, honeynet log, Hadoop workload log and some other open data and based on those dataset and improvement local cache design (i.e., average response time improvement 92.36% and request availability improvement 70%). With the platform, many education and competition activities can be hold successfully on the collaboration platform. |
