Marine data users clustering using data mining technique

The objective of this research is marine data users clustering using data mining technique. To achieve this objective، marine organizations will enable to know their data and users requirements. In this research، CRISP-DM standard model was used to implement the data mining technique. The required data was extracted from 500 marine data users profile database of Iranian National Institute for Oceanography and Atmospheric Sciences (INIOAS) from 1386 to 1393. The TwoStep algorithm was used for clustering. In this research، patterns was discovered between marine data users such as student، organization and scientist and their data request (Data source، Data type، Data set، Parameter and Geographic area) using clustering for the first time. The most important clusters are: Student with International data source، Chemistry data type، “World Ocean Database” dataset، Persian Gulf geographic area and Organization with Nitrate parameter. Senior managers of the marine organizations will enable to make correct decisions concerning their existing data. They will direct to planning for better data collection in the future. Also data users will guide with respect to their requests. Finally، the valuable suggestions were offered to improve the performance of marine organizations.