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N4_Data management
This week, there was a detailed discussion on data management. They introduced us to " Data life cycle", which is an interesting thing to learn. Being aware of the life cycle of data, we can better plan how to manage or handle the data for our research purpose. Plan, collect, assure, describe, preserve, discover, integrate and analyze can be the ideal path for a data cycle. They showed us different tips while in any of these stages. There was also discussion on FAIR and CARE principles. Then there was discussion on DMP (data management plan).
This week's discussion made me think about the importance of data management plan before actually collecting data. I always knew there should be an organized and effective way to collect and manage data, however, did not know how and what resources to follow. This week's discussion showed us strong tools and ways to follow an effective data management plan. I am trying to utilize the concepts of last two weeks in my data collection. Initially, I am maintaining a detailed description of the data being collected before the actual laboratory experiments and the outcomes of the tests even if it is not significant, while storing the data following variable standard practices, keeping both the cloud and local backup of data, started utilizing cookie cutter research object package for developing code. It really is helping me to get organized and keep me on track.