Materials science has heralded its new paradigm in data-driven science following the generation of Big Data from high-performance computing and high-throughput experimentations. Such Big Data need to be standardized, curated, preserved, and disseminated in a way that is Findable, Accessible, Interoperable, and Reusable (FAIR) to make use of its full potential. The materials science community is in its premature stage concerning adapting research data management (RDM) practices. In this work, we provide detailed recommendations to be followed within the data-driven research life cycle, which aims to promote RDM within the community. More interoperable materials databases and standards need to be developed and adopted within the community to get the maximum benefit from this initiative. The nature of heterogeneous data in materials science makes this a huge challenge. However, if we all as a community work together to make our data FAIR, materials discovery could indeed be accelerated.