Open Science is increasingly viewed as a priority for collaboration and advancement of scientific disciplines. This paper presents two Open Science methods for building performance studies: i) a method for storing building performance information using an open data format, including the creation of a custom XML schema and the novel use of both XML and CSV formats for data storage; and ii) a method for carrying out building performance analysis in an open and reproducible manner using the Jupyter Notebook tool.The work is based on the open-access REFIT Smart Home dataset (publically available at https://doi.org/10.17028/rd.lboro.2070091.v1), a published dataset of building performance information in 20 UK homes. The dataset includes detailed building survey information and over 1.3 billion sensor readings.The paper concludes with a discussion on the future of Open Science approaches for building performance studies, and how the processes described in the paper can be applied to both measurement and simulation datasets.