The digital twin of the rail system plays a pivotal role in advancing infrastructure management, ushering in greater punctuality and safety for trains. By harnessing data from diverse sources, it facilitates real-time updates throughout the lifecycle of railway assets. This comprehensive digital twin encompasses every aspect of infrastructure management, offering multifaceted functionalities beyond mere asset oversight. These include providing insights into the current state of the rail system and furnishing simulation tools to bolster decision-making processes across all stakeholders. Given the fundamental reliance on digital data within this framework, our primary focus is on ensuring its usability and quality. Accurate analysis of asset conditions hinges upon the trustworthiness of the data, a requirement shared by maintainers and operators alike. Consequently, we’ve diligently crafted a set of digital data confidence indicators aimed at instilling trust in the information at hand. In tandem with the endeavors to develop a digital twin for the rail system, there arises a pressing need to establish digital solutions that capitalize on data pertinent to business objectives. This necessity is underscored by the efforts of SNCF’s network description department in modeling both processes and data. However, the efficacy of these digital solutions is contingent upon the relevance, efficiency, and high quality of the data they rely on. To this end, we’ve embedded the notion of trust within the digital data used to delineate the condition of railway assets. While these indicators amalgamate various factors impacting user confidence in digital data, further expansion is warranted to ensure the widespread effectiveness and adoption of digital tools by end-users.