With increasingly complex activities, scientific workflows are becoming more data-intensive. In this context, may require a collaborative, distributed or high performance (HPC) environment such as grids or clouds for their execution. Considering its extensibility feature, resources pool and pay-to-use, cloud computing environments have been increasingly adopted. Scientists are formulating their scientific experiments in a collaborative way, provisioning resources (software, hardware) and managing large volumes of data, based on cloud infrastructures. In data-driven collaborative scientific experiments, aspects such interoperability, privacy and trust in shared provenance data should be considered to allow the reproducibility of the results. In this paper, we present the BlockFlow architecture, which aims to bring trust to scientists of a scientific ecosystem platform (E-SECO) in the execution of their collaborative scientific experiments on cloud platforms.