Data quality is crucial for the data-driven method of life cycle assessment (LCA) to achieve reliable results. Existing data quality indicators are hard to apply to the unique methodology used in building LCA. Here, data origin has a paramount effect on the reliability of the results. However, the extensive amount of data used from a broad range of sources makes the origin hard to trace and, thus, makes it difficult to assess the aforementioned reliability. This paper presents a new method of visualizing the data sources using an UpSet graph, aiming for an overview of their impact on building LCA results. Furthermore, the new method is applied to a use case as a proof of concept.