The　systematic　Brain　Informatics　(BI)　study　is　a　data-driven　process　and　all　decision-making　and　suppositions　depend　on　the　deep　understanding　of　brain　data.　Aiming　at　unstructured　brain　data,　semantic　neuroimaging　data　provenances,　called　BI　provenances,　have　been　constructed　to　support　the　quick　and　comprehensive　understanding　about　data　origins　and　data　processing.　However,　the　existing　file-based　or　transaction-database-based　provenance　queries　cannot　effectively　meet　the　requirements　of　understanding　data　and　generating　decision　or　suppositions　in　the　systematic　study,　which　needs　multi-aspect　and　multigranularity　information　of　provenances.　Inspired　by　the　online　analytical　processing　(OLAP)　system,　this　paper　proposes　provenance　cubes　to　support　multi-aspect　and　multi-granularity　provenance　queries.　A　Data-　Brain　based　approach　is　also　designed　to　develop　a　BI　OLAP　system　based　on　provenances　cubes.　The　case　study　demonstrates　significance　and　usefulness　of　the　proposed　approach.　©　Springer-Verlag　Berlin　Heidelberg　2014.