Peculiarity　rules　are　a　new　type　of　useful　knowledge　that　can　be　discovered　by　searching　the　relevance　among　peculiar　data.　A　main　task　in　mining　such　knowledge　is　peculiarity　identification.　Previous　methods　for　finding　peculiar　data　focus　on　attribute　values.　By　extending　to　record-level　peculiarity,　this　paper　investigates　relational　peculiarity-oriented　mining.　Peculiarity　rules　are　mined,　and　more　importantly　explained,　in　a　relational　mining　framework.　Several　experiments　are　carried　out　and　the　results　show　that　relational　peculiarity-oriented　mining　is　effective.