The　deep　coupling　and　favorable　interaction　among　different　energy　flow　networks　such　as　electricity,　natural　gas　and　transportation　has　posed　a　great　challenge　to　the　coordinated　optimization　operation　of　diversified　integrated　energy　system.　In　view　of　the　multiple　uncertainties　in　the　coupled　electricity-gas-transportation　system,　a　data-driven　robust　coordination　optimization　scheduling　model　was　proposed,　which　took　into　account　the　uncertainties　of　traffic　flow,　wind　power　and　gas　consumption　by　gas-fired　units　comprehensively.　Firstly,　the　optimal　flow　distribution　in　transportation　network　was　achieved　by　Wardrop　user　equilibrium　principle,　and　the　uncertainties　from　the　transportation　and　gas　networks　were　transformed　into　the　distribution　network　for　unified　consideration　according　to　the　coupling　constraints　between　networks.　Secondly,　an　ambiguity　set　of　high-dimensional　source　and　load　uncertainties　was　constructed　to　describe　the　probability　distribution　characteristics　based　on　the　historical　data　of　wind　power　and　traffic　flow.　Then,　aiming　at　minimizing　the　day-ahead　operation　cost　in　the　base　prediction　case　and　real-time　adjustment　cost　in　the　worst-case　distribution　of　uncertainties,　a　data-driven　two-stage　robust　economic　dispatch　model　was　established,　which　was　solved　by　column-and-　constraint　generation　method　in　the　master-subproblem　cooperative　solution　framework.　Finally,　the　simulation　results　on　the　test　system　demonstrated　the　effectiveness　of　the　proposed　model　and　solution　approach.　©　2021　Chin.　Soc.　for　Elec.　Eng.