This is a global liquefaction susceptibility map (EPSG:4326) based on the geospatial liquefaction prediction models of Zhu et al.[1] . The coastal model was applied for areas <20km from the coast. The inland model was applied elsewhere. Refer to Zhu et al. [1] in the first instance for further methodology and descriptions. Input data used in part, or their entirety may comprise (amongst others): rivers [2-4] depth to ground water [5] precipitation [6] land [7] Vs30 [8] Cell values are based on Zhu et al. [1] susceptibility classes where: very low, low, moderate, high, very high 0 refers to no data -- typically water bodies. While this data may be useful as preliminary information for regional-scale planning, a PGV intensity term is required for probability maps. Again, see Zhu et al. [1] for a discussion here. An application using this dataset is seen in Koks et al. [9]. [1] Zhu et al. (2017) An updated geospatial liquefaction model for global application. Bull. Seismol. Soc. Am. 107, 1365–1385. [2] Lehner et al. (2006) HydroSHEDS: Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales, Version 1.0. [3] Vogt et al. (2008) CCM River and Catchment Database, version 2.1. [4] Wessel et al. (1992) Digital Chart of the World: Inland Water. [5] Fan et al. (2013) Global patterns of groundwater table depth. Science (80)339, 940–943. [6] Fick et al. (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315. [7] Wessel et al. (2017) LGSHHG: A Global Self-consistent, Hierarchical, High-resolution Geography Database Version 2.3.7. [8] Worden et al. (2017) Development of an Open-Source Hybrid Global Vs30 Model, Seismological Society of America Annual Meeting, 21-23 April, Pasadena, CA. [9] Koks et al. (2019) A global multi-hazard risk analysis of road and railway infrastructure assets Nature Communications 10 (2677)