some international agencies are doing a great job to process and integrate global datasets to make them "interoperable". A good example for soils is ISRIC
See two recent papers for their global efforts on soils.
Hengl, T., J. Mendes de Jesus, B. M. Heuvelink, B. M. Gerard, B. M. G. Heuvelink, M. Ruiperez Gonzalez, M. Kilibarda, A. Blagotic, W. Shangguan, M. N. Wright, X. Geng, B. Bauer-Marschallinger, M. A. Guevara, R. Vargas, R. A. MacMillan, N. H. Batjes, J. G. B. Leenaars, E. Ribeiro, I. Wheeler, S. Mantel, and B. Kempen. 2017. SoilGrids250m: global gridded soil information based on Machine Learning. Plos One 2:e0169748. doi:0169710.0161371/journal. pone.0169748.
Batjes, N. H., E. Ribeiro, A. van Oostrum, J. Leenaars, T. Hengl, and J. M. de Jesus. 2017. WoSIS: providing standardised soil profile data for the world. Earth System Science Data 9:1-14.
Useful tidbit of info from Rodrigo Vargas:
some international agencies are doing a great job to process and integrate global datasets to make them "interoperable". A good example for soils is ISRIC
http://www.isric.org
See two recent papers for their global efforts on soils.
Hengl, T., J. Mendes de Jesus, B. M. Heuvelink, B. M. Gerard, B. M. G. Heuvelink, M. Ruiperez Gonzalez, M. Kilibarda, A. Blagotic, W. Shangguan, M. N. Wright, X. Geng, B. Bauer-Marschallinger, M. A. Guevara, R. Vargas, R. A. MacMillan, N. H. Batjes, J. G. B. Leenaars, E. Ribeiro, I. Wheeler, S. Mantel, and B. Kempen. 2017. SoilGrids250m: global gridded soil information based on Machine Learning. Plos One 2:e0169748. doi:0169710.0161371/journal. pone.0169748.
Batjes, N. H., E. Ribeiro, A. van Oostrum, J. Leenaars, T. Hengl, and J. M. de Jesus. 2017. WoSIS: providing standardised soil profile data for the world. Earth System Science Data 9:1-14.