Nitrification plays an important role in global nitrogen recycling and exists ubiquitously on earth. Nitrification activity determines nitrogen transformation process and is solely catalyzed by ammonia oxidizers and nitrite oxidizers. Nitrification has been intensively investigated, generally, on a field scale in a single location but little has been done on a large scale. On a global scale, soil varies and distributes in the epigeosphere regularly according to certain laws as affected by different hydrothermal conditions. Meanwhile, soil microbial communities exhibit distinct biogeographic patterns and their distribution is mainly influenced by contemporary environmental factors and historical evolutionary factors. However, almost little is known about spatial patterns of functionally important biogeochemical processes that are mainly driven by microbial communities. In this study, here we report the construction of a soil nitrification database, meta-analysis of nitrification activity in ecosystems typical of China and main driving forces of nitrification rate on a national scale. From the 2 900 papers published both abroad and at home during the period of 1959-2013 on soil nitrification and found available in the literature database of soil science, 111 papers were collected according to the same data mining standards. A total of 288 sets of data were obtained on soil nitrification activity in the soils in 26 provinces of China. Based on the data extracted from the papers and acquired from the online database, a Soil Nitrification Information System (SNIS), was constructed. The system covers data, like sample locations, soil properties (including pH, total nitrogen, nitrate nitrogen, organic carbon, available phosphorous, clay content, etc.) and nitrification activity. Nitrification activity was assessed by three parameters including net nitrification rate, potential nitrification rate and gross nitrification rate using the conventional analytical methods. One-way analysis of variance (ANOVA) and the least significant difference test (LSD) were employed to explore difference in nitrification activity between different ecosystems, that is, farmland, grassland, forest land, desert and wetland. Pearson correlation analysis was employed to reveal relationships between soil properties and nitrification activity. Single factor models were used to estimate correlation coefficients between nitrification activity and soil properties. Net nitrification rate varied with the ecosystem, displaying a decreasing order of from farmland (NO₃⁻-N 1.39±0.27 mg kg^-1 d^-1) > grassland (0.74±0.17) > forest (0.66±0.16) > desert (0.17±0.08) > wetland (0.06±0.04). The net nitrification rate of the farmland ecosystem is significantly higher than those of the others. In terms of potential nitrification rate, grassland (7.41±3.73) ranks first among the five ecosystem and was followed by farmland (4.97±0.43), forest (1.06±0.24) and the other two, showing differences significant on a 0.05 level, while in terms of gross nitrification rate, forest land (7.76±0.43) did first and was followed by farmland (5.72±0.86), grassland (5.25±1.76) and the others. Pearson correlation analysis shows that in the farmland ecosystem, net nitrification rate was closely related to soil nitrate nitrogen and available phosphorous, and potential nitrification rate to soil pH, nitrate nitrogen, organic carbon and available phosphorous, while in the forest ecosystem, net nitrification rate was to soil available nitrogen and carbon-nitrogen ratio. Statistic analysis demonstrates that on the national scale, nitrification activity varied significantly between the ecosystems and nitrification rate was significantly lower in natural ecosystems than in anthropogenic ecosystems, and soil pH and nitrate nitrogen concentration appeared to be good indicators of soil nitrification activity in these ecosystems.