  Spatial Data Infrastructure (SDI) is an important concept for sharing spatial
data across the web. With cumulative techniques with spatial cloud computing
and fog computing, SDI has the greater potential and has been emerged as a tool
for processing, analysis and transmission of spatial data. The Fog computing is
a paradigm where Fog devices help to increase throughput and reduce latency at
the edge of the client with respect to cloud computing environment. This paper
proposed and developed a fog computing based SDI framework for mining analytics
from spatial big data for mineral resources management in India. We built a
prototype using Raspberry Pi, an embedded microprocessor. We validated by
taking suitable case study of mineral resources management in India by doing
preliminary analysis including overlay analysis. Results showed that fog
computing hold a great promise for analysis of spatial data. We used open
source GIS i.e. QGIS and QIS plugin for reducing the transmission to cloud from
the fog node.
