Contemporary Computing Technologies for Processing Big Spatiotemporal Data - Space-Time Integration in Geography and GIScience - page 326

Fig. 18.1 Big data discovery
flow with GEOSS
clearinghouse as an example

process by providing basic description of data so that we can handle relative small
scale data (e.g. metadata with 10-20 elements) before getting to real big data.
Global Earth Observation System of Systems (GEOSS) clearinghouse is one of
such components (GEO 2012 ). GEOSS clearinghouse facilitates better integration
and access to geospatial resources for GEOSS and other global communities
by providing metadata/data management, and discovery capability. In GEOSS
clearinghouse, metadata, data content and online access are standardized through
different metadata schema, which includes: (1) FGDC CSDGM Metadata Standards
(FGDC 2012 ), (2) Dublin core (Dublin 2012 ), (3) ISO-19115, and (4) ISO-
19139. These metadata standards can be extended to different data series and
datasets including geographic features and feature properties. For example, ISO
standards precisely define the description of geographic information and provide
the mandatory and conditional metadata sections, metadata entities and metadata
elements. These standardized metadata could be archived in various catalogs that
provide searching capabilities for different domain users (Huang et al. 2011 ).

18.3.2 Database and Index

The GEOSS clearinghouse supports MySQL, Postgresql, Oracle, MckoiDB, and
SQL server as the database according to different requirements. It also support