Feature - Academia Sinica watches global carbon
With the help of data standards and computing resources, Academia Sinica Grid Computing Center (ASGC) has developed an innovative, grid-enabled approach to tackle carbon flux observation.
The carbon cycle — in which the carbon from the greenhouse gas carbon dioxide (CO2) travels from the atmosphere to living creatures to the ground and back — plays a key part to global warming. Therefore, observing how this cycle fluctuates tells researchers much about climate change.
One of the ways to do so is with a network of 500 geographically dispersed collecting towers, whose raw data provides information for use in both the global flux research community and for broader research communities interested in carbon cycle observation and global climate change.
However, the ecological data collected from the sensors of different tower sites are stored in different databases which do not have a standardized format; to reprocess the data has so far required complicated pipeline computing.
But now, Academia Sinica Grid Computing Center (ASGC) has developed a new, grid-oriented way in which to deal with carbon flux observations.
Taking advantage of grid technologies, this prototype features data management, massive job submission and on-demand computing resources. The system integrates the Grid Application Platform (GAP), the Kepler scientific workflow system and a data warehouse framework.
The GAP — developed by ASGC — is designed to reduce the complexity in accessing the grid environment. Not only does GAP allow massive job submission, but is also provides other functions such as job monitoring and data discovery.
Bridging with the GAP
Meanwhile, the data warehouse framework, by using the Ecological Metadata Language (EML) standard and the AMGA Metadata Service, was incorporated into the grid system to handle the heterogeneity and complexity of ecological data. Raw data is automatically archived on EGEE, and users can easily retrieve and access data via the Metadata Server and the GAP framework.
In addition to data management, the data warehouse framework is also capable of data processing and analysis functions.
In an attempt to bring a new e-Science infrastructure approach to the carbon flux community in Taiwan, ASGC is employing grid technologies with the traditional workflow system. By deploying the new approach, carbon flux users could easily access distributed data sets, and submit and monitor their jobs.
Today, several Asian users – such as Thailand and Malaysia – have expressed interest in joining the carbon flux application initiated by ASGC.
—ASGC, for iSGTW