Earth Science Datacasting is an RSS-based technology for distributing Earth Science data. Providers of the data publish the availability of files through a web-feed, along with relevant ancillary information pertinent to Earth Science data (e.g., file format, data collection methods and data content). Users subscribe to the feeds with the Datacasting Feed Reader, which enables them to list and interrogate the feeds for identification and download of the files for further analysis.
VERSION 2.0 IS OUT
Version 2.0 of the Earth Science Datacasting Client is now available for download.
The software consists of two parts:
- A set of publishing scripts that provide data providers an easy way to generate XML formatted feeds accessible via a URL
- A java based Feed Reader, which consumers of the data use to subscribe to the feeds and download earth science data
A powerful addition to the Datacasting Feed Reader is that of filtering, which gives users the ability to precisely identify the files that are relevant to a particular need. By building filters that make comparisons with information contained within a feed, users are able to construct lists of relevant files and have these files downloaded automatically.
For example, a user might subscribe to a Datacasting feed that contains information about files produced by an orbiting imaging satellite, but they may only be interested in data that contain wild fires in California. The user would therefore construct a filter that lists only the files that have been tagged in the Datacasting feed to contain data related to a wild fire and imaged within a bounding box (). The user could further refine the filter to show only the files where the wild fire exceeds a specific size or within a certain distance of an urban area.
The types of filters a user can build are solely dependent on the richness of information tagged in the web-feed. Our hope is that through the Datacasting forum, users are able to make recommendations to data providers on the information that ought to be contained within a feed and also promote the uptake of standard metadata conventions and taxonomies, and thereby enable filtering across multiple feeds.
In this way, a user interested in identifying all satellite and buoy data that are contained within a specific region and during a specific period that contain information about a harmful algae bloom can identify data relating to their interests. They could even extract higher-order information by building filters that provide answers to questions such as: Are there any HABs currently identified in my area of interest?
In addition to filtering, the Datacasting Feed Reader will have the ability to read files that have been downloaded and display the data. The intent is to give users the capability to quickly analyze the data and further decide if it is useful or not. For more in depth investigations, users would use their usual tools to perform analyses on the downloaded data.