significant issues, discussed in the sections below and covered in greater depth in Annex 1 (which provides a short history of the EOSDIS), have swirled around EOSDIS from the beginning.
Attention over the past decade has focused on the design and implementation of a data and information system—with emphasis on the “system.” Today, in view of the issues, it may be advantageous to focus less on a system and more on the capabilities and attributes that will enable and encourage the most effective use of the data by scientists and others.
The motivation for public investment in EOS is the enhancement in scientific understanding, applications, and education that will result from the observations. But for these benefits to be realized, the data must be readily available to all who would use them. Over the past decade the advance of computer and information systems has dramatically altered the possibilities of taking advantage of data streams with large data rates. Nevertheless, many issues remain. In fact, many of these issues are true for any large data system and hence also bear on the so-called Global Change Data and Information System. The only issue unique to EOS is the fact that it is space borne with specific instruments. There are three different areas of concern:
Data stream processing and operations. For Earth observations such as those of EOS, there will be strong interdependencies among instruments that must be resolved during data processing, and thus algorithmic complexities and sequencing issues complicate the problems associated with large data rates. The instrument teams must find ways to interact effectively to produce accurate data and to document carefully and rigorously what has been done to the observations. These are management not technology issues, and it is important to seek a solution that is no more complex than the particular circumstances require.
Archiving. Technological and conceptual advances together have dramatically improved communication lines between the sources and potential users of data. Individual scientists can have capabilities at their workstations that rival those of computer centers of a few years ago; and the power of contemporary communications capabilities such as the World Wide Web, which have revolutionized interactions among scientists as well as access to data sources. How much we should depend on this rapidly evolving environment in developing EOS data capabilities has been controversial. Questions about how to store and eventually archive data are also pressing, with modern technologies obviating old assumptions and offering wide replication of datasets as a potentially more secure approach than formal archiving.