Welcome to the GeoStrat Digital Information System (GeoStrat) - our gateway to data management and discovery. GeoStrat is supported by the Earth Sciences Division of the National Science Foundation.

GeoStrat targets the next generation of data management for field- and laboratory-based science.  No longer is it sufficient for a researcher to document their work by only publishing a paper, even if a supplemental data table is included. No longer is it sufficient to think of data management only in terms of datasets and their associated papers, we have to break these up into their component data bits and work with them at that level. We have to enter the modern realm where all data associated with all research can be accessed in their most granular, discrete form while maintaining the attribution of each bit of data to its original author. These data must be openly accessible, once they are public, but held privately during a publication moratorium period.  We need to have seamless links from the structured databases to publications. This will allow future users to easily move from the published paper to the data and metadata behind the publication and just as easily utilize these data in their ongoing research.

A major challenge is to build such systems without imposing artificial constraints on the scientist users. For example, restricted vocabularies where each word has one meaning. This restriction makes the discovery and movement of information easier through the Internet, but it compromises knowledge. In contrast, a thesaurus approach is much better; this increases the technological challenges, but better supports the integrity of the knowledge behind the data.  For example, we may want some geologic maps to be "edge-matched" with units, their ages and descriptions uniform across all maps - but only at the regional to global scales. At the quadrangle scale or larger, it is the differences among maps that carry the meaning as these differences reflect the interpretations of the authors. In short, the system cannot overly impose its design restrictions on the scientist if we truly want to build systems for the science. It is harder to do it this way, but better for the science.

Data drive transformative, transparent, and collaborative science.

                                                                                            - Dr. Walter Snyder