Rationale

With recent initiatives within many scientific communities toward trans-disciplinary, synthetic research using both new and existing data resources, our ability to share, discover, interpret, and integrate data is paramount to scientific progress. Indeed, new scientific advances are dependent on the synthesis of observations from multiple measurements, at multiple scales, across scientific disciplines, across environmental observatory or other experimental sites, and from multiple sources. We are now at a point where our ability to collect data far outstrips our capabilities to analyze it using existing technologies and where the inadequacy of tools available for describing and sharing data leads to heterogeneity in the way data are organized, described, and encoded that hinders its discovery and interpretation.

Several systems have emerged within geoscience communities for sharing earth observations, including the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS), EarthChem, the Integrated Ocean Observing System (IOOS), and, more recently, the Critical Zone Observatory (CZO) Integrated Data Management System (CZOData) and the Data Observations Network for Earth (DataONE). While these systems have increased the availability and reduced the heterogeneity of earth observations within geoscience domains, deficiencies remain because they describe, encode, and publish data differently. This limits the ability of all of these systems to unambiguously describe observations in a way that they could be interpreted by scientists from outside the domain.

The information model and prototype schemas we are developing are consistent with the architectures of the systems listed above, but enhance domain-specific information models and encodings used by these systems. ODM2 is standardizing descriptions of common characteristics of spatially-discrete, feature-based earth observations. This will lead to opportunities for more reliable data and information integration across multiple domain cyberinfrastructures.