Broad-scale ecological studies often require information assembled from multiple disciplines. Data heterogeneity across multiple disciplines and data sets creates major informatics challenges that include the need to better discover, access, interpret, and integrate relevant data that have been collected by others. A National Science Foundation (NSF) sponsored workshop was held to address these challenges. The major conclusion from the workshop was that a shared model for observational data would facilitate data interoperability, and would enable significant integration within and across disciplines. This observational data model would provide a flexible and ubiquitous construct for scientific data, and would be appropriate for building an interoperable data sharing framework. Promoting a shared community model for observations could lead to major implementation advantages, and facilitate tool construction and re-use. This presentation will provide more detail on the results of the workshop.