Development of a data management framework in support of southeastern tidal creek research

Abstract

The NOAA Center of Excellence for Oceans and Human Health Initiative (OHHI) at the Hollings Marine Laboratory (HML) is developing a data management framework that supports an integrated research program across scientific disciplines. The primary focus of the database is to support environmental research focused on tidal creek watershed systems. Specifically, the current data holdings include physical water quality parameters, nutrients, pathogens, chemical contaminants, benthic and nekton species abundances and human dimensions data from Georgia, North Carolina and South Carolina dating to 1994. These data are not from a single long-term research project but are derived from several state and federal research programs and integrated into a common database model to support current research being conducted under the OHHI program at HML. The Tidal Creek database was developed with the intent to support a well documented and open system, thus metadata elements from common metadata standards including the Dublin Core ISO 15836:2003 and Federal Geographic Data Committee (FGDC-STD-001-1998) are components of the database model. The result is a semantic database framework with descriptive ancillary data at the record level including methods, investigator names, date, locations and other descriptive elements. The primary users of the database are project personnel to meet analytical needs. The database is also available through a number of web-based applications that are designed to give users the necessary information to evaluate and access data. In addition, data can be accessed with Open Geospatial Consortium (OGC) standards, and species records and abundances are being made available to the Ocean Biogeographic Information System (OBIS). Overall, the Tidal Creek database summarizes the response of tidal creeks and watersheds to coastal development, and serves as a repository for environmental, demographic, and socioeconomic data in the Southeast.