Making United States Integrated Ocean Observing System (U.S. IOOS) inclusive of marine biological resources
An important Data Management and Communication (DMAC) goal is to enable a multi-disciplinary view of the ocean environment by facilitating discovery and integration of data from various sources, projects and scientific domains. United States Integrated Ocean Observing System (U.S. IOOS) DMAC functional requirements are based upon guidelines for standardized data access services, data formats, metadata, controlled vocabularies, and other conventions. So far, the data integration effort has focused on geophysical U.S. IOOS core variables such as temperature, salinity, ocean currents, etc. The IOOS Biological Observations Project is addressing the DMAC requirements that pertain to biological observations standards and interoperability applicable to U.S. IOOS and to various observing systems. Biological observations are highly heterogeneous and the variety of formats, logical structures, and sampling methods create significant challenges. Here we describe an informatics framework for biological observing data (e.g. species presence/absence and abundance data) that will expand information content and reconcile standards for the representation and integration of these biological observations for users to maximize the value of these observing data. We further propose that the approach described can be applied to other datasets generated in scientific observing surveys and will provide a vehicle for wider dissemination of biological observing data. We propose to employ data definition conventions that are well understood in U.S. IOOS and to combine these with ratified terminologies, policies and guidelines.
Citation Information
Publication Year | 2011 |
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Title | Making United States Integrated Ocean Observing System (U.S. IOOS) inclusive of marine biological resources |
DOI | 10.23919/OCEANS.2011.6106922 |
Authors | H. Moustahfid, J. Potemra, P. Goldstein, R. Mendelssohn, A. Desrochers |
Publication Type | Conference Paper |
Publication Subtype | Conference Paper |
Index ID | 70035655 |
Record Source | USGS Publications Warehouse |