OBIS-USA: Enhancing Ocean Science Outcomes through Data Interoperability and Usability

Wednesday, 17 December 2014: 9:30 AM
Philip Goldstein, Univ of Colorado, Broomfield, CO, United States and Mark Fornwall, United States Geological Survey, Core Science Analytics, Synthesis, and Libraries, Lakewood, CO, United States
Commercial and industrial information systems have long built and relied upon standard data formats and transactions. Business processes, analytics, applications, and social networks emerge on top of these standards to create value. Examples of value delivered include operational productivity, analytics that enable growth and profit, and enhanced human communication and creativity for innovation.

In science informatics, some research and operational activities operate with only scattered adoption of standards and few of the emergent benefits of interoperability. In-situ biological data management in the marine domain is an exemplar. From the origination of biological occurrence records in surveys, observer programs, monitoring and experimentation, through distribution techniques, to applications, decisions, and management response, marine biological data can be difficult, limited, and costly to integrate because of non-standard and undocumented conditions in the data.

While this presentation identifies deficits in marine biological data practices, the presentation also identifies this as a field of opportunity. Standards for biological data and metadata do exist, with growing global adoption and extensibility features. Scientific, economic, and social-value motivations provide incentives to maximize marine science investments. Diverse science communities of national and international scale begin to see benefits of collaborative technologies.

OBIS-USA ( is a program of the United States Geological Survey. This presentation shows how OBIS-USA directly addresses the opportunity to enhance ocean science outcomes through data infrastructure, including: (1) achieving rapid, economical, and high-quality data capture and data flow, (2) offering technology for data storage and methods for data discovery and quality/suitability evaluation, (3) making data understandable and consistent for application purposes, (4) distributing and integrating data in various formats, (5) addressing a range of subject matter within data contents, and (6) preserving data for access long-term.