Developing an Ontology for Ocean Biogeochemistry Data

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Presented at the AGU Fall Meeting 2010


Semantic Web technologies offer great promise for enabling new and better scientific research. However, significant challenges must be met before the promise of the Semantic Web can be realized for a discipline as diverse as oceanography. Evolving expectations for open access to research data combined with the complexity of global ecosystem science research themes present a significant challenge, and one that is best met through an informatics approach. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is funded by the National Science Foundation Division of Ocean Sciences to work with ocean biogeochemistry researchers to improve access to data resulting from their respective programs. In an effort to improve data access, BCO-DMO staff members are collaborating with researchers from the Tetherless World Constellation (Rensselaer Polytechnic Institute) to develop an ontology that formally describes the concepts and relationships in the data managed by the BCO-DMO. The project required transforming a legacy system of human-readable, flat files of metadata to well-ordered controlled vocabularies to a fully developed ontology. To improve semantic interoperability, terms from the BCO-DMO controlled vocabularies are being mapped to controlled vocabulary terms adopted by other oceanographic data management organizations. While the entire process has proven to be difficult, time-consuming and labor-intensive, the work has been rewarding and is a necessary prerequisite for the eventual incorporation of Semantic Web tools. From the beginning of the project, development of the ontology has been guided by a use case based approach. The use cases were derived from data access related requests received from members of the research community served by the BCO-DMO. The resultant ontology satisfies the requirements of the use cases and reflects the information stored in the metadata database. The BCO-DMO metadata database currently contains information that powers several different user and machine-to-machine interfaces to the BCO-DMO data repositories. One goal of the ontology development project is to enable subsequent development of semantically-enabled components (e.g. faceted search) to enhance the power of those interfaces. Addition of semantic capabilities to the existing data interfaces will improve data access through enhanced data discovery. In addition to sharing the ontology, we will describe the challenges encountered thus far in the project, the technologies currently being used, and the strategies associated with the use case based informatics approach.


DateCreated ByLink
October 20, 2014
Patrick WestDownload

Related Projects:

Biological and Chemical Oceanography Data Management OfficeBiological and Chemical Oceanography Data Management Office (BCO-DMO)
Principal Investigator: Peter Fox
Description: The Biological and Chemical Oceanography Data Management Office (BCO-DMO) was created to serve PIs funded by the NSF Biological and Chemical Oceanography Sections as a location where marine biogeochemical, ecological and oceanographic data and information developed in the course of scientific research can easily be disseminated, protected, and stored on short and intermediate time-frames.

Related Research Areas:

Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

Concepts: eScience
Semantic eScience
Lead Professor: Peter Fox
Science has fully entered a new mode of operation. E-science, defined as a combination of science, informatics, computer science, cyberinfrastructure and information technology is changing the way all of these disciplines do both their individual and collaborative work.
As semantic technologies have been gaining momentum in various e-Science areas (for example, W3C's new interest group for semantic web health care and life science), it is important to offer semantic-based methodologies, tools, middleware to facilitate scientific knowledge modeling, logical-based hypothesis checking, semantic data integration and application composition, integrated knowledge discovery and data analyzing for different e-Science applications.
Partially influenced by the Artificial Intelligence community, the Semantic Web researchers have largely focused on formal aspects of semantic representation languages or general-purpose semantic application development, with inadequate consideration of requirements from specific science areas. On the other hand, general science researchers are growing ever more dependent on the web, but they have no coherent agenda for exploring the emerging trends on the semantic web technologies. It urgently requires the development of a multi-disciplinary field to foster the growth and development of e-Science applications based on the semantic technologies and related knowledge-based approaches.

Concepts: eScience
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: , eScience