Current and future uses of OWL for Earth and Space science data frameworks: successes and limitations

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Presented at the AGU Fall Meeting 2007


Based on almost three years of experience in developing and deploying scientific data frameworks built using semantic technologies, we now have a production virtual observatory in operation, serving two broad communities: solar physics and terrestrial upper atmospheric physics. Within this application, a data framework provides online location, retrieval, and analysis services to a variety of heterogeneous scientific data sources distributed over the internet. We describe selected current and planned uses of our ontologies in OWL-DL, and tools involved in development and deployment. We describe both successes and limitations we have found to date using OWL- based technologies, especially tool support. We also indicate the important components we require from a robust technical infrastructure as we move forward with expanding the functionality of the frameworks. This expansion includes additional semantic representation and reasoning/query services as well as broadening the scope of our scientific disciplines.


DateCreated ByLink
May 13, 2013
Patrick WestDownload

Related Projects:

DCO-DS LogoVirtual Solar Terrestrial Observatory (VSTO)
Principal Investigator: Peter Fox
Co Investigator: Deborah L. McGuinness
Description: VSTO is a collaborative project between the High Altitude Observatory and Scientific Computing Division of the National Center for Atmospheric Research and McGuinness Associates. VSTO is funded by a grant from the National Science Foundation, Computer and Information Science and Engineering (CISE) in the Shared Cyberinfrastructure (SCI) division.

Related Research Areas:

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.