Semantic Representation of Temporal Metadata in a Virtual Observatory

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Presented at the AGU Fall Meeting 2011


The Virtual Solar-Terrestrial Observatory (VSTO) Portal at provides a set of guided workflows to implement use cases designed for solar-terrestrial physics and upper atmospheric science. Semantics are used in VSTO to model abstract instrument and parameter classifications, providing data access to users without extended domain specific vocabularies. The temporal restrictions used in the workflows are currently possible via RESTful services made to a remote system with access to a SQL-based metadata catalog. In order to provide a greater range of temporal reasoning and search capabilities for the user, we propose an alternative architecture design for the VSTO Portal, where the temporal metadata is integrated in the domain ontology. We achieve this integration by converting temporal metadata from the headers of raw data files into RDF using the OWL-Time vocabulary. This presentation covers our work with semantic temporal metadata, including: our representation using OWL-Time, issues that we have faced in persistent storage, and performance and scalability of semantic query. We conclude with discussions of the significance semantic temporal metadata has in virtual observatories.


DateCreated ByLink
December 4, 2011
Han WangDownload
December 4, 2011
Han WangDownload

Related Projects:

SeSF Project LogoSemantic eScience Framework (SeSF)
Principal Investigator: Peter Fox
Co Investigator: Jim Hendler and Deborah L. McGuinness
Description: Over the past few years, semantic technologies have evolved and new tools are appearing. Part of the effort in this project will be to accommodate these advances in the new framework and lay out a sustainable software path for the (certain) technical advances. In addition to a generalization of the current data science interface, we will include an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.

Related Research Areas:

Data Frameworks
Lead Professor: Peter Fox
Description: None.
Concepts: eScience