Other
Scientific paper
May 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008agusmin44a..02m&link_type=abstract
American Geophysical Union, Fall Meeting 2007, abstract #IN44A-02
Other
9810 New Fields (Not Classifiable Under Other Headings), 9820 Techniques Applicable In Three Or More Fields
Scientific paper
A limiting factor for virtual observatories which intend to make diverse data sets available to a diverse user base is that the following use cases are very difficult to implement: 1. Determine which flat field calibration was applied to the image taken on January, 26, 2005 around 2100UT by the ACOS Mark IV polarimeter. 2. What processing steps were completed to obtain the ACOS PICS limb image of the day for January 26, 2005. 3. What was the cloud cover and atmospheric seeing conditions during the local morning of January 26, 2005 at MLSO. Key to addressing these use cases often requires information that was either not collected from different stages in the data processing pipeline or it was but was not carried forward when the datasets were made available on-line. Collectively, this information is called provenance and in a semantic web data framework; knowledge provenance. In this presentation, we describe the knowledge provenance requirements that have emerged in our previous work on virtual observatories as well as requirements identified from a series of uses cases collected from scientific data users and instrument scientists. We will describe the progress we are making on meeting these requirements in the context of solar physics image data processing pipelines. The Semantic Provenance Capture in Data Ingest Systems (SPCDIS) is a NSF OCI/SDCI-funded project to implement an extensible meta data provenance scheme within the Virtual Solar-Terrestrial Observatory.
Fox Patrick
Garcia Javier
McGuinness D.
Zednik S.
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