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Applying Semantics in Dataset Summarization for Solar Data Ingest Pipelines

IN51D- 1713. Semantic Visualization Provenance Records:. Intensity Visualizations. Applying Semantics in Dataset Summarization for Solar Data Ingest Pipelines

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Applying Semantics in Dataset Summarization for Solar Data Ingest Pipelines

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  1. IN51D-1713 Semantic Visualization Provenance Records: Intensity Visualizations Applying Semantics in Dataset Summarization for Solar Data Ingest Pipelines James Michaelis (michaelis@cs.rpi.edu), Deborah L. McGuinness(dlm@cs.rpi.edu), Stephan Zednik(zednis@rpi.edu), Patrick West (westp@rpi.edu), Peter Arthur Fox (pfox@cs.rpi.edu) Rensselaer Polytechnic Institute 110 8th St., Troy, NY, 12180 United States Raw Image Data Captured Publishes Mauna Loa Solar Observatory (MLSO) Hawaii National Center for Atmospheric Research (NCAR) Data Center. Boulder, CO Raw Image Data Follow-up Processing on Raw Data • Motivations and Challenges: • Analysis of solar data necessary for space weather modeling and forecasting – which have broad implications for terrestrial activity (e.g., communication grid reliability). • Time series visualizations of solar activity, created by the High Altitude Observatory [1], enable needed analyses. • This work focuses on two challenges: • Only small sections of the data will typically contain content of interest to scientists • Subsets of time-series data may correspond to an event of interest at a particular time (e.g., a solar event) • Based on these challenges, one goal in this work was to enable scientists to get back data sets corresponding to desired data products - to facilitate further analysis. • Data Management Strategies: • Provenance records for individual visualizations. • Ontological classification of visualizations, using DQ and STOM • Encoding records in RDF Datacube [2] (proposed) Datacube Basics: Properties attached to datasets/slices/observations: Dimensions: Year, Metric Attributes:GBU Metric Measures:146 (the value) Case Study: Coronal Multi-channel Polarimeter (CoMP): • Datacube Usage: • For HAO visualization records, Datacube can be used in two ways: • Returning aggregations of statistics for images (e.g., GBU results). • - Returning sets of visualizations (data points) for further exploration, based on constraints (e.g., temporal range). • Use Cases: • - Activity Log Usage: Return images corresponding to a specific solar event record. • - Provenance (utilized data product): For this set of images utilizing the following flat fieldconfiguration file. • - Provenance (utilized process): For this set of images running based on version 2.0 of process “Extract Intensity”. • - Observer Log Usage: For the following observer log comment, return visualizations within 2 hours of the comment timestamp. Time-stamped Observation Logs, maintained by MLSO staff. Comments on: Weather + Instrument conditions Time-stamped Activity Logs, maintained by MLSO staff. Comments on solar events (Coronal Mass Ejections, Active Regions) Next Steps Sponsors: National Science Foundation Get the poster at - Deployment of provenance record retrieval as part of Virtual Solar Terrestrial Observatory . - Semantic Encoding of MLSO Event Logs - or data from Lockheed Martin's Heliophysics Events Knowledge Base [3]. - Expanded use of dimensions in data cube, to include FITS header data. http://bit.ly/V8NkBo Poster: MT15A-08 Glossary: RPI – Rensselaer Polytechnic Institute TWC – Tetherless World Constellation at Rensselaer Polytechnic Institute VSTO – Virtual Solar Terrestrial Observatory. FITS – Flexible Image Transport System References: [1] Mauna Loa Solar Observatory (High Altitude Observatory Site): http://mlso.hao.ucar.edu/ [2] RDF Datacube Vocabulary: http://www.w3.org/TR/vocab-data-cube/ [3] Heliophysics Event Knowledge Base: http://www.lmsal.com/hek/index.html Acknowledgments: Sapan Shah and Naveen Sridhar from the Tetherless World Constellation at RPI Joan Burkepile, Steve Tomczyk and Leonard Sitongia at the High Altitude Observatory.

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