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Automated Data Analysis with Knowledge Ontologies
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| A major advance in the direction of automated scientific data analysis becomes clear by recognizing that the graphical representation of procedures in Visual Programming (VP) is a directed graph that can be represented by standard ontology such as the W3Cís OWL. A merger of these two technologies would brings together set theory, first order logic reasoning, planning and scheduling, and XML technologies of ontologies, with the advanced modeling, on-the-fly programming, and interchangeable software components of VP. Additionally, both ontology and VP interface well with the distributed execution and storage technologies of WebServices and the Grid. Therefore, such an integrated system is not limited by the local hardware capabilities. For this AISR we propose to make use of mostly existing open source software to create an extremely powerful space science data analysis tool that implements expert knowledge about space science and learns and grows by experiences shared by multiple users across the web. We will replace the graphical front end typically used in a visual programming (VP) software (SCIRun from http://software.sci.utah.edu/) with an ontological front-end (ProtÈgÈ http://protege.stanford.edu) that provide knowledge of the relationships between transformations/functions and data classes. We will add to the existing set of functions available to SCIRun a selected set of functions needed in space physics and astronomy. We will provide read and write for standard data formats (CDF, FITS and VOTable). We will provide query tools for extracting data from the Virtual Observatories and individual data centers. We will add the capability of transparently shifting computations to the Grid when the load is too heavy for local resources. Finally, we will provide a web based repository where working procedures and relationships are stored as OWL/RDF files. This is a novel computational method that will increase productivity of researchers by making it irrelevant to create detailed programs/scripts or even flow diagrams for each step in a scientific investigation. Scientific return and public outreach will be enhanced by simplifying the path to creating visualization of complex data. We will be providing a key step in enabling recent IT developments in semantic Web and advance problem solving for scientific output of OSS missions. In addition, this package will make possible increased data return through onboard science processing and reduction which also leads to huge compression factors. |
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