PUBLICATIONS and PRESENTATIONS
Visualize, analyze and mine satellite imagery using GLIDER software tool. In: 90th AMS Annual Meeting. 90th AMS Annual Meeting. Atlanta, GA; 2010.
. Mine Your Data: GLIDER brings data mining to the masses. [Internet]. 2012 . Available from: https://www.itsc.uah.edu/sites/default/files/esipmeeting2011_glider.jpg
. Bird's Eye View of Data Mining in Geosciences. In: Geoinformatics: Data to Knowledge. Geoinformatics: Data to Knowledge. Geological Society of America Special Paper 397; 2006.
. Investigating Data Mining Techniques to Detect Dust Storms in MODIS Imagery. 32nd International Symposium on Remote Sensing of Environment. 2007 .
. GLIDER: Earth Science Image Visualization and Analysis. 2010 [Internet]. 2010 . Available from: https://www.itsc.uah.edu/main/sites/default/files/glider_poster.jpg
. Flexible Framework for Mining Meteorological Data. American Meteorological Society's (AMS) 19th International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology. 2003 .
. Visualize, Analyze and Mine Satellite Imagery Using a Single Tool. In: 17th International Conference on Geoinformatics. 17th International Conference on Geoinformatics. Fairfax, VA; 2009. Available from: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5292953
. Data Prospecting–A Step Towards Data Intensive Science. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2013 ;6(3):1233-1241.
. Earth Science Markup Language: A Solution for Generic Access to Heterogeneous Data Sets. NASA Earth Science Technology Conference. 2001 .
. Ontology Re-engineering Use Case: Extending SWEET to Map Climate and Forecasting Vocabulary Terms. Geoinformatics 2006. 2006 .
. Earth Science Markup Language: An update. NASA Earth Science Technology Conference. 2002 .
. Mining Earth Science Data. 8th International Symposium on Remote Sensing of Environment. 2000 .
. Earth Science Markup Language Tutorial. In: Earth Science Federation Meeting. Earth Science Federation Meeting. Boulder, Colorado; 2003.
. Noesis: Ontology based Scoped Search Engine and Resource Aggregator for Atmospheric Science. AGU Annual Meeting. 2006 .
. Estimating Ice Water Content Using Observed Lightning. International Conference on Atmospheric Electricity. 1996 .
. Emergent Science - a new way forward?. In: IEEE International Geoscience & Remote Sensing Symposium. IEEE International Geoscience & Remote Sensing Symposium. Honolulu, HI; 2010.
. Data Mining: Atmospheric Science Case Study. In: NASA Workshop on Issues in the Application of Data Mining to Scientific Data. NASA Workshop on Issues in the Application of Data Mining to Scientific Data. University of Alabama in Huntsville, Huntsville, AL; 1999.
. Create Collaboratories for Earth Science using Talkoot. [Internet]. 2012 . Available from: https://www.itsc.uah.edu/sites/default/files/ESIPmeeting2012_Talkoot_poster.jpg
. A Syntactic and Semantic Metadata Solution for Intelligent Applications in Earth Science. American Geophysical Union 2004 Fall Meeting. 2004 .
. Polaris: A Discovery Engine for Big Data. IGARSS. 2013 .
. WxGuru: An ontology driven chatbot prototype for Atmospheric Science Outreach and Education. In: Geoinformatics 2007 Conference. Geoinformatics 2007 Conference. San Diego, CA; 2007.
. Earth Science Markup Language: A Solution to the Earth Science Data Format Heterogeneity Problem. American Meteorological Society's (AMS) 19th International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology. 2003 .
. Talkoot Software Appliance for Collaborative Science. In: IEEE International Geoscience & Remote Sensing Symposium. IEEE International Geoscience & Remote Sensing Symposium. Cape Town, South Africa; 2009.
. Intelligent Data Thinning Algorithm for Earth System Numerical Model Research and Application. 21st International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, 85th AMS Annual Meeting. 2005 .
. Earth Science Markup Language (ESML): a solution for scientific data-application interoperability problem. Computers & Geosciences [Internet]. 2004 ;30:117-124. Available from: http://www.sciencedirect.com/science/article/B6V7D-4BF5TY9-2/2/430d6854b74d0499f30ce80b57d51966
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