{"id":78,"date":"2021-06-30T20:32:48","date_gmt":"2021-06-30T20:32:48","guid":{"rendered":"https:\/\/www.mcgovern-fagg.org\/idea\/?page_id=78"},"modified":"2021-06-30T20:33:01","modified_gmt":"2021-06-30T20:33:01","slug":"software","status":"publish","type":"page","link":"https:\/\/www.mcgovern-fagg.org\/idea\/software\/","title":{"rendered":"Software"},"content":{"rendered":"<div class=\"boldgrid-section\">\n<div class=\"container\">\n<div class=\"row\">\n<div class=\"col-md-12 col-xs-12 col-sm-12\">\n<h1 class=\"\" style=\"text-align: center;\">IDEA Lab Software&nbsp;<\/h1>\n<p class=\"\">Software releases are listed below by the type of software. Most of our lab paper publications and theses &amp; dissertations release code when they appear.<\/p>\n<h2 class=\"red\">Hagelslag<\/h2>\n<ul>\n<li>Hagelslag is an object-based severe storm hazard forecasting system, developed and released open source by&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/theses\/gagne_phd\/index.html\">David Gagne as part of his PhD thesis<\/a>.<\/li>\n<li>Gagne II, D. J., A. McGovern, N. Snook, R. Sobash, J. Labriola, J. K. Williams, S. E. Haupt, and M. Xue, 2016:<br \/>\nHagelslag: Scalable object-based severe weather analysis and forecasting. Proceedings of the Sixth Symposium on<br \/>\nAdvances in Modeling and Analysis Using Python, New Orleans, LA, Amer. Meteor. Soc., 447.<\/li>\n<li><a href=\"https:\/\/github.com\/djgagne\/hagelslag\">Link to Hagelslag on github<\/a><\/li>\n<\/ul>\n<h2><span class=\"red\">Spatiotemporal Relational Random Forests and Spatiotemporal Relational Probability Trees<\/span><\/h2>\n<ul>\n<li>McGovern, Amy and Gagne II, David J. and Williams, John K. and Brown, Rodger A. and Basara, Jeffrey B. (2014)&nbsp;<em>Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning<\/em>. Machine Learning. Volume 95, Issue 1, Pages 27-50.&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/software\/mlj_2013\">Code, paper, software, and data<\/a>.<\/li>\n<li>Nathaniel Troutman. (2010).&nbsp;<em>Enhanced Spatiotemporal Relational Probability Trees and Forests.&nbsp;<\/em>Master&#8217;s Thesis, School of Computer Science, University of Oklahoma.&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/thesis\/ntroutman\/index.html\">Code, data, and the thesis.<\/a><\/li>\n<li>McGovern, Amy; Supinie, Timothy; Gagne II, David John; Troutman, Nathaniel; Collier, Matthew; Brown, Rodger A.; Basara, Jeffrey; Williams, John. (2010)&nbsp;<em>Understanding Severe Weather Processes through Spatiotemporal Relational Random Forests<\/em>. To appear in the NASA Conference on Intelligent Data Understanding: CIDU 2010.&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/software\/cidu2010\/index.html\">Code and data for the paper.<\/a><\/li>\n<\/ul>\n<h2 class=\"red\">Spacewar<\/h2>\n<ul>\n<li>McGovern, Amy and Trytten, Deborah. (2013).&nbsp;<em>Making In-Class Competitions Desirable For Marginalized Groups<\/em>. Proceedings of the 2013 Frontiers in Education Conference, pages 704-706. [<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/pubs\/McGovernTryttenFIE2013.pdf\">pdf<\/a>&nbsp;(261K)]&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/software\/spacewar\/index.html\">Code and documentation.<\/a><\/li>\n<li>McGovern, Amy and Tidwell, Zachery and Rushing, Derek (2011).&nbsp;<em>Teaching Introductory Artificial Intelligence through Java-based Games<\/em>. Proceedings of the symposium on Educational Advances in Artificial Intelligence.&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/software\/eaai_2011\">Code, paper, and model assignments<\/a>.<\/li>\n<li><a href=\"http:\/\/www.cs.ou.edu\/~amy\">McGovern, Amy<\/a>, and Fager, Jason. (2007)&nbsp;<em>Creating Significant Learning Experiences in Introductory Artificial Intelligence<\/em>. Proceedings of SIGCSE 2007, technical symposium on computer science education, pages 39-43. [<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/pubs\/mcgovern_sigcse2007.pdf\">pdf<\/a>&nbsp;(223K)]<\/li>\n<\/ul>\n<h2 class=\"red\">Tornado motif mining<\/h2>\n<ul>\n<li><span class=\"doublespace\">McGovern, Amy and Rosendahl, Derek H. and Brown, Rodger A.(2014)<em>&nbsp;Toward Understanding Tornado Formation Through Spatiotemporal Data Mining<\/em>.&nbsp;<a href=\"http:\/\/www.springer.com\/computer\/database+management+%26+information+retrieval\/book\/978-1-4614-7668-9\">Book chapter in Data Mining for Geoinformatics: Methods and Applications<\/a>, edited by Cervone, Guid and Lin, Jessica and Waters, Nigel. 29 DOI 10.1007\/978-1-4614-7669-6 2, Springer Science Business Media New York 2014. [link to a<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/McGovernRosendahlBrown2014.pdf\">pre-print of the pdf<\/a>. The officially formatted pdf is linked above.]<\/span><\/li>\n<li><span class=\"doublespace\">McGovern, Amy; Rosendahl, Derek H; Brown, Rodger A; and Droegemeier, Kelvin K. (2011) Identifying Predictive Multi-Dimensional Time Series Motifs: An application to severe weather prediction. Data Mining and Knowledge Discovery. Volume 22, Issue 1, pages 232-258. [<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/pubs\/mcgovern_dmkd2011.pdf\">pdf<\/a>&nbsp;(2.0M).&nbsp;<a href=\"http:\/\/www.springerlink.com\/content\/9w77364l2605h2r5\/\">Link to official springer version<\/a>.]<\/span><\/li>\n<li><a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/theses\/drosendahl\/index.html\">Code and data from the paper are on Derek Rosendahl&#8217;s thesis page.<\/a><\/li>\n<\/ul>\n<h2 class=\"red\">Multi-Modal Utility Trees<\/h2>\n<ul>\n<li>Dabney, William and McGovern, Amy (2010). Multi-Modal Utile Distinctions. University of Massachusetts Amherst Technical Report UM-CS-2010-065.<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/mmu\/index.html\">Code and tech report<\/a><\/li>\n<\/ul>\n<h2 class=\"red\">Ensembles of Bayesian Probability Networks<\/h2>\n<ul>\n<li>Christopher Utz. (2010).&nbsp;<em>Learning Ensembles of Bayesian Network Structures Using Random Forest Techniques.<\/em>&nbsp;Master&#8217;s Thesis, School of Computer Science, University of Oklahoma.&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/theses\/cutz\/index.html\">Code, data, and the thesis.<\/a><\/li>\n<\/ul>\n<h2 class=\"red\">Spatial kernels for drought<\/h2>\n<ul>\n<li>Collier, Matthew and McGovern, Amy. (2008).&nbsp;<em>Kernels for the Investigation of Localized Spatiotemporal Transitions of Drought with Support Vector Machines<\/em>. Proceedings of ICDM 2008, the 8th IEEE International Conference on Data Mining Workshops. Pisa, Italy. 15-19 December 2008, pages 359-368. [<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/pubs\/Collier_McGovern_ICDM2008.pdf\">pdf (400K)<\/a>]&nbsp;<a href=\"https:\/\/mcgovern-fagg.org\/idea_html\/software\/drought\/index.html\">Data page corresponding to the paper<\/a><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>IDEA Lab Software&nbsp; Software releases are listed below by the type of software. Most of our lab paper publications and theses &amp; dissertations release code when they appear. Hagelslag Hagelslag<\/p>\n<div class=\"read-more\"><a class=\"btn button-secondary\" href=\"https:\/\/www.mcgovern-fagg.org\/idea\/software\/\">Read More<\/a><\/div>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"bgseo_title":"Idea Lab Software","bgseo_description":"","bgseo_robots_index":"index","bgseo_robots_follow":"follow","crio-premium-page-header-override":null,"crio-premium-page-header-select":"none","crio-premium-page-header-featured-image-background":"","crio-premium-page-header-background":"","footnotes":""},"class_list":["post-78","page","type-page","status-publish"],"_links":{"self":[{"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/pages\/78","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/comments?post=78"}],"version-history":[{"count":1,"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/pages\/78\/revisions"}],"predecessor-version":[{"id":79,"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/pages\/78\/revisions\/79"}],"wp:attachment":[{"href":"https:\/\/www.mcgovern-fagg.org\/idea\/wp-json\/wp\/v2\/media?parent=78"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}