{"id":215443,"date":"2016-05-07T00:00:00","date_gmt":"2016-05-07T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/making-sense-of-temporal-queries-with-interactive-visualization-2\/"},"modified":"2018-10-16T22:09:10","modified_gmt":"2018-10-17T05:09:10","slug":"making-sense-of-temporal-queries-with-interactive-visualization-2","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/making-sense-of-temporal-queries-with-interactive-visualization-2\/","title":{"rendered":"Making Sense of Temporal Queries with Interactive Visualization"},"content":{"rendered":"<div class=\"asset-content\">\n<p>As real-time monitoring and analysis become increasingly important, researchers and developers turn to data stream management systems (DSMS\u2019s) for fast, efficient ways to pose temporal queries over their datasets. However, these systems are inherently complex, and even database experts find it difficult to understand the behavior of DSMS queries. To help analysts better understand these temporal queries, we developed StreamTrace, an interactive visualization tool that breaks down how a temporal query processes a given dataset, step-by-step. The design of StreamTrace is based on input from expert DSMS users; we evaluated the system with a lab study of programmers who were new to streaming queries. Results from the study demonstrate that StreamTrace can help users to verify that queries behave as expected and to isolate the regions of a query that may be causing unexpected results.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>As real-time monitoring and analysis become increasingly important, researchers and developers turn to data stream management systems (DSMS\u2019s) for fast, efficient ways to pose temporal queries over their datasets. However, these systems are inherently complex, and even database experts find it difficult to understand the behavior of DSMS queries. To help analysts better understand these [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563,13554],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-215443","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"ACM - Association for Computing Machinery","msr_edition":"Proceedings of the 34th Conference on Human-Computer Interaction (CHI 2016)","msr_affiliation":"","msr_published_date":"2016-05-07","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"264570","msr_publicationurl":"","msr_doi":"10.1145\/2858036.2858408","msr_publication_uploader":[{"type":"file","title":"p5433-battle","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/05\/p5433-battle.pdf","id":264570,"label_id":0},{"type":"doi","title":"10.1145\/2858036.2858408","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Leilani Battle","user_id":0,"rest_url":false},{"type":"user_nicename","value":"danyelf","user_id":31539,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=danyelf"},{"type":"user_nicename","value":"rdeline","user_id":33370,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=rdeline"},{"type":"user_nicename","value":"mbarnett","user_id":32849,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=mbarnett"},{"type":"user_nicename","value":"badrishc","user_id":31166,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=badrishc"},{"type":"user_nicename","value":"jongold","user_id":32389,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=jongold"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[144794,371909,957177],"msr_project":[171204],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":171204,"post_title":"Tempe","post_name":"tempe","post_type":"msr-project","post_date":"2013-09-12 11:45:21","post_modified":"2017-06-19 13:33:13","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/tempe\/","post_excerpt":"Tempe is a web service for exploratory data analysis. 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