{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/130689"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/130689","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Database updates using interactive Pan and Zoom visualizations","abstract":"As datasets continue to get larger, there is a great need for visualization systems that scale well while maintaining interactivity. Kyrix [1] is a system that helps developers create scalable pan and zoom visualizations. It combines visualization paradigms for good performance like data tiling and prefetching with a database backend that creates spatial indexes for faster querying. This thesis modifies Kyrix to support direct manipulation of datasets through a data visualization. We add bindings to the Kyrix specification that allow the developer to enable updates in a visualization. The user can then interact with the visualization and update the data in order to test a hypotheses, add new data, or fix a data error. We showcase this functionality by implementing three different types of Kyrix visualizations: an NBA timeline visualization, an election forecasting visualization, and a scatter plot visualization of NBA game scores. We report the update performance statistics for each of the demo visualizations and provide an evaluation of changes to the Kyrix specification language.","abstract_html":"As datasets continue to get larger, there is a great need for visualization systems that scale well while maintaining interactivity. Kyrix [1] is a system that helps developers create scalable pan and zoom visualizations. It combines visualization paradigms for good performance like data tiling and prefetching with a database backend that creates spatial indexes for faster querying. This thesis modifies Kyrix to support direct manipulation of datasets through a data visualization. We add bindings to the Kyrix specification that allow the developer to enable updates in a visualization. The user can then interact with the visualization and update the data in order to test a hypotheses, add new data, or fix a data error. We showcase this functionality by implementing three different types of Kyrix visualizations: an NBA timeline visualization, an election forecasting visualization, and a scatter plot visualization of NBA game scores. We report the update performance statistics for each of the demo visualizations and provide an evaluation of changes to the Kyrix specification language.","abstract_has_math":false,"creators":["Griggs, Peter,M. Eng.(Peter A.)Massachusetts Institute of Technology."],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Michael Stonebraker."],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021","date_published":"2021","updated_at":"2026-07-22T22:21:21Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses may be protected by copyright. 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Kyrix [1] is a system that helps developers create scalable pan and zoom visualizations. It combines visualization paradigms for good performance like data tiling and prefetching with a database backend that creates spatial indexes for faster querying. This thesis modifies Kyrix to support direct manipulation of datasets through a data visualization. We add bindings to the Kyrix specification that allow the developer to enable updates in a visualization. The user can then interact with the visualization and update the data in order to test a hypotheses, add new data, or fix a data error. We showcase this functionality by implementing three different types of Kyrix visualizations: an NBA timeline visualization, an election forecasting visualization, and a scatter plot visualization of NBA game scores. We report the update performance statistics for each of the demo visualizations and provide an evaluation of changes to the Kyrix specification language."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M. Eng."]},{"key":"dc:title","label":"Title","values":["Database updates using interactive Pan and Zoom visualizations"]}]}],"canonical_facts":{"dc:contributor.advisor":["Michael Stonebraker."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","EECS"],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:creator":["Griggs, Peter,M. Eng.(Peter A.)Massachusetts Institute of Technology."],"dc:date.accessioned":["2021-05-24T19:52:02Z"],"dc:date.available":["2021-05-24T19:52:02Z"],"dc:date.issued":["2021"],"dc:description":["Thesis: M. 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We showcase this functionality by implementing three different types of Kyrix visualizations: an NBA timeline visualization, an election forecasting visualization, and a scatter plot visualization of NBA game scores. We report the update performance statistics for each of the demo visualizations and provide an evaluation of changes to the Kyrix specification language."],"dc:description.degree":["M. Eng."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/130689"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses may be protected by copyright. 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