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We create unique unit visualization with the customizable aggregated view based on the visual metaphor of flower bursts. Each visualization unit is encoded with the abstraction of spatiotemporal properties. To reduce user cognition load, UcVE allows users to visualize, save, and track in-the-process exploration results. In coordination of storage sequence and block tracking views, UcVE can facilitate comparison with multiple visualization units concurrently, selected from historical and current exploration results. UcVE offers a flexible geo-based layout, with aggregation functions and temporal views of the timeline with categorized events, to maximize the user\u2019s exploration capabilities. Finally, we demonstrate the usefulness by using COVID-19 datasets, case studies with different user scenarios, and expert feedback.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Graphical abstract<\/jats:title>\n                \n              <\/jats:sec>","DOI":"10.1007\/s12650-022-00882-3","type":"journal-article","created":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T14:02:49Z","timestamp":1668002569000},"page":"403-421","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["User-centered visual explorer of in-process comparison in spatiotemporal space"],"prefix":"10.1007","volume":"26","author":[{"given":"Dong","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oppermann","family":"Ian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Jie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Xiaoru","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nguyen Quang","family":"Vinh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,11,9]]},"reference":[{"key":"882_CR1","doi-asserted-by":"crossref","unstructured":"Afzal S, Ghani S, Jenkins-Smith HC, Ebert DS, Hadwiger M, Hoteit I (2020) A visual analytics based decision making environment for covid-19 modeling and visualization. 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