{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:53:53Z","timestamp":1760234033180,"version":"build-2065373602"},"reference-count":110,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,3,22]],"date-time":"2021-03-22T00:00:00Z","timestamp":1616371200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008247","name":"University of Otago","doi-asserted-by":"publisher","award":["Doctoral Scholarship"],"award-info":[{"award-number":["Doctoral Scholarship"]}],"id":[{"id":"10.13039\/100008247","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Current spatiotemporal data has facilitated movement studies to shift objectives from descriptive models to explanations of the underlying causes of movement. From both a practical and theoretical standpoint, progress in developing approaches for these explanations should be founded on a conceptual model. This paper presents such a model in which three conceptual levels of abstraction are proposed to frame an agent-based representation of movement decision-making processes: \u2018attribute,\u2019 \u2018actor,\u2019 and \u2018autonomous agent\u2019. These in combination with three temporal, spatial, and spatiotemporal general forms of observations distinguish nine (3 \u00d7 3) representation typologies of movement data within the agent framework. Thirdly, there are three levels of cognitive reasoning: \u2018association,\u2019 \u2018intervention,\u2019 and \u2018counterfactual\u2019. This makes for 27 possible types of operation embedded in a conceptual cube with the level of abstraction, type of observation, and degree of cognitive reasoning forming the three axes. The conceptual model is an arena where movement queries and the statement of relevant objectives takes place. An example implementation of a tightly constrained spatiotemporal scenario to ground the agent-structure was summarised. The platform has been well-defined so as to accommodate different tools and techniques to drive causal inference in computational movement analysis as an immediate future step.<\/jats:p>","DOI":"10.3390\/ijgi10030190","type":"journal-article","created":{"date-parts":[[2021,3,22]],"date-time":"2021-03-22T11:13:26Z","timestamp":1616411606000},"page":"190","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Beyond Objects in Space-Time: Towards a Movement Analysis Framework with \u2018How\u2019 and \u2018Why\u2019 Elements"],"prefix":"10.3390","volume":"10","author":[{"given":"Saeed","family":"Rahimi","sequence":"first","affiliation":[{"name":"School of Surveying, University of Otago, Dunedin 9016, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7738-2308","authenticated-orcid":false,"given":"Antoni B.","family":"Moore","sequence":"additional","affiliation":[{"name":"School of Surveying, University of Otago, Dunedin 9016, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter A.","family":"Whigham","sequence":"additional","affiliation":[{"name":"Department of Information Science, University of Otago, Dunedin 9016, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,22]]},"reference":[{"key":"ref_1","unstructured":"Harvey, D. 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