Journal article Open Access
Ferreira, Karine;
Camara, Gilberto;
Monteiro, Miguel
{ "description": "<p>Recent technological advances in geospatial data gathering have created massive data sets with better spatial and temporal resolution than ever before. These large spatiotemporal data sets have motivated a challenge for Geoinformatics: how to model changes and design good quality software. Many existing spatiotemporal data models represent how <em>objects</em> and <em>fields</em> evolve over time. However, to properly capture changes, it is also necessary to describe <em>events</em>. As a contribution to this research, this article presents an algebra for spatiotemporal data. Algebras give formal specifications at a high\u2010level abstraction, independently of programming languages. This helps to develop reliable and expressive applications. Our algebra specifies three data types as generic abstractions built on real\u2010world observations: <em>time series</em>, <em>trajectory</em> and <em>coverage</em>. Based on these abstractions, it defines <em>object</em> and <em>event</em> types. The proposed data types and functions can model and capture changes in a large range of applications, including location\u2010based services, environmental monitoring, public health, and natural disasters.</p>", "license": "https://creativecommons.org/licenses/by/4.0/legalcode", "creator": [ { "affiliation": "INPE (National Institute for Space Research), Brazil", "@id": "https://orcid.org/0000-0003-2656-5504", "@type": "Person", "name": "Ferreira, Karine" }, { "affiliation": "INPE (National Institute for Space Research), Brazil", "@id": "https://orcid.org/0000-0002-3681-487X", "@type": "Person", "name": "Camara, Gilberto" }, { "affiliation": "INPE (National Institute for Space Research), Brazil", "@type": "Person", "name": "Monteiro, Miguel" } ], "headline": "An Algebra for Spatiotemporal Data: From Observations to Events", "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", "datePublished": "2013-05-22", "url": "https://zenodo.org/record/3832891", "keywords": [ "Spatio-temporal data, GIS, abstract data type, observations, events" ], "@context": "https://schema.org/", "identifier": "https://doi.org/10.1111/tgis.12030", "@id": "https://doi.org/10.1111/tgis.12030", "@type": "ScholarlyArticle", "name": "An Algebra for Spatiotemporal Data: From Observations to Events" }
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