Journal article Open Access

An Algebra for Spatiotemporal Data: From Observations to Events

Ferreira, Karine; Camara, Gilberto; Monteiro, Miguel

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    <subfield code="a">Spatio-temporal data, GIS, abstract data type, observations, events</subfield>
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    <subfield code="a">Camara, Gilberto</subfield>
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    <subfield code="a">An Algebra for Spatiotemporal Data: From Observations to Events</subfield>
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    <subfield code="a">&lt;p&gt;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&amp;nbsp;&lt;em&gt;objects&lt;/em&gt;&amp;nbsp;and&amp;nbsp;&lt;em&gt;fields&lt;/em&gt;&amp;nbsp;evolve over time. However, to properly capture changes, it is also necessary to describe&amp;nbsp;&lt;em&gt;events&lt;/em&gt;. As a contribution to this research, this article presents an algebra for spatiotemporal data. Algebras give formal specifications at a high‐level 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‐world observations:&amp;nbsp;&lt;em&gt;time series&lt;/em&gt;,&amp;nbsp;&lt;em&gt;trajectory&lt;/em&gt;&amp;nbsp;and&amp;nbsp;&lt;em&gt;coverage&lt;/em&gt;. Based on these abstractions, it defines&amp;nbsp;&lt;em&gt;object&lt;/em&gt;&amp;nbsp;and&amp;nbsp;&lt;em&gt;event&lt;/em&gt;&amp;nbsp;types. The proposed data types and functions can model and capture changes in a large range of applications, including location‐based services, environmental monitoring, public health, and natural disasters.&lt;/p&gt;</subfield>
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    <subfield code="a">10.1111/tgis.12030</subfield>
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