Journal article Open Access

An Algebra for Spatiotemporal Data: From Observations to Events

Ferreira, Karine; Camara, Gilberto; Monteiro, Miguel


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{
  "DOI": "10.1111/tgis.12030", 
  "container_title": "Transactions in GIS", 
  "title": "An Algebra for Spatiotemporal Data: From Observations to Events", 
  "issued": {
    "date-parts": [
      [
        2013, 
        5, 
        22
      ]
    ]
  }, 
  "abstract": "<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&nbsp;<em>objects</em>&nbsp;and&nbsp;<em>fields</em>&nbsp;evolve over time. However, to properly capture changes, it is also necessary to describe&nbsp;<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:&nbsp;<em>time series</em>,&nbsp;<em>trajectory</em>&nbsp;and&nbsp;<em>coverage</em>. Based on these abstractions, it defines&nbsp;<em>object</em>&nbsp;and&nbsp;<em>event</em>&nbsp;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>", 
  "author": [
    {
      "family": "Ferreira, Karine"
    }, 
    {
      "family": "Camara, Gilberto"
    }, 
    {
      "family": "Monteiro, Miguel"
    }
  ], 
  "page": "253-269", 
  "volume": "18", 
  "type": "article-journal", 
  "id": "3832891"
}
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