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UID:pretalx-foss4g-2024-NKBU8E@talks.staging.osgeo.org
DTSTART;TZID=-03:20241204T150000
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DESCRIPTION:FAIR principles are a set of best practices aimed at making dat
 a findable\, accessible\, interoperable\, and reusable to both humans and 
 machines. The growth of spatial data infrastructures and discovery catalog
 s (aka ‘geoportals’) have highlighted the importance of geospatial dat
 a management\, metadata\, and systems architecture. These data are invalua
 ble to public\, private\, and academic sectors for use in decision-making\
 , policy development\, research\, as well as subsequent data production. H
 owever\, the costs and overall effort associated with the curation of data
  throughout their lifecycle can be substantial. The Stanford Spatial Data 
 Infrastructure implements FAIR principles to its collections of geospatial
  data in order to better meet the needs of its researchers and worldwide u
 ser community. These principles are applied to data\, metadata\, and infra
 structure\, and serve as a guide for collecting\, organizing\, and managin
 g data that are produced through research endeavors\, published by public 
 entities for open consumption\, or created by vendors for commercial purpo
 ses.\n\nIn this presentation\, the design and implementation of a geospati
 al data curation strategy utilizing FAIR principles will be described. Add
 itionally. we will discuss our efforts around automation in data wrangling
  and metadata\, as well as access\, licensing\, and digital preservation.
DTSTAMP:20260504T204149Z
LOCATION:Room IV
SUMMARY:FAIR Principles for Geospatial Data Curation - Kim Durante
URL:https://talks.staging.osgeo.org/foss4g-2024/talk/NKBU8E/
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