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Contenido proporcionado por MapScaping. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente MapScaping o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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Hub Ocean

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Manage episode 373149855 series 2502116
Contenido proporcionado por MapScaping. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente MapScaping o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

This is an interview with a senior data scientist from Hub Ocean, a platform that aims to unlock and unite ocean data.

Hub Ocean - as the name suggests is a hub for ocean data

Now we have talked about these kinds of data hubs before on the podcast - Sentinal Hub - a data hub for earth observation data, Microsoft Planetary Computer, Google Earth Engine, Open Topography is data but for topography data …. The concept is not new but also not easy to implement and if they work, these types of data hubs have a gravity to them that becomes more powerful over time.

One of the guiding concepts behind these data hubs seems to be the idea of FAIR data - Findable, Accessible, Interoperable, and Reuseable data

…. But its not enough to ensure that the data is fair I think we should also consider how we can make the results of our research Findable, Accessible, Interoperable, and Reuseable data

If you are not already familiar with Cloud Optimised Geospatial formats it is worth checking out these two episodes.

https://mapscaping.com/podcast/cloud-optimized-point-clouds/

https://mapscaping.com/podcast/cloud-native-geospatial/

Some more episodes you might enjoy

ESRI, GIS careers, Geospatial Data Science

QGIS, Geospatial Python, ArcGIS Pro

Google Maps, Geomatics, Cartography

Location Intelligence, Mapping

  continue reading

237 episodios

Artwork
iconCompartir
 
Manage episode 373149855 series 2502116
Contenido proporcionado por MapScaping. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente MapScaping o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

This is an interview with a senior data scientist from Hub Ocean, a platform that aims to unlock and unite ocean data.

Hub Ocean - as the name suggests is a hub for ocean data

Now we have talked about these kinds of data hubs before on the podcast - Sentinal Hub - a data hub for earth observation data, Microsoft Planetary Computer, Google Earth Engine, Open Topography is data but for topography data …. The concept is not new but also not easy to implement and if they work, these types of data hubs have a gravity to them that becomes more powerful over time.

One of the guiding concepts behind these data hubs seems to be the idea of FAIR data - Findable, Accessible, Interoperable, and Reuseable data

…. But its not enough to ensure that the data is fair I think we should also consider how we can make the results of our research Findable, Accessible, Interoperable, and Reuseable data

If you are not already familiar with Cloud Optimised Geospatial formats it is worth checking out these two episodes.

https://mapscaping.com/podcast/cloud-optimized-point-clouds/

https://mapscaping.com/podcast/cloud-native-geospatial/

Some more episodes you might enjoy

ESRI, GIS careers, Geospatial Data Science

QGIS, Geospatial Python, ArcGIS Pro

Google Maps, Geomatics, Cartography

Location Intelligence, Mapping

  continue reading

237 episodios

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