Benno Blumenthal International Research Institute for Climate Prediction Columbia University. Data Interoperability at the IRI: translating between data cultures. Work presented has been done by. John del Corral Michael Bell Emily Grover-Kopec. Outline. Data Cultures
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International Research Institute for Climate Prediction
Columbia UniversityData Interoperability at the IRI: translating between data cultures
“geolocated by lat/lon”
vector object or
GRIB grid codes
Metadata standards are useful because they let us make meaningful connections between datasets.
Difficult to document dataset – currently at IRI user has to follow a series of links to find out about districts and related information
Would be nice if
Latter are local but solid; former are standard and possibly hazy
Given a dataset following one metadata standard, how do we make connections to datasets following a different standard?
Example: climate division outlines associated with climate division data are conceptually
Where location is a geometry (multipolygon)
This becomes nested sequences in OpenDAP
with some attributes
Point, LineString, Polygon, MultiPoint, MultiLineString,MultiPolygon,GeometryCollection
NDVI [ x y time]