Title: Unidatas Common Data Model
1Unidatas Common Data Model
- John Caron
- Unidata/UCAR
- Nov 2006
2Goals / Overview
- Look at the landscape of scientific datasets from
a few thousand feet up. - What semantics are needed to make these useful?
- georeferencing
- specialized subsetting
3Whats a Data Model?
- An Abstract Data Model describes data objects and
what methods you can use on them. - An API is the interface to the Data Model for a
specific programming language - A file format is a way to persist the objects in
the Data Model. - An Abstract Data Model removes the details of any
particular API and the persistence format.
4Common Data Model Layers
Coordinate Systems
Data Access
5Application
Scientific Datatypes
Datatype Adapter
NetCDF-Java version 2.2 architecture
NetcdfDataset
CoordSystem Builder
ADDE
NetcdfFile
I/O service provider
OPeNDAP
NetCDF-3
NIDS
GRIB
NetCDF-4
NcML
HDF5
GINI
Nexrad
DMSP
6NetCDF-4 and Common Data Model (Data Access Layer)
7I/O Service Provider Implementations
- General NetCDF, HDF5, OPeNDAP
- Gridded GRIB-1, GRIB-2
- Radar NEXRAD level 2 and 3, DORADE
- Point BUFR, ASCII
- Satellite DMSP, GINI
- In development
- NOAA GOES (Knapp/Nelson), many others
8Coordinate Systems needed
- NetCDF, OPeNDAP, HDF data models do not have
integrated coordinate systems - so georeferencing not part of API
- Need conventions to specify (eg CF-1, COARDS,
etc) - Contrast GRIB, HDF-EOS, other specialized formats
9NetCDF Coordinate Variables
- dimensions
- lat 64
- lon 128
- variables
- float lat(lat)
- float lon(lon)
- double temperature(lat,lon)
10Coordinate Variables
- One-dimension variable with same name as its
dimension - Strictly monotonic values
- No missing values
- The coordinates of a point (i,j,k) is
- CV1(i), CV2(j), CV3(k)
11Limitations of 1D Coordinate Variables
- Non lat/lon horizontal grids
- float temperature(y,x)
- float lat(y, x)
- float lon(y, x)
- Trajectory data
- float NKoreaRadioactivity(pt)
- float lat(pt)
- float lon(pt)
- float altitude(pt)
- float time(pt)
12General Coordinates in CF-1.0
- float P(y,x)
- Pcoordinates lat lon
- float lat(y, x)
- float lon(y, x)
- float Sr90(pt)
- Sr90coordinates
- lat lon altitude time
13Coordinate Systems (abstract)
- A Coordinate System for a data variable is a set
of Coordinate Variables2 such that the
coordinates of the (i,j,k) data point is - CV1(i,j,k),CV2(i,j,k),CV3(i,j,k),CV4(i,j,k
) - previous was CV1(i), CV2(j), CV3(k)
- The dimensions of each Coordinate Variable must
be a subset of the dimensions of the data
variable.
14Need Coordinate Axis Types
float gridData(t,z,y,x) float time(t) float
y(y) float x(x) float lat(y,x) float
lon(y,x) float height(t,z,y,x)
float radialData(radial, gate) float
distance(gate) float azimuth(radial) float
elevation(radial) float time(radial)
15 The same??
float stationObs(pt) float lat(pt) float
lon(pt) float z(pt) float time(pt)
float trajectory(pt) float lat(pt) float
lon(pt) float z(pt) float time(pt)
16Revised Coordinate Systems
- Specify Coordinate Variables
- Specify Coordinate Types
- (time, lat, lon, projection x, y, height,
pressure, z, radial, azimuth, elevation) - Specify connectivity (implicit or explicit)
between data points - Implicit Neighbors in index space are
(connected) neighbors in coordinate space. Allows
efficient searching.
17Gridded Data
float gridData(t,z,y,x) float time(t) //
Time float y(y) // GeoX float x(x) //
GeoY float z(t,z,y,x) // Height or Pressure
- Cartesian coordinates
- All dimensions are connected
- Connected means
- Neighbors in index space are neighbors in
coordinate space
18Coordinate Systems UML
19Scientific Data Types
- Based on datasets Unidata is familiar with
- APIs are evolving
- How are data points connected?
- Intended to scale to large, multifile collections
- Intended to support specialized queries
- Space, Time
- Corresponding standard NetCDF file conventions
20Gridded Data
- Cartesian coordinates
- All dimensions are connected
- x, y, z, time
- recently added runtime and ensemble
- refactored into GridDatatype interface
float gridData(t,z,y,x) float time(t) float
y(y) float x(x) float lat(y,x) float
lon(y,x) float height(t,z,y,x)
21GridDatatype methods
- CoordinateAxis getTaxis()
- CoordinateAxis getXaxis()
- CoordinateAxis getYaxis()
- CoordinateAxis getZaxis()
- Projection getProjection()
- int findXYindexFromCoord( double x_coord,
double y_coord) - LatLonRect getLatLonBoundingBox()
- Array getDataSlice (Range )
- GridDatatype makeSubset (Range )
22Radial Data
- Polar coordinates
- All dimensions are connected
- Not separate time dimension
radialData(radial, gate) distance(gate)
azimuth(radial) elevation(radial) time(radial)
23Swath
- lat/lon coordinates
- not separate time dimension
- all dimensions are connected
swathData(line,cell) lat(line,cell)
lon(line,cell) time(line) z(line,cell) ??
24Point Observation Data
- Set of measurements at the same point in space
and time - Point dimension not connected
float obs1(pt) float obs2(pt) float lat(pt)
float lon(pt) float z(pt) float time(pt)
Structure lat, lon, z, time v1, v2,
... obs( pt)
25PointObsDataset Methods
- // IteratorltStructureDatagt
- Iterator getData(
- LatLonRect boundingBox,
- Date start, Date end)
26Time series Station Data
Structure name lat, lon, z
Structure time v1, v2, ...
obs() // connected stn(stn) // not connected
27StationObs Methods
- // ListltStationgt
- List getStations(
- LatLonRect boundingBox)
- // IteratorltStructureDatagt
- Iterator getData(
- Station s,
- Date start, Date end)
28Trajectory Data
- pt dimension is connected
- Collection dimension not connected
Structure lat, lon, z, time v1, v2, ...
obs(pt) // connected
Structure name Structure lat,
lon, z, time v1, v2, ... obs() //
connected traj(traj) // not connected
29Profiler/Sounding Station Data
Structure name lat, lon, time
Structure z v1, v2, ...
obs() // connected loc(nloc) // not
connected
Structure name lat, lon Structure
time, Structure z
v1, v2, ... obs() // connected
time() // connected stn(stn) // not
connected
30Unstructured Grid
- Pt dimension not connected
- Looks the same as point data
- Need to specify the connectivity explicitly
float unstructGrid(t,z,pt) float lat(pt)
float lon(pt) float time(t) float height(z)
31Data Types Summary
- Data access through a standard API
- Convenient georeferencing
- Specialized subsetting methods
- Efficiency for large datasets
32Payoff N M instead of N M things on your TODO
List!
File Format 1
Visualization Analysis
NetCDF file
File Format 2
OpenDAP Server
File Format N
WCS Service
Web Service
33THREDDS Data Server
HTTP Tomcat Server
Catalog.xml
Application
THREDDS Server
NetCDF-Java library
hostname.edu
Datasets
IDD Data
34Next DataType Aggregation
- Work at the CDM DataType level, know (some) data
semantics - Forecast Model Collection
- Combine multiple model forecasts into single
dataset with two time dimensions - With NOAA/IOOS (Steve Hankin)
- Point/Station/Trajectory/Profile Data
- Allow space/time queries, return nested sequences
- Start from / standardize Dapper conventions
35Forecast Model Collections
36Conclusion
- Standardized Data Access in good shape
- HDF5, NetCDF, OPeNDAP
- Write an IOSP for proprietary formats (Java)
- But thats not good enough!
- To do
- Standard representations of coordinate systems
- Classifications of data types, standard services
for them