22
JL2-SESIP-0717 Data Are from Mars, Tools Are from Venus H. Joe Lee ([email protected]) The HDF Group This work was supported by NASA/GSFC under Raytheon Co. contract number NNG15HZ39C All images used in this presentation are from autodraw.com for public use.

Data Are from Mars, Tools Are from Venus

Embed Size (px)

Citation preview

Page 1: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

Data Are from Mars,

Tools Are from Venus

H. Joe Lee ([email protected])

The HDF Group

This work was supported by NASA/GSFC under

Raytheon Co. contract number NNG15HZ39C

All images used in this presentation are from

autodraw.com for public use.

Page 2: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

2

No “Earth” in title?

“Men Are from Mars, Women are from Venus”

- John Gray

Page 3: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

3

Are data from Mars?

Why can’t I use Earth tools?Correct geo-referencing

Page 4: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

4

Are tools from Venus?

Why can’t I open Earth data?

Page 5: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

5

Data Producers from Mars

• I want my data slim and efficient.

• How can I save money in managing data?

Tool Developers from Venus• I make my tool work for popular data first.

• Can I make money by supporting your data?

Page 6: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

6

Result: Frustrated Users

Page 7: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

7

We (HDFEOS.org) can help.

Page 8: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

8

• Hierarchical Data Format (HDF)

• Network Common Data Format (netCDF)

• Geospatial Tagged Image File Format

(GeoTIFF)

• Keyhole Markup Language (KML) /

zipped KML (KMZ)

• Comma-separated values (CSV)

• etc.

We identify gaps in File Formats

Page 9: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

9

• hdf

• netcdf-C

• netcdf-Java

• HDF – Earth Observing System (hdf-eos)

• Climate and Forecast Metadata (CF) conventions

• Geospatial Data Abstraction Library (GDAL)

• etc.

We identify gaps in Libraries

Page 10: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

10

• Microsoft Excel

• Esri ArcGIS

• Google Earth

• MATLAB

• Python

• Interactive Data Language (IDL)

• Panoply

• Integrated Data Viewer (IDV)

• HDFView

• h5dump

• Etc.

We identify gaps in Tools

Page 11: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

11

• Open-source Project for a Network Data

Access Protocol (OPeNDAP)

• Web Map Service (WMS)

• Web Map Tile Service (WMTS)

• Web Coverage Service (WCS)

• etc.

We identify gaps in Services

Page 12: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

12

• File conversion

• Libraries and tools usage

• NASA HDF product specific examples

• Demo services (e.g., Hyrax*, THREDDS**)

AND we provide Solutions…

*Hyrax is the data server from OPeNDAP.

**Thematic Real-time Environmental Distributed Data Services

Page 13: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

13

• Make HDF5 data work with

– GDAL

– netCDF

– Hyrax/THREDDS

• Don’t forget a few key CF conventions.

• Follow DIWG* recommendations.

Suggestions for data producers

*Data Interoperability Working Group

Page 14: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

14

• Download and test NASA HDF products.

• Support them natively.

• Support augmentation.

– VRT* in GDAL

– NcML** in netCDF

• Support 3D visualization for data in the air.

Suggestions for tool developers

*Virtual Dataset in XML format

**netCDF Markup Language

Page 15: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

15

3D Visualization

Page 16: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

16

• Try OPeNDAP first. CSV may be enough.

• Try netCDF conversion / augmentation.

• Correct metadata with NcML / VRT.

• Try GEE* instead of GDAL.

• Use CMR** wisely.

Suggestions for end-users

*GDAL Enhancement for ESDIS project

** Core Metadata Repository

Page 17: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

17

• Hadoop / Spark (streaming) / Dask

• Parquet / Arrow

• Elastic Search / Kibana

How about Big (fast) data?

Page 18: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

18

Streaming Swath

Hadoop + Spark Streaming + Elasticsearch & Kibana

S3 + AWS Lambda + Elasticsearch & Kibana

Page 19: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

19

• scikit-learn / keras / h2o.ai

• Please contact us at

[email protected] if you’d like to see

examples on machine learning.

Future: (Deep) Machine Learning?

Page 20: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

20

Deep Learning: Amazon

Rekognition

Page 21: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

21

Alexa, what does MODIS see now?

Alexa: I can recognize “Alps.”

Page 22: Data Are from Mars, Tools Are from Venus

JL2-SESIP-0717

22

This work was supported by

NASA/GSFC under Raytheon Co.

contract number NNG15HZ39C