19
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Emily Law - [email protected] Shan Malhotra - [email protected] 11/01/17 Big Data Task Force @ JPL 1 Big Data Visualization for Planetary Science

Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

  • Upload
    others

  • View
    8

  • Download
    0

Embed Size (px)

Citation preview

Page 1: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Emily Law - [email protected] Malhotra - [email protected]

11/01/17 Big Data Task Force @ JPL 1

Big Data Visualization for Planetary Science

Page 2: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Takeaway

• Big data has many challenges • Opportunity to leverage big data to improve user experiences and

outcome• Interactive Visualization and Analytics are critical• Proven technologies and capabilities of those tools available today, yet

data usability remains a challenge • Path forward

– Increase focus on data usability – Invest and research in these key areas– Work to improve and scale up data usability to meet increasing user expectations– Partner with industries

11/01/17 Big Data Task Force @ JPL 2

Page 3: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Outline

• Solar System Treks Project Overview• What Big Data Challenges Treks face• How Treks Address Big Data Challenges• Treks Features • Demo / Discussion

11/01/17 Big Data Task Force @ JPL 3

Page 4: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Solar System Treks Project Overview

• Sponsored by SMD and HEOMD, Mission (e.g., Cassini)• Development and operations at JPL• An element of NASA’s Solar System Exploration Research Virtual Institute (SSERVI)• A family of web based interactive portals for mission planning, scientific research

and public outreach– Visualization and Analysis tools– Data products from many past and current missions

• Data Access APIs– A variety of user interfaces (e.g., virtual reality goggles)– A variety of external platforms (e.g., Eyes on Solar System, planetariums)

11/01/17 Big Data Task Force @ JPL 4

Page 5: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Operational Treks

• Mars Trek https://marstrek.jpl.nasa.gov

• Moon Trek https://moontrek.jpl.nasa.gov

• Vesta Trek https://vestatrek.jpl.nasa.gov

11/01/17 Big Data Task Force @ JPL 5

Page 6: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Treks In Work

• Titan Trek• Icy Moons Trek • Phobos Trek • Ceres Trek • Comet CG Trek

Page 7: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

What Big Data Challenges Treks face

• Ever increasing (Velocity) Data Volume– Over 3000 data products and > 8 TB data

• Usability of large volume and Variety of data– Discovery (browse, search)

– Provenance, Quality (Veracity)– Download– Sharing, Collaboration

– Value Transformation of Archive Data for Visualization and Analysis

11/01/17 Big Data Task Force @ JPL 7

Page 8: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

How Treks Address Big Data Challenges

• Architecture (Data and System)– Scalability– Extensibility – Reusability– Standardization / Interoperability– FAIR (Findable, Accessible, Interoperable, Reusable)

• Approach – Common Service Oriented Infrastructure– Data Science framework (Visualization and Analysis)– Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL, Deep Learning)

• Applicable to other domains – E.g., Earth Science (Hydrology: Water Trek)

11/01/17 Big Data Task Force @ JPL 8

Page 9: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

• Data products browse, search & download Analysis tools • Lighting, Measurement, Profile, Sun angle, Slope,

Rock/Crater Detection, Hazard, Surface Potential, Subset, Path

• Visualization • Overlay• 3D Flyover• Landing Site features

• Collaboration (sharing)• 3D print • Data

• Past/current missions and various instruments• Various types of data products

• Users• Missions, Lunar scientists, Teachers/Students,

General Public

Treks Features

Page 10: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Variety of User Experiences

Touch Table

WebREST API

Virtual Reality Client

Serving data to Morrison and Hayden planetariums

HyperWall

Page 11: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

11/01/17 Big Data Task Force @ JPL 11

Page 12: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Thank You!

Questions ?

11/01/17 Big Data Task Force @ JPL 12

Page 13: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Backup

11/01/17 Big Data Task Force @ JPL 13

Page 14: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Lighting Analysis

Page 15: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Lighting Analysis

Page 16: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Lighting Analysis

Page 17: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Slope Tool

Page 18: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Slope Tool

Page 19: Big Data Visualization for Planetary Science · – Data Science framework (Visualization and Analysis) – Open Source Big Data Technologies (e.g., Cloud computing, Hadoop, No SQL,

National Aeronautics and Space Administration

Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California

Crater Detection

11/01/17 Big Data Task Force @ JPL 19