Big Data Visualization for Planetary Science
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1 Big Data Visualization for Planetary Science Emily Law - emily.s.law@jpl.nasa.gov Shan Malhotra - shan.malhotra@jpl.nasa.gov 11/01/17 Big Data Task JPL 1
2 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 JPL 2
3 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 JPL 3
4 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 JPL 4
5 Operational Treks Mars Trek Moon Trek Vesta Trek 11/01/17 Big Data Task JPL 5
6 Treks In Work Titan Trek Icy Moons Trek Phobos Trek Ceres Trek Comet CG Trek
7 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 JPL 7
8 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 JPL 8
9 Treks Features 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
10 Variety of User Experiences Virtual Reality Client Web REST API HyperWall Touch Table Serving data to Morrison and Hayden planetariums
11 11/01/17 Big Data Task JPL 11
12 Thank You! Questions? 11/01/17 Big Data Task JPL 12
13 Backup 11/01/17 Big Data Task JPL 13
14 Lighting Analysis
15 Lighting Analysis
16 Lighting Analysis
17 Slope Tool
18 National Aeronautics and Slope Tool
19 Crater Detection 11/01/17 Big Data Task JPL 19
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