, Key Components of a Successful Earth Science Subsetter Architecture ASDC Introduction The Atmospheric Science Data Center (ASDC) at NASA Langley Research.

Slides:



Advertisements
Similar presentations
ESA Data Integration Application Open Grid Services for Earth Observation Luigi Fusco, Pedro Gonçalves.
Advertisements

1 NASA CEOP Status & Demo CEOS WGISS-25 Sanya, China February 27, 2008 Yonsook Enloe.
Future Directions and Initiatives in the Use of Remote Sensing for Water Quality.
University of Chicago Department of Energy The Parallel and Grid I/O Perspective MPI, MPI-IO, NetCDF, and HDF5 are in common use Multi TB datasets also.
Interoperable Data Systems for Satellite, Airborne and Terrestrial LiDAR Data C. Meertens and J. McWhirter, UNAVCO S-J. S.Khalsa and T. Haran, NSIDC/CU.
Mike Smorul Saurabh Channan Digital Preservation and Archiving at the Institute for Advanced Computer Studies University of Maryland, College Park.
Data Grid: GRASP Mike Smorul. Grid Retrieval and Search Platform Based on concepts developed in the Earth Science Data Interface (ESDI) developed at the.
CEOS System Engineering Toolset (CSET) CSET is a Software Framework + Suite of Tools (Apps) that leverages a Common Architecture, Unified Data Model, Common.
Development of Japanese GIS Tool for use in the Humanities ○ Masatoshi ISHIKAWA †, Yoichi KAWANISHI ††, Hidefumi OKUMURA †††, Shoichiro HARA †††† † University.
Operational Dataset Update Functionality Included in the NCAR Research Data Archive Management System 1 Zaihua Ji Doug Schuster Steven Worley Computational.
Internet GIS. A vast network connecting computers throughout the world Computers on the Internet are physically connected Computers on the Internet use.
Information Technology for Ocean Observations and Climate Research TYKKI Workshop, December 9-11, 1998, Tokyo, Japan Nancy N. Soreide NOAA Pacific Marine.
World Renewable Energy Forum May 15-17, 2012 Dr. James Hall.
MODIS Atmosphere Team Webinar Series #12: Resources for Finding and Using MODIS Products 1 Richard Kleidman (SSAI/613) and Lots and lots and lots of other.
Unidata TDS Workshop THREDDS Data Server Overview October 2014.
Introduction Downloading and sifting through large volumes of data stored in differing formats can be a time-consuming and sometimes frustrating process.
Obtaining MISR Data and Information Jeff Walter Atmospheric Science Data Center April 17, 2009.
EU 2nd Year Review – Jan – WP9 WP9 Earth Observation Applications Demonstration Pedro Goncalves :
Metr 415/715 Monday May Today’s Agenda 1.Basics of LIDAR - Ground based LIDAR (pointing up) - Air borne LIDAR (pointing down) - Space borne LIDAR.
Geospatial Data Abstraction Library (GDAL) Enhancement for ESDIS (GEE) Increasing Accessibility and Interoperability of NASA Data Products with GIS Tools.
, Data for Disaster Planning, Response, Management and Awareness ASDC Introduction The Atmospheric Science Data Center (ASDC) at NASA Langley Research.
Data Merge Examples, Toolsets for Airborne Data (TAD): Customized Data Merging Function ASDC Introduction The Atmospheric Science Data Center (ASDC) at.
, Increasing Discoverability and Accessibility of NASA Atmospheric Science Data Center (ASDC) Data Products with GIS Technology ASDC Introduction The Atmospheric.
, Implementing GIS for Expanded Data Accessibility and Discoverability ASDC Introduction The Atmospheric Science Data Center (ASDC) at NASA Langley Research.
Updates from EOSDIS -- as they relate to LANCE Kevin Murphy LANCE UWG, 23rd September
Leveraging research and future funding opportunities Hajo Eicken Geophysical Institute & International Arctic Research Center University of Alaska Fairbanks.
Unidata TDS Workshop TDS Overview – Part I XX-XX October 2014.
material assembled from the web pages at
Ohio State University Department of Computer Science and Engineering 1 Cyberinfrastructure for Coastal Forecasting and Change Analysis Gagan Agrawal Hakan.
Planning for Arctic GIS and Geographic Information Infrastructure Sponsored by the Arctic Research Support and Logistics Program 30 October 2003 Seattle,
Introduction to Apache OODT Yang Li Mar 9, What is OODT Object Oriented Data Technology Science data management Archiving Systems that span scientific.
ATMOSPHERIC SCIENCE DATA CENTER ‘Best’ Practices for Aggregating Subset Results from Archived Datasets Walter E. Baskin 1, Jennifer Perez 2 (1) Science.
Integrated Model Data Management S.Hankin ESMF July ‘04 Integrated data management in the ESMF (ESME) Steve Hankin (NOAA/PMEL & IOOS/DMAC) ESMF Team meeting.
1 1 ECHO Overview and Status Enabling Interoperability with NASA Earth Science Data and Services GES DISC User Working Group May 10, 2011 Andrew E. Mitchell.
Integrated Grid workflow for mesoscale weather modeling and visualization Zhizhin, M., A. Polyakov, D. Medvedev, A. Poyda, S. Berezin Space Research Institute.
Transitioning Low Earth Orbit Satellite Archive Data from Informix (Geodetic DataBlade) to PostgreSQL (PostGIS) Churngwei Chu [
Cloud Computing for the NASA Atmospheric Sciences Data Center with Amazon Web Services Cloud Computing for the NASA Atmospheric Sciences Data Center with.
Unidata TDS Workshop THREDDS Data Server Overview
1 NASA CEOP Status & Demo CEOS WGISS-24 Oberpfaffenhofen, Germany October 15, 2007 Yonsook Enloe.
ESIP Federation 2004 : L.B.Pham S. Berrick, L. Pham, G. Leptoukh, Z. Liu, H. Rui, S. Shen, W. Teng, T. Zhu NASA Goddard Earth Sciences (GES) Data & Information.
NA-MIC National Alliance for Medical Image Computing UCSD: Engineering Core 2 Portal and Grid Infrastructure.
View_hdf Kam-Pui Lee Science Applications International Corporation CERES Data Management Team Linda Hunt Computer Sciences Corporation Atmospheric Sciences.
GO-ESSP Workshop, LLNL, Livermore, CA, Jun 19-21, 2006, Center for ATmosphere sciences and Earthquake Researches Construction of e-science Environment.
NetCDF file generated from ASDC CERES SSF Subsetter ATMOSPHERIC SCIENCE DATA CENTER Conversion of Archived HDF Satellite Level 2 Swath Data Products to.
User Working Group 2013 Data Access Mechanisms – Status 12 March 2013
Jianchun Qin, Liguang Wu, Michael Theobald, A. K. Sharma, George Serafino, Sunmi Cho, Carrie Phelps NASA Goddard Space Flight Center, Code 902 Greenbelt,
ITSC/University of Alabama in Huntsville ADaM System Architecture Rahul Ramachandran, Sara Graves and Ken Keiser Mathematical Challenges in Scientific.
Obtaining MISR Data and Information Nancy Ritchey Atmospheric Science Data Center March 20, 2006.
NOAAServer: Unified access to distributed NOAA data Ernest Daddio, NOAA/ESDIM Steve Hankin, NOAA/PMEL Donald Denbo, NOAA/PMEL/JISAO Nancy Soreide, NOAA/PMEL.
Federated Space-Time Query for Earth Science Data Using OpenSearch Conventions ESIP Federated Search Cluster Chris Lynnes Bruce Beaumont Ruth Duerr Hook.
Fire Emissions Network Sept. 4, 2002 A white paper for the development of a NSF Digital Government Program proposal Stefan Falke Washington University.
1 CALIPSO Search and Sub-setting Website Quick Tutorial.
More Information Working Group Composition End Users Data Modelers Data Analysts Airborne Measurement Scientists Airborne Instrument Scientists Data Management.
AIRS/AMSU-A/HSB Data Subsetting and Visualization Services at GES DAAC Sunmi Cho, Jason Li, Donglian Sun, Jianchun Qin and Carrie Phelps, Code 902, NASA.
The Earth Information Exchange. Portal Structure Portal Functions/Capabilities Portal Content ESIP Portal and Geospatial One-Stop ESIP Portal and NOAA.
From Missions to Measurements: an Ocean Discipline Experience.
1 2.5 DISTRIBUTED DATA INTEGRATION WTF-CEOP (WGISS Test Facility for CEOP) May 2007 Yonsook Enloe (NASA/SGT) Chris Lynnes (NASA)
ECHO Technical Interchange Meeting 2013 Timothy Goff 1 Raytheon EED Program | ECHO Technical Interchange 2013.
Origami: Scientific Distributed Workflow in McIDAS-V Maciek Smuga-Otto, Bruce Flynn (also Bob Knuteson, Ray Garcia) SSEC.
Simulation Production System Science Advisory Committee Meeting UW-Madison March 1 st -2 nd 2007 Juan Carlos Díaz Vélez.
Physical Oceanography Distributed Active Archive Center THUANG June 9-13, 20089th GHRSST-PP Science Team Meeting GHRSST GDAC and EOSDIS PO.DAAC.
DataGrid France 12 Feb – WP9 – n° 1 WP9 Earth Observation Applications.
Sea Surface Temperature Distribution from the Physical Oceanography DAAC Ed Armstrong JPL PO.DAAC MODIS Science Team Meeting.
Making Satellite Datasets Accessible for Everyone A look into my NASA Internship – summer 2015 Aaron Scott University of North Dakota.
MERRA Data Access and Services
Design and Manufacturing in a Distributed Computer Environment
CERES Data Management Team Science Data Processing Workshop 2002
SDM workshop Strawman report History and Progress and Goal.
Operational Dataset Update Functionality Included in the NCAR Research Data Archive Management System Zaihua Ji Doug Schuster Steven Worley Computational.
Presentation transcript:

, Key Components of a Successful Earth Science Subsetter Architecture ASDC Introduction The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. The ASDC specializes in atmospheric data that is important to understanding the causes and processes of global climate change and the consequences of human activities on the climate. The ASDC currently supports more than 44 projects and has over 1,700 archived data sets, which increase daily. ASDC customers include scientists, researchers, federal, state, and local governments, academia, industry, and application users, the remote sensing community, and the general public. JAVA HDF Subsetter Strategy & Innovation Search and Subsetter Application Interface & Framwork Jennifer Perez, Walter Baskin, & Peter Piatko NASA Langley Research Center, Hampton, VA Goal #4 The ASDC will continue to foster innovation by actively assessing emerging technologies and their applicability to existing and projected customer needs and requirements in order to mitigate gaps in capability Conclusion Key Components Since the unveiling of a new CALIPSO Search and Subset Application at the 2010 A-Train Symposium by the Atmospheric Science Data Center (ASDC) and CALIPSO science team, Atmospheric Scientists have responded enthusiastically. Congruent to this goal, the template of this subsetter application architecture has since been applied to the distribution of Level 2 Satellite data granules from Clouds and the Earth's Radiant Energy System (CERES) SSF swath datasets and Tropospheric Emission Spectrometer (TES) datasets. This permits science data users to employ new tools to rapidly locate, subset, and order specific dataset parameters tailored to their requirements. The 2013 ASDC Strategic Plan serves as a mission-focused plan with six defined goals, each with supporting objectives and tasks for implementation that emphasize the vision and support the mission and values of the ASDC. There are four key components of successful earth science subsetter architecture. These are: 1.Interactive user interface that is tightly integrated with a PostgrSQL-PostGIS metadata database specifically tailored for the Science Product data granules to be subsetted. 2.Scalable workflow framework for scheduling potentially thousands of subset processes across a configurable number of cluster processing nodes. 3.Efficient subset application with high-speed access to archived data granules. 4.Robust Metadata mining capability focused on obtaining high resolution spatial and temporal metadata. High Resolution Spatial Metadata Mined Directly From Archived HDF Data Granules The original CALIPSO Level 1 LIDAR spatial metadata is defined by a LineString consisting of ten points. The Search and Subset Application uses LineString metadata constructed by approximately 50 points, greatly increasing the accuracy of two dimensional bounding box queries near the poles. (Green = metadata used by new Search and Subset Applications | Red = original metadata used in legacy data access applications) Metadata currently provided for one hour CERES Level 2 SSF granules assumed full coverage of the Earth within 20 degrees of the poles and stepped along the granule footprint boundaries at ten degree longitude intervals. A newer metadata mining technique directly detects field of view positions of the observations along the edges of the granule footprint and implements a Douglas-Peucker simplification on the resulting polygon. The updated hourly footprint polygon contains the same number of points as the original metadata polygon, and is more accurate. In the ECS archive system, Level2 Tropospheric Emission Spectrometer (TES) Ozone metadata assumes global coverage for each daily granule. The ASDC is currently working with the TES Science Team on a prototype search and subset application. The metadata database used in this prototype stores the observation location for every data entry in the granule as an array of points. Bounding Box queries for observations over the entire mission consistently return results in less than five seconds. This ability to obtain any observation over the life of the mission within a few seconds is unprecedented. The CALIPSO Search Subsetter User Interface automatically updates and displays the number of granules meeting the spatial and temporal constraints as the user changes them. This dynamic feedback provides a very positive user experience. New subset interfaces under development for CERES and TES datasets leverage this functionality. Details of the resulting data granules are displayed on the ‘Confirm Request’ page. Users are able to download a list of granules that meet their search criteria, browse profile plots for each resulting granule, or submit an order to subset the granules based on their spatial-temporal inputs. The CALPSO Science Team provides browse images for their LIDAR data products. These profiles are easily accessed through links under each granule result on the ‘Confirm Request’ page. Search and Subset Application Interface Subsetter Workflow Framework Node2 Metadata Database Web User Interface Node1 FTP Site Web Server SciFlo - Univa Grid Engine Processing node running JAVA HDF Subsetter Node2 Node … The Subsetter Framework is a generic framework for subset processing. It uses SciFlo as its workflow engine to drive the processing, and Univa Grid Engine as its resource scheduler, so that the subsetting can be scaled across a set of computational nodes. The ASDC developed dedicated subsetters for the CALIPSO, CERES, and TES missions leveraging the HDF Group’s JAVA JNI libraries used in the open source HDFView application. These subsetters are deployed on Univa Grid Engine processing nodes and are managed by the Subsetter Workflow Framework. The subsetters have the capability to return subsetted files in NetCDF format. Types of granules subsetted from each data provider:  CALIPSO: HDF4  CERES: HDF4  TES: HDF-EOS (HDF5 out) Inspection of a CERES ES8 subset result file in the HDFView application The ASDC subsetters leverage the Common Object Package and use specific methods in the Java HDF and HDF5 JNI Interfaces to directly access lower level functions in the C libraries. (source of diagram: New HDF subset and file access capabilities recently developed through ASDC’s collaboration with data providers give science data users the ability to quickly subset and mine data from large archived files, and has set the stage to directly stream desired data directly from archived files to a client’s visualization or analysis applications. Future Work for Improving ASDC’s Subset and Science Data access  Machine-to-Machine subset interfaces  Very high granularity in spatial/temporal metadata  Geospatial plots of subsetted dataset query results  Real-time browse images of dataset query results