[ESIP-all] Workshop on Data and Computational Science Technologies for Earth Science Research - IEEE Big Data Conference

[Law, Emily S (3980)]

Call for papers and participation
Workshop on Data and Computational Science Technologies for Earth Science Research - IEEE Big Data Conference http://ieee-bigdata-earthscience.jpl.nasa.gov/
Oct 29-Nov 1, 2015
Santa Clara, CA

Abstracts are currently being accepted, due August 30, 2015: http://ieee-bigdata-earthscience.jpl.nasa.gov/papers





Workshop on Data and Computational Science Technologies for Earth Science Research



2015 IEEE Big Data Conference<http://cci.drexel.edu/bigdata/bigdata2015/>
October 29, 2015 – November 1, 2015
Santa Clara, CA
http://ieee-bigdata-earthscience.jpl.nasa.gov





Workshop Description


Currently, the analysis of large data collections from earth science research is executed through traditional computational and data analysis approaches, which require users to bring data to their desktops and perform local data analysis. Future earth science remote sensing missions, which historically assume that all data can be collected, transmitted, processed, and archived, may not scale as more capable instruments stress existing architectural approaches and systems. A new paradigm is needed in order to increase the productivity and effectiveness of scientific data analysis. This paradigm must recognize that architectural and analytical choices are interrelated, and must be carefully coordinated in any system that aims to allow efficient, interactive scientific exploration and discovery to exploit massive data collections, from point of collection (e.g., onboard) to analysis and decision support. Both future observational systems, including satellite and airborne experiments, and research in climate modeling will significantly increase the size of the data requiring new approaches across the entire data lifecycle from capture to generation, management, and analysis of the data.

The workshop seeks computational and data science experts to present on their research and discuss Big Data roadmaps, architectures, technologies, and methodologies for future Earth Science data challenges emerging from both observational systems and climate studies.



Technical Focus


I. Architectural considerations/tradeoffs for integrating the entire data lifecycle from observational systems to climate modeling and research

•   Approaches for scaling observing systems for satellite, airborne and ground-based sensors

•   Integration of computational methods with observing systems

•   New concepts for data intensive missions

•   Integration of data, computing/HPC/cloud, and algorithms

•   Cloud computing, software as a service

•   New technologies (e.g., distributed frameworks, database technologies, search, etc) for scaling the architecture



II. Onboard/Sensor-based Computing

•   Embedded and real-time data reduction and triage/analytics methods

•   Managing bandwidth constraints for high volume instruments



III. Scalable Data Management and Computation for ground-based systems

•           Capturing well-architected and curated data repositories

•           Data and semantic information architectures

•           Architecting automated pipelines for data capture

•           Enabling analytics on data pipelines for computation, data discovery, event detection, reduction, etc

•           Open source data science frameworks

•           Cloud computing



IV. Scalable Data Analytics for Massively Distributed Data

•         Access and integration of highly distributed, heterogeneous data

•         Novel statistical approaches for data integration and fusion

•         Sampling strategies from massive data repositories

•         Uncertainty in scientific inferences

•         In situ analysis for High Performance Computing

•         Computation applied at the data sources

•         Automated Machine Learning methods for identifying and extracting interesting features and patterns

•         Methods for visualizing massive observational and model data

Target Audience


Data and computational science technologists, earth science research community, government program managers in data science and computation.


Papers


Extended abstracts are solicited that cover the research areas described in this workshop.  Speakers will be chosen from the abstracts.  Go here<http://ieee-bigdata-earthscience.jpl.nasa.gov/papers> for information on abstract and paper submissions.  Papers are due August 1, 2015.


Workshop Report


A workshop report will be produced highlighting the roadmap and technologies presented.

Program Committee


Daniel Crichton, NASA Jet Propulsion Laboratory

Yolanda Gil, University of Southern California, Information Sciences Institute

Jacqueline Lamoigne-Stewart, NASA Goddard Space Flight Center

Emily Law, NASA Jet Propulsion Laboratory

Mike Little, NASA Headquarters

Piyush Mehrotra , NASA Ames Research Center

Jim Nelson, EROS Data Center/USGS

Dean Williams, Lawrence Livermore National Laboratory


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