Earth Science Data Analytics/2015-11-12 Telecon

From Earth Science Information Partners (ESIP)

ESDA Telecon notes – 11/12/15

Known Attendees:

ESIP Host (Annie Burgess), Steve Kempler, Tiffany Mathews, Sean Barberie, Beth Huffer, Chung-Lin Shie, Robert Downs, Ethan McMahon, Joan Aron



1. Finalize ESDA Analytics Definitions and Goals Statement to ESIP ExComm

2. Determining Analytics Tools/Techniques Requirements associated with Analytics Goals

3. Process for associating Analytics Tools/Techniques that can fulfill Requirements

4. Open Mic


None, this time.

Use Case Information:


Thank you all for attending and participating in our telecon.

Well we covered Agenda Item #1 pretty well. The hour consisted of an excellent discussion on the letter being prepared for the ExComm recommending the ESIP endorse the ESDA Earth science data analytics definition. It is felt that having a clear ESDA definition will facilitate the development of ESDA techniques and tools that focus on Earth science.

Today's discussion focused on improving the definition to its final form, and editing the letter. The current version of the letter will soon be posted and further discussed (finalized?) at the next ESDA telecon. The ESDA definition is as follows:

Earth Science Data Analytics definition:

The process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth.

The remainder of the time reviewed our to do list (see below), our Winter meeting session (see abstract that follows), and the following potential collaborations with other ESIP working groups (clusters,etc.):

Emerging Big Data Technologies for Geoscience - We can share derived ESDA requirements and found technology gaps

Esip-disasters and Esip-infoquality - We can share use cases to determine what data analytics requirements may emerge

WInter ESIP ESDAS Cluster Session Abstract:

The Earth Science Data Analytics (ESDA) Cluster has made great strides in understanding the utilization of data analytics in Earth science, an area virtually untouched in the literature. In achieiving its goal to support advancing science research that increasingly includes very large volumes of heterogeneous data, the ESDA Cluster has defined terms, documented use cases, and loosely identified tools and technologies that faciltate a better understanding of the needs of Earth science research.

This cluster session will discuss and initate the work still to be done, including evaluating use cases, extracting data analytics requirements from use cases (this will be a major part of the discussion), survey exisiting data anlytics tools and techniques, and sharing derived ESDA requirements and found technology gaps with the ESIP group interested in 'Emerging Big Data Technologies for Geoscience'.

To Do List:


1. Finalize ESDA Definition and Goal categories


2. Write letter to ESIP Executive Committee proposing that the ESDA Definitions and Goal categories be ESIP approved

3. Acquire many more additional use cases

4. Characterize use cases by Goal categories and other analytics driving considerations

5. Derive requirements from #4

6. Survey existing data analytics tools/techniques

7. Write our paper describing ... all the above

Questions to think about:

What is the best way to record use cases, and associated requirements, and matching tools? A forum?

Going to AGU?

The following Data Analytics / Big Data related sessions are listed to occur at the AGU in December:

  • Advanced Information Systems to Support Climate Projection Data Analysis

Gerald L Potter, Tsengdar J Lee, Dean Norman Williams, and Chris A Mattmann

  • Big Data Analytics for Scientific Data

Emily Law, Michael M Little, Daniel J Crichton, and Padma A Yanamandra-Fisher

  • Big Data in Earth Science – From Hype to Reality

Kwo-Sen Kuo, Rahul Ramachandran, Ben James Kingston Evans. and Mike M Little

  • Big Data in the Geosciences: New Analytics Methods and Parallel Algorithms

Jitendra Kumar and Forrest M Hoffman

  • Computing Big Earth Data

Michael M Little, Darren L. Smith, Piyush Mehrotra, and Daniel Duffy

  • Geophysical Science Data Analytics Use Case Scenarios

Steven J Kempler, Robert R Downs, Tiffany Joi Mathews, and John S Hughes

  • Man vs. Machine - Machine Learning and Cognitive Computing in the Earth Sciences

Jens F Klump, Xiaogang Ma, Jess Robertson and Peter A Fox

  • New approaches for designing Big Data databases

David W Gallaher and Glenn Grant

  • Partnerships and Big Data Facilities in a Big Data World

Kenneth S Casey and Danie Kinkade

  • Towards a Career in Data Science: Pathways and Perspectives

Karen I Stocks, Lesley A Wyborn, Ruth Duerr, and Lynn Yarmey

Next Telecon:

Thursday, December 3, 2015, 3:00 EST


Among other things, finalize letter to ESIP Executive Committee for ESIP ESDA definition approval; Discuss process for matching use case requirements with capabilities of existing tools.


Steve: Update ESDA definition endorsement letter

Volunteers: Review endorsement paper, when ready

All: Think about process for matching use case requirements with capabilities of existing tools.