[Esip-esda] ESIP Earth Sciences Data Analytics (ESDA) Telecon

[Kempler, Steven J. (GSFC-5860)]

When: Thursday, March 20, 2014 3:00 PM-4:00 PM. (UTC-05:00) Eastern Time (US & Canada)
Where: Upcoming Telecon-info comimng

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Next Earth Science Data Analytics (ESDA) telecon:

When: Thursday, March 20, 2014 3:00 PM-4:00 PM. (UTC-05:00) Eastern Time (US & Canada)

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 Connection information to come
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It seems that this Cluster can serve multiple purposes to address the various levels of members understanding and interests regarding Data Analytics.  This includes:


-       ‘Academic’ discussions that allow all of us to be better educated and on the same page in understanding the various aspects of Data Analytics

-       Bringing in guest speakers to describe external efforts and further teach us about the broader use of Data Analytics

-       Activities that ESIP members can actually address and tackle

Agenda - 3/20/14 (details below)


1.     Topics to better understand

2.     Guest Speaker

3.     ESDA Activities

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Agenda Details:


1.     Topics to better understand, so far (let’s say, one per telecom)

A few topics that have come up from our past discussions include:


o   March 20 - Data Scientist vs Data Analytics – Lead by Brand Niemann


Later Dates:

o   Defining the end-to-end data analytics needs:  Define data producer/supplier analytics needs vs. data user analytics needs

o   Understanding the Data Scientists user needs


2.     Guest Speaker – What are people doing with Data Analytics, out there (let’s say two guests per telecom):


TBD:

o   Dave Jones

o   John Schnase

o   IEEE – Beth Plale?

o   Brand Niemann?

o   Belmont Forum - Lee Allison

o   CODATA

o   NSF

o   EarthCube

o   Data- Scientist or two - Understanding the Data Scientists user needs


3.     ESDA Activities


Discussion:  These are solid activities that have been suggested so far.  Do they sound correct?  Any other suggestions/ refinements?  Next:  Volunteers needed to breakout work and move forward…discuss.



1.  Compile use cases (include producer/supplier and data user analytics utilization)

     Compile analytics tools (internal and external to ESIP)

     Do gap analysis


2.  Examine project long case studies to determine successfulness of using data analytics in the project (i.e., lessons learned)


3.  Oh yeah:  Create a Cluster Mission Statement and Objectives


4.  Report out to the Federation All
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