Difference between revisions of "Earth Science Data Analytics"

From Earth Science Information Partners (ESIP)
 
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- Seek graduate data analytics/ Data Science student internship opportunities
 
- Seek graduate data analytics/ Data Science student internship opportunities
  
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'''ESIP has adopted the following definition for Earth Science Data Analytics: '''
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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.
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This encompasses:
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---Data Preparation – Preparing heterogeneous data so that they can be jointly analyzed
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---Data Reduction – Correcting, ordering and simplifying data in support of analytic objectives
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---Data Analysis – Applying techniques/methods to derive results
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'''In addition, ESIP has adopted the following Goals of Earth Science Data Analytics:'''
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ESDA Goals (read: Earth science data analytics needed ...)
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---To calibrate data
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---To validate data (note it does not have to be via data intercomparison)
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---To assess data quality
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---To perform coarse data preparation (e.g., subsetting data, mining data, transforming data, recovering data)
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---To intercompare datasets (i.e., any data intercomparison; Could be used to better define validation/quality)
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---To tease out information from data
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---To glean knowledge from data and information
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---To forecast/predict/model phenomena (i.e., Special kind of conclusion)
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---To derive conclusions (i.e., that do not easily fall into another type)
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---To derive new analytics tools
 
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[[Use Case Collection|Gathering Use Cases...]]<br>
 
[[Use Case Collection|Gathering Use Cases...]]<br>
  
[[Analytics Tools|Gathering Analytics Tools/Techniques...]]<br>
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[[ESIP Earth Science Data Analytics Use Cases|ESIP Earth Science Data Analytics Use Cases...]]<br>
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[[Analysis Use Case information definitions|Analysis Use Case information definitions...]]<br>
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[[ESDA Tool/Technique Descriptions|ESDA Tool/Technique Descriptions...]]<br>
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[[Techniques/Goals/ESDA Types Relationships Matrix|Techniques/Goals/ESDA Types Relationships Matrix...]]<br>
  
 
[[Use Case Information Needed|Use Case Information Needed Working Spreadsheet...]]<br>
 
[[Use Case Information Needed|Use Case Information Needed Working Spreadsheet...]]<br>
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[[Earth Science Data Analytics/Other References|Other References]]<br>
 
[[Earth Science Data Analytics/Other References|Other References]]<br>
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[[Earth Science Data Analytics/2016 Plan|2016 Plan]]<br>
  
 
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* '''[[/{{PAGENAME}}_Telecons|Telecons:]]'''
 
* '''[[/{{PAGENAME}}_Telecons|Telecons:]]'''
 
** Third Thursday of each month (3 - 4 p.m. EST)
 
** Third Thursday of each month (3 - 4 p.m. EST)
** Next: May 14, 2015, 3-4 EST
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** Next Telecon: January or February, 2017
** WebEx: https://esipfed.webex.com/ ,  23136782
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** '''NEXT FACE-TO-FACE at ESIP Meeting, Thursday, January 12, 4:00, Salon E'''
** Telecon: 1-877-668-4493, 23136782#
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**To join the meeting from your computer, tablet or smartphone, click:
* '''Cluster Contacts:''' Steve Kempler, Tiffany Mathews
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**https://www.gotomeeting.com/join/407339749
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**You can also dial in using your phone.
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***United States: +1 (312) 757-3121
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***Access Code: 407-339-749
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* '''Cluster Contacts:''' Lindsay Barbieri, Tiffany Mathews, Shea Caspersen
 
    
 
    
 
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Latest revision as of 09:16, December 14, 2016

Welcome to the Earth Science Data Analytics Cluster

Mission:

To promote a common understanding of the usefulness of, and activities that pertain to, Data Analytics and more broadly, the Data Scientist; Facilitate collaborations between organizations that seek new ways to better understand the cross usage of heterogeneous datasets and organizations/individuals who can provide accommodating data analytics expertise, now and as the needs evolve into the future; Identify gaps that, once filled, will further collaborative activities.

Objectives

- Provide a forum for ‘Academic’ discussions that allow ESIP members to be better educated and on the same page in understanding the various aspects of Data Analytics

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

- Perform activities that:

--- Compile use cases generated from specific community needs to cross analyze heterogeneous data (could be ESIP members or external)

--- Compile experience sources on the use of analytics tools, in particular, to satisfy the needs of the above data users (also, could be ESIP members or external)

--- Examine gaps between needs and expertise

--- Document the specific data analytics expertise needed in above collaborations

- Seek graduate data analytics/ Data Science student internship opportunities


ESIP has adopted the following definition for Earth Science Data Analytics:

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. This encompasses:

---Data Preparation – Preparing heterogeneous data so that they can be jointly analyzed

---Data Reduction – Correcting, ordering and simplifying data in support of analytic objectives

---Data Analysis – Applying techniques/methods to derive results


In addition, ESIP has adopted the following Goals of Earth Science Data Analytics:

ESDA Goals (read: Earth science data analytics needed ...)

---To calibrate data

---To validate data (note it does not have to be via data intercomparison)

---To assess data quality

---To perform coarse data preparation (e.g., subsetting data, mining data, transforming data, recovering data)

---To intercompare datasets (i.e., any data intercomparison; Could be used to better define validation/quality)

---To tease out information from data

---To glean knowledge from data and information

---To forecast/predict/model phenomena (i.e., Special kind of conclusion)

---To derive conclusions (i.e., that do not easily fall into another type)

---To derive new analytics tools

Events and Activities[edit | edit source]

2016-12-08: Telecon XXIX
2016-11-17: Telecon XXVIII
2016-10-20: Telecon XXVII
2016-09-15: Telecon XXVI
2016-08-18: Telecon XXV
2016-07-20: July, 2016 ESIP Meeting notes (Durham), Earth Science Data Analytics Tools, Techniques and More
2016-06-16: Telecon XXIV
2016-05-26: Telecon XXIII
2016-04-21: Telecon XXII
2016-03-17: Telecon XXI
2016-02-18: Telecon XX
2016-01-21: Nineteenth Telecon
2016-01-07: January, 2016 ESIP Meeting notes (Washington), Earth Science Data Analytics - What are your analytics requirements?
2015-12-03: Eighteenth Telecon
2015-11-12: Seventeenth Telecon
2015-09-17: Sixteenth Telecon
2015-08-20: Fifteenth Telecon
2015-07-16: July, 2015 ESIP Meeting notes (Asilomar), The Need for Earth Science Data Analytics to Facilitate Community Resilience (and other applications)
2015-07-14: July, 2015 ESIP Meeting notes (Asilomar), Teaching Science Data Analytics Skills, and the Earth Science Data Scientist
2015-06-18: Fourteenth Telecon
2015-05-21: Thirteenth Telecon
2015-04-16: Twelfth Telecon
2015-03-19: Eleventh Telecon
2015-02-26: Tenth Telecon
2015-02-05: Ninth Telecon
2015-01-07: January, 2015 ESIP Meeting notes (Washington), ESDA 201 Session
2015-01-07: January, 2015 ESIP Meeting notes (Washington), ESDA 101 Session
2014-11-20: Eighth Telecon
2014-10-23: Seventh Telecon
2014-08-21: Sixth Telecon
2014-07-10: July, 2014 ESIP Meeting notes (Frisco)
2014-06-26: Fifth Telecon
2014-05-22: Fourth Telecon
2014-04-17: Third Telecon
2014-03-20: Second Telecon
2014-02-20: First Telecon
2014-01-09: Initial ESIP Meeting notes

Archive

Active Collaborations[edit | edit source]

Gathering Use Cases...

ESIP Earth Science Data Analytics Use Cases...

Analysis Use Case information definitions...

ESDA Tool/Technique Descriptions...

Techniques/Goals/ESDA Types Relationships Matrix...

Use Case Information Needed Working Spreadsheet...

Resources[edit | edit source]

Presentations

Other References

2016 Plan

Get Involved[edit | edit source]




What links here: Earth Science Data Analytics Earth_Science_Data_Analytics