Difference between revisions of "ESIP 2021 Winter Meeting Preparatory Material for the meeting session 'Carbon Management, Food, Agriculture, Human well-being: Using informatics to connect the climate action dots'"

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='''Seed concept map'''=
 
='''Seed concept map'''=
The "seed" concept map is shown below, and is static.
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The "seed" concept map is shown below.  URLs in the concept map (look for the icons that resemble a document) are clickable.
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*[https://cmapscloud.ihmc.us/viewer/cmap/1WKVSQBZ3-TG0ZX8-1WP?title=false&toolbar=false&footer=false '''To see the map evolve as it is updated through the presentations, click here''' to see the 'live' concept map].
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*To see a more complex representation of the ideas that will be explored during the session, [[#Experimental concept graph visualization|see the next section on an approach to generate a concept graph (as opposed to a concept map) using the Neo4j graph database]].
  
[https://cmapscloud.ihmc.us/viewer/cmap/1WKVSQBZ3-TG0ZX8-1WP?title=false&toolbar=false&footer=false" width="835" height="663"  '''To see the map evolve as it is updated through the presentations''', click here and the 'live' concept map will be opened in a new window].
 
 
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='''Experimental concept graph'''=
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='''Experimental concept graph visualization'''=
  
 
Below, we show an experimental visualization that uses selected documents to show the connections between entities like the SDGs, journal publications, a private sector white paper, and US government reports.  The visualization is part of the <b>[https://2021esipwintermeeting.sched.com/event/g4A6/carbon-management-food-agriculture-human-well-being-using-informatics-to-connect-the-climate-action-dots 'Carbon Management, Food, Agriculture, Human well-being: Using informatics to connect the climate action dots'] session </b> at the ESIP Winter 2021 Meeting.   
 
Below, we show an experimental visualization that uses selected documents to show the connections between entities like the SDGs, journal publications, a private sector white paper, and US government reports.  The visualization is part of the <b>[https://2021esipwintermeeting.sched.com/event/g4A6/carbon-management-food-agriculture-human-well-being-using-informatics-to-connect-the-climate-action-dots 'Carbon Management, Food, Agriculture, Human well-being: Using informatics to connect the climate action dots'] session </b> at the ESIP Winter 2021 Meeting.   
  
'''You may need to click on the image below to initiate the rendering of a concept graph.'''  The graph is 'live': experiment with zooming, panning, and clicking on nodes and relationships (relationships are the lines connecting nodes).  Look for the "Open in a new window" icon in the menu bar, right next to the word "WORKBOOK" below.  Clicking on that icon opens up a new browser tab to better visualize the concept graph.
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'''You may need to click on the image below to initiate the rendering of a concept graph (and, sometimes, refresh this page).'''  The graph is 'live': experiment with zooming, panning, and clicking on nodes and relationships (relationships are the lines connecting nodes).  Look for the "Open in a new window" icon in the menu bar, right next to the word "WORKBOOK" below.  Clicking on that icon opens up a new browser tab to better visualize the concept graph.
  
 
The data for the visualization is maintained in a "labeled property graph" database called Neo4j.  A database query, written in the Neo4j query language "Cypher", was issued against the database from within a Python Jupyter notebook.  The query results were formatted and then sent to the Graphistry web service for visualization.
 
The data for the visualization is maintained in a "labeled property graph" database called Neo4j.  A database query, written in the Neo4j query language "Cypher", was issued against the database from within a Python Jupyter notebook.  The query results were formatted and then sent to the Graphistry web service for visualization.

Latest revision as of 09:44, January 25, 2021

Overview

How does the Sustainable Development Goals (SDG) relate to President Biden's goals for managing the US's contribution to the global carbon budget? What is the role of the farming sector and crop management best practices? How can your work as a research scientist inform farm management? These are the issues that we shall be exploring at the ESIP Winter 2021 Meeting session titled 'Carbon Management, Food, Agriculture, Human well-being: Using informatics to connect the climate action dots'.

During the session, attendees will be introduced to a high-level concept map that provides a landscape overview of the concepts that will be addressed in the session. That concept map will be incrementally evolved as each of our invited speakers present their materials. At the end of the presentations, attendees will be assigned small breakout groups to continue evolving the concept map.

You are encouraged to familiarize yourself with the "seed" concept map before the session.

Seed concept map

The "seed" concept map is shown below. URLs in the concept map (look for the icons that resemble a document) are clickable.



Experimental concept graph visualization

Below, we show an experimental visualization that uses selected documents to show the connections between entities like the SDGs, journal publications, a private sector white paper, and US government reports. The visualization is part of the 'Carbon Management, Food, Agriculture, Human well-being: Using informatics to connect the climate action dots' session at the ESIP Winter 2021 Meeting.

You may need to click on the image below to initiate the rendering of a concept graph (and, sometimes, refresh this page). The graph is 'live': experiment with zooming, panning, and clicking on nodes and relationships (relationships are the lines connecting nodes). Look for the "Open in a new window" icon in the menu bar, right next to the word "WORKBOOK" below. Clicking on that icon opens up a new browser tab to better visualize the concept graph.

The data for the visualization is maintained in a "labeled property graph" database called Neo4j. A database query, written in the Neo4j query language "Cypher", was issued against the database from within a Python Jupyter notebook. The query results were formatted and then sent to the Graphistry web service for visualization.