View source for ESIP 2021 Winter Meeting Materials for the session 'Carbon Management, Food, Agriculture, Human well-being: Using informatics to connect the climate action dots'

==Purpose of this page==
This page provides a summary of the session [https://sched.co/g4A6 ESIP Winter 2021 meeting session 'Carbon Management, Food, Agriculture, Human well-being: Using informatics to connect the climate action dots'] held on 2021-01-28 and organized by the ESIP [[Agriculture and Climate]] Cluster.  You may also be interested in another session organized by the cluster titled [https://wiki.esipfed.org/ESIP_2021_Winter_Meeting_Materials_for_the_session_%27Science_and_the_US_Government:_Where_does_your_contribution_fit_into_the_picture%3F%27 'Science and the US Government: Where does your contribution fit into the picture?'].

==People involved==

*Session organizers: [https://linkedin.com/in/weebrian Brian Wee], [https://www.linkedin.com/in/bill-teng-a7033b174/ Bill Teng]
*Presenters: Linsday Barbieri (University of Vermont), Todd Walter (Cornell University), Steele Lorenz (Farmers Business Network)
*Session attendees: Captured in the [https://docs.google.com/document/d/1uD5xOOKzvGOu5zJ4Wv_vl927Nhek8A1fLwZIT1FSgWU session notes Google doc]

==Overview==
How do 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 explored at the ESIP Winter 2021 Meeting session titled [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'].

==Outcome of session==
The three takeaways are:

*Carbon sequestration can be enhanced through climate smart land management practices.
*Climate-friendly farming can be achieved through science and socio-technical innovations that meet the needs of consumers and food producers.
*Technology and informatics for agro-ecosystem research is essential for spanning across geographical scales and scientific disciplines.

A thumbnail version of a graphical session summary is presented as a concept map below.  [https://cmapscloud.ihmc.us/viewer/cmap/1WKVSQBZ3-TG0ZX8-1WP?title=false&toolbar=false&footer=false '''A full-sized version of the concept map is accessible here.''']  Nodes in the concept map that feature an icon at the bottom of the node indicate clickable links.  Different colored nodes indicate the source of those ideas from the respective speakers:

*Blue: Lindsay Barbieri
*Green: Todd Walter
*Gold: Steele Lorenz

To see a different representation of the concepts discussed 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]].

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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.  

'''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.

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    src="https://hub.graphistry.com/graph/graph.html?dataset=06b2d55b8dbe46818b495e5435895658&type=arrow&viztoken=69bc4420-5069-46e8-a820-7e063395276b&usertag=44a9ab01-pygraphistry-0.15.0&splashAfter=1611168020&info=true&play=2000&showArrows=True&showLabels=True&showLabelOnHover=True&pointsOfInterestMax=50&pointSize=25&labelColor=black&session=aca57661fc5c46a2863848486b3a0cb2"
    style="border: 1px solid black; width: 100%; height: 100%; min-height: 600px"
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