Difference between revisions of "Usage-based Data Discovery - Episode 2"

From Earth Science Information Partners (ESIP)
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= Notes =
 
= Notes =
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Use Cases:  Participating: Bob, Jonathon, Beth, Ed
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Ed: interested in interdisciplinary, datasets used together WITHIN a given application
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Mark:  simple, single dataset use case + complex interdisciplinary use cases
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Beth:  dataset interconnections circles back to data transformations
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Irina:  validation requires MANY different datasets being used together, shows up in separate of research papers that focus on the application vs. those that focus on validation
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J.B.: discovery / search process:  present datasets relevant to their problem, e.g., homeowner types in more colloquial term, interpret what the user's real concern is
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Adrienne (Axiom Data Science): how do we interact with users where they know what they are getting back; users expect fancy searches, but they need to be transparent (document how they got there) - show the graph!
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B. Downs: combine with location of interest
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JB: maybe too big a tech lift at this point?
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Mark:  location is relevant, sure, but how does it
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Chris:  dataset used Gulf of Maine, might be useful in Puget Sound
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Mark:  identify desired outcome
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IMPACT Use Case:
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In addition to how many, what type of use cases
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Beth: Take me to the articles about the data
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Irina: Data providers want to know about applications of their data; ask them if they know how their data are being used
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Bob: What other data were used in conjunction with the datasets in a given climate study
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JB: datasets commonly used together (Mark: closer to Beth's use case variant)
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JB: IMPACT might be a roll up of lots of datasets
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Mark: may want to contrast similar instrument, different algorithms, (Chris: or different platforms)
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Ed:
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Agenda:
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Irina, Beth more graphs, how to make them
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Adrienne: User story, aiming to create at the end
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Ed: Using graphs for discovery, esp. related datasets, practical examples
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Mark:  Take one of these use cases, work a user story end to end to see what the graph looks like, including the tools
 +
Bob: examples of graphs, something about the process we are going through, getting from here to there
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Megan: Session proposal, ESIP Collaboration Slide
  
 
= New Actions =
 
= New Actions =

Revision as of 13:51, March 19, 2020

Participants

  • Chris Lynnes
  • Joe Lee
  • Irina Gerasimov
  • Adrienne
  • Megan Carter
  • Ed Armstrong
  • Mark Parsons
  • Bob Downs
  • Beth Huffer
  • Jonathon Blythe
  • Doug Newman
  • Steve Olding

Current Actions

  • Done: Lynnes - write up some text for Megan's newsletter
  • Done: Lynnes set up regular meeting with ESIP G2M, some time other than 4th Thursday
  • TBD - spin off a subgroup to work on use cases
  • Done: Lynnes/Newman - generate a sample export of EOSDIS knowledge graph
  • Done: Blythe - provide research_prov_model info on use of W3C Prov model

Agenda

  • Use cases for connecting Data with Usage
    • Best Practice Use Case: Which rainfall dataset is most often used for flood prediction?
    • Impact Use Case: How many climate studies use TRMM 3B42 rainfall?
    • <Your use case here>
  • Sample graphs
  • Any other business?
  • Agenda for next telecon…

Notes

Use Cases: Participating: Bob, Jonathon, Beth, Ed Ed: interested in interdisciplinary, datasets used together WITHIN a given application Mark: simple, single dataset use case + complex interdisciplinary use cases Beth: dataset interconnections circles back to data transformations Irina: validation requires MANY different datasets being used together, shows up in separate of research papers that focus on the application vs. those that focus on validation J.B.: discovery / search process: present datasets relevant to their problem, e.g., homeowner types in more colloquial term, interpret what the user's real concern is Adrienne (Axiom Data Science): how do we interact with users where they know what they are getting back; users expect fancy searches, but they need to be transparent (document how they got there) - show the graph! B. Downs: combine with location of interest JB: maybe too big a tech lift at this point? Mark: location is relevant, sure, but how does it Chris: dataset used Gulf of Maine, might be useful in Puget Sound Mark: identify desired outcome

IMPACT Use Case: In addition to how many, what type of use cases Beth: Take me to the articles about the data Irina: Data providers want to know about applications of their data; ask them if they know how their data are being used Bob: What other data were used in conjunction with the datasets in a given climate study JB: datasets commonly used together (Mark: closer to Beth's use case variant) JB: IMPACT might be a roll up of lots of datasets Mark: may want to contrast similar instrument, different algorithms, (Chris: or different platforms) Ed:

Agenda: Irina, Beth more graphs, how to make them Adrienne: User story, aiming to create at the end Ed: Using graphs for discovery, esp. related datasets, practical examples Mark: Take one of these use cases, work a user story end to end to see what the graph looks like, including the tools Bob: examples of graphs, something about the process we are going through, getting from here to there Megan: Session proposal, ESIP Collaboration Slide

New Actions