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  1. Data Management
  2. DM-34607

Write SPIE 2022 butler paper

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    • Type: Story
    • Status: Done
    • Resolution: Done
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    • Team:
      Architecture
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      Description

      A butler paper has been accepted for the SPIE conference in the summer in Montreal.

      • Paper ID: 12189-40
      • Title: The Vera C. Rubin Observatory Data Butler and pipeline execution system

      This ticket is to write the paper (not the talk). How much technical detail to include is still open to debate. The SPIE requirements are for a minimum of 4 pages but they seem to have removed the cap for maximum length (maybe they no longer publish hardcopy proceedings so page counts aren't an issue).

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          Web Link DMTN-229

          Web Link Manuscript guidelines

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            tjenness Tim Jenness added a comment -

            Draft PDF: https://dmtn-229.lsst.io/v/DM-34607/index.html
            Pull request: https://github.com/lsst-dm/dmtn-229/pull/2

            Jim Bosch can you please review the entire paper. I've tried to give a general overview and show features and motivation without getting into technical details. The balance between butler and pipelines is towards butler because that's what I work on.

            Nate Lust please look at the pipelines section and Michelle Gower please look at the batch processing section. Currently only a page each.

            All types of comment are welcomed. It's a little drafty and I'm not entirely happy with the way I introduce dimensions vs dataset types. The introduction probably needs to be more exciting.
            Especially let me know if there are things I've missed that should be included (and of course anything that is wrong).

            Remember the paper will go for project internal review before being submitted. We need it to go to project review on June 1st.

            Andy Salnikov, Nate Pease [X], and Mikolaj Kowalik should also take a look to confirm that they are happy to be included as co-authors.

            Show
            tjenness Tim Jenness added a comment - Draft PDF: https://dmtn-229.lsst.io/v/DM-34607/index.html Pull request: https://github.com/lsst-dm/dmtn-229/pull/2 Jim Bosch can you please review the entire paper. I've tried to give a general overview and show features and motivation without getting into technical details. The balance between butler and pipelines is towards butler because that's what I work on. Nate Lust please look at the pipelines section and Michelle Gower please look at the batch processing section. Currently only a page each. All types of comment are welcomed. It's a little drafty and I'm not entirely happy with the way I introduce dimensions vs dataset types. The introduction probably needs to be more exciting. Especially let me know if there are things I've missed that should be included (and of course anything that is wrong). Remember the paper will go for project internal review before being submitted. We need it to go to project review on June 1st. Andy Salnikov , Nate Pease [X] , and Mikolaj Kowalik should also take a look to confirm that they are happy to be included as co-authors.
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            tjenness Tim Jenness added a comment -

            In case it's not obvious, the only files that need to be looked at on the pull request are DMTN-229.tex and local.bib (if you have opinions about references).

            Show
            tjenness Tim Jenness added a comment - In case it's not obvious, the only files that need to be looked at on the pull request are DMTN-229.tex and local.bib (if you have opinions about references).
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            jbosch Jim Bosch added a comment -

            Done with my review and removing myself from the list.  Thanks for writing this up - I think you actually did a very good job of explaining all of the semi-circular data model concepts, but I may not be representative of the intended audience.

            Show
            jbosch Jim Bosch added a comment - Done with my review and removing myself from the list.  Thanks for writing this up - I think you actually did a very good job of explaining all of the semi-circular data model concepts, but I may not be representative of the intended audience.
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            tjenness Tim Jenness added a comment -

            Marking the review as complete since I have now received comments from everyone.

            Show
            tjenness Tim Jenness added a comment - Marking the review as complete since I have now received comments from everyone.
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            tjenness Tim Jenness added a comment -

            Paper has been submitted to publications board in PUB-132

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            tjenness Tim Jenness added a comment - Paper has been submitted to publications board in PUB-132

              People

              Assignee:
              tjenness Tim Jenness
              Reporter:
              tjenness Tim Jenness
              Reviewers:
              Michelle Gower, Nate Lust
              Watchers:
              Jim Bosch, Michelle Gower, Nate Lust, Tim Jenness
              Votes:
              0 Vote for this issue
              Watchers:
              4 Start watching this issue

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