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Job request: 18095

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
openprompt-hrqol
ID:
h2vd4o5otpadldiu
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Oliver Carlile requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level various outputs were written to. Researchers can never directly view outputs marked as highly_sensitive ; they can only request that code runs against them. Outputs marked as moderately_sensitive can be viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as moderately_sensitive can be requested for release to the public, via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

expectations:
 population_size: 10000

actions:

  # create_dummy_openprompt_data: 
  #   run: >
  #     r:latest
  #       analysis/create_dummy_openprompt_data.R
  #   outputs: 
  #     moderately_sensitive: 
  #       dummy_openprompt: output/dummy_openprompt.csv.gz

  generate_openprompt_baseline: 
    run: >
      databuilder:v0
        generate-dataset 
        analysis/model_questions/process_baseline.py 
        --output output/openprompt_baseline.csv
        --
        --day=0
    outputs:
      highly_sensitive:
        openprompt_baseline: output/openprompt_baseline.csv

  generate_openprompt_survey1: 
    run: >
      databuilder:v0
        generate-dataset 
        analysis/model_questions/process_research.py 
        --output output/openprompt_survey1.csv
        --
        --day=0
    outputs:
      highly_sensitive:
        openprompt_survey1: output/openprompt_survey1.csv

  generate_openprompt_survey2: 
    run: >
      databuilder:v0
        generate-dataset 
        analysis/model_questions/process_research.py 
        --output output/openprompt_survey2.csv
        --
        --day=30
    outputs:
      highly_sensitive:
        openprompt_survey2: output/openprompt_survey2.csv

  generate_openprompt_survey3: 
    run: >
      databuilder:v0
        generate-dataset 
        analysis/model_questions/process_research.py 
        --output output/openprompt_survey3.csv
        --
        --day=60
    outputs:
      highly_sensitive:
        openprompt_survey3: output/openprompt_survey3.csv

  generate_openprompt_survey4: 
    run: >
      databuilder:v0
        generate-dataset 
        analysis/model_questions/process_research.py 
        --output output/openprompt_survey4.csv
        --
        --day=90
    outputs:
      highly_sensitive:
        openprompt_survey4: output/openprompt_survey4.csv

  combine_openprompt:
    run: >
      r:latest analysis/001_datacombine.R
    needs: [generate_openprompt_baseline, generate_openprompt_survey1, generate_openprompt_survey2, generate_openprompt_survey3, generate_openprompt_survey4]
    outputs: 
      highly_sensitive: 
        openprompt_combined: output/openprompt_raw.gz.parquet
      moderately_sensitive:
        openprompt_summ_skim: output/data_properties/op_raw_skim.txt
        openprompt_summ_tab: output/data_properties/op_raw_tabulate.txt
        table1: output/tab1_baseline_description.html

  # generate_openprompt_plus_tpp: 
  #   run: >
  #     databuilder:v0
  #       generate-dataset analysis/dataset_definition_openprompt.py --output output/openprompt_raw_plus_tpp.csv.gz
  #   needs: [create_dummy_openprompt_data]
  #   outputs:
  #     highly_sensitive:
  #       openprompt_tpp_combined: output/openprompt_raw_plus_tpp.csv.gz

  # quick_summ_data:
  #   run: >
  #     r:latest
  #       analysis/010_table1.R
  #   needs: [generate_openprompt_plus_tpp]
  #   outputs:
  #     highly_sensitive:
  #       cleandata: output/cleaned_data.gz.parquet
  #     moderately_sensitive:
  #       table1: output/tab1_baseline_description.html
  #       longcovid_dates: output/longcovid_dates.pdf

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:06:24

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status
Succeeded
Backend
TPP
Workspace
openprompt-hrqol
Requested by
Oliver Carlile
Branch
main
Force run dependencies
Yes
Git commit hash
faa8805
Requested actions
  • run_all

Code comparison

Compare the code used in this Job Request