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Job request: 16656

Organisation:
University of Bristol
Workspace:
risk-factors-winter-infections
ID:
wwbeatwhm7suxlnm
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Scott Walter 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: 200000

actions:

  ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # 
  ## DO NOT EDIT project.yaml DIRECTLY 
  ## This file is created by create_project_actions.R 
  ## Edit and run create_project_actions.R to update the project.yaml 
  ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # 
  ## Generate study population - winter2019 

  generate_study_population_winter2019:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_winter2019
      --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_winter2019.csv.gz

  ## Describe - input_winter2019.csv.gz 

  describe_input_winter2019:
    run: stata-mp:latest analysis/describe.do input_winter2019 csv
    needs:
    - generate_study_population_winter2019
    outputs:
      highly_sensitive:
        cohort: output/describe-input_winter2019.log

  ## Data cleaning - winter2019 

  data_cleaning_winter2019:
    run: stata-mp:latest analysis/data_cleaning.do winter2019 td(1dec2019) td(28feb2020)
    needs:
    - generate_study_population_winter2019
    outputs:
      moderately_sensitive:
        consort: output/consort_winter2019.csv
        rounded_consort: output/rounded_consort_winter2019.csv
      highly_sensitive:
        cohort: output/clean_winter2019.dta.gz

  ## Describe - clean_winter2019.dta.gz 

  describe_clean_winter2019:
    run: stata-mp:latest analysis/describe.do clean_winter2019 dta
    needs:
    - data_cleaning_winter2019
    outputs:
      highly_sensitive:
        cohort: output/describe-clean_winter2019.log

  ## Table 1 - winter2019 

  table1_winter2019:
    run: stata-mp:latest analysis/table1.do winter2019
    needs:
    - data_cleaning_winter2019
    outputs:
      moderately_sensitive:
        table1: output/table1_winter2019.csv
        rounded_table1: output/rounded_table1_winter2019.csv

  ## Table 2 - winter2019 

  table2_winter2019:
    run: stata-mp:latest analysis/table2.do winter2019
    needs:
    - data_cleaning_winter2019
    outputs:
      moderately_sensitive:
        table1: output/table2_winter2019.csv
        rounded_table1: output/rounded_table2_winter2019.csv

  ## Generate study population - winter2021 

  generate_study_population_winter2021:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_winter2021
      --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_winter2021.csv.gz

  ## Describe - input_winter2021.csv.gz 

  describe_input_winter2021:
    run: stata-mp:latest analysis/describe.do input_winter2021 csv
    needs:
    - generate_study_population_winter2021
    outputs:
      highly_sensitive:
        cohort: output/describe-input_winter2021.log

  ## Data cleaning - winter2021 

  data_cleaning_winter2021:
    run: stata-mp:latest analysis/data_cleaning.do winter2021 td(1dec2021) td(28feb2022)
    needs:
    - generate_study_population_winter2021
    outputs:
      moderately_sensitive:
        consort: output/consort_winter2021.csv
        rounded_consort: output/rounded_consort_winter2021.csv
      highly_sensitive:
        cohort: output/clean_winter2021.dta.gz

  ## Describe - clean_winter2021.dta.gz 

  describe_clean_winter2021:
    run: stata-mp:latest analysis/describe.do clean_winter2021 dta
    needs:
    - data_cleaning_winter2021
    outputs:
      highly_sensitive:
        cohort: output/describe-clean_winter2021.log

  ## Table 1 - winter2021 

  table1_winter2021:
    run: stata-mp:latest analysis/table1.do winter2021
    needs:
    - data_cleaning_winter2021
    outputs:
      moderately_sensitive:
        table1: output/table1_winter2021.csv
        rounded_table1: output/rounded_table1_winter2021.csv

  ## Table 2 - winter2021 

  table2_winter2021:
    run: stata-mp:latest analysis/table2.do winter2021
    needs:
    - data_cleaning_winter2021
    outputs:
      moderately_sensitive:
        table1: output/table2_winter2021.csv
        rounded_table1: output/rounded_table2_winter2021.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 09:04:27

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

Job information

Status
Succeeded
Backend
TPP
Workspace
risk-factors-winter-infections
Requested by
Scott Walter
Branch
main
Force run dependencies
No
Git commit hash
ec8cd20
Requested actions
  • data_cleaning_winter2019
  • table1_winter2019
  • table2_winter2019
  • data_cleaning_winter2021
  • table1_winter2021
  • table2_winter2021

Code comparison

Compare the code used in this Job Request