values.yaml

ambassador:
  enabled: true
  image:
    repository: quay.io/datawire/ambassador
    tag: 1.4.2
arborist:
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/arborist
    tag: "2025.07"
  externalSecrets:
    dbcreds: qa-midrc-arborist-creds
audit:
  enabled: true
  externalSecrets:
    auditG3auto: qa-midrc-audit-g3auto
    dbcreds: qa-midrc-audit-creds
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/audit-service
    tag: master
aws-es-proxy:
  enabled: true
  image:
    repository: quay.io/cdis/aws-es-proxy
    tag: v1.3.1
  esEndpoint: vpc-devplanetv2-gen3-metadata-2-xkwr2f3gbxua5mqqi7rhnat4la.us-east-1.es.amazonaws.com
awshelper:
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/awshelper
    tag: "2025.07"
dashboard:
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/gen3-statics
    tag: "2025.07"
ohif-viewer:
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/ohif-viewer
    tag: gen3-v3.9.3
orthanc:
  enabled: true
  externalSecrets:
    orthancS3G3Auto: qa-midrc-orthanc-s3-g3auto
    dbcreds: qa-midrc-orthanc-s3-creds
dicom-server:
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/gen3-orthanc
    tag: gen3-0.1.2
  externalSecrets:
    orthancG3Auto: qa-midrc-orthanc-g3auto
    dbcreds: qa-midrc-orthanc-creds
fence:
  usersync:
    usersync: true
    userYamlS3Path: s3://cdis-gen3-users/qa/user.yaml
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  externalSecrets:
    createK8sGoogleAppSecrets: false
    fenceConfig: qa-midrc-fence-config
    fenceGoogleAppCredsSecret: qa-midrc-fence-google-app-creds
    fenceGoogleStorageCredsSecret: qa-midrc-fence-google-storage-creds
    fenceJwtKeys: qa-midrc-fence-jwt
    dbcreds: qa-midrc-fence-creds
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/fence
    tag: "2025.07"
fluentd:
  enabled: true
  image:
    repository: fluent/fluentd-kubernetes-daemonset
    tag: v1.15.3-debian-cloudwatch-1.0
gen3-workflow:
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/gen3-workflow
    tag: test_plugin-support-with-logs
global:
  crossplane:
    enabled: true
    oidcProviderUrl: "oidc.eks.us-east-1.amazonaws.com/id/F057519C0E32B7DE2580904C4007BB21"
    accountId: "707767160287"
  aws:
    account: "707767160287"
    awsEsProxyRole: devplanetv2--qa-midrc--es-access
    enabled: true
    secretStoreServiceAccount:
      enabled: true
      # roleArn: arn:aws:iam::707767160287:role/qa-midrc-external-secrets-sa
      # temporarily using shared role
      roleArn: arn:aws:iam::707767160287:role/devplanetv2-external-secrets-sa
    wafv2:
      enabled: true
      wafAclArn: "arn:aws:wafv2:us-east-1:707767160287:regional/webacl/devplanetv2-waf/30660590-f707-4ecf-aeae-ddfbe381f388"
  dev: false
  dictionaryUrl: https://s3.amazonaws.com/dictionary-artifacts/midrc_dictionary/1.3.9/schema.json
  dispatcherJobNum: "10"
  environment: devplanetv2
  externalSecrets:
    deploy: true
  hostname: qa-midrc.planx-pla.net
  manifestGlobalExtraValues:
    kube_bucket: kube-qaplanetv2-gen3
    logs_bucket: logs-qaplanetv2-gen3
  publicDataSets: true
  tierAccessLevel: libre
  tierAccessLimit: "2"
  portalApp: gitops
  postgres:
    dbCreate: false
  revproxyArn: arn:aws:acm:us-east-1:707767160287:certificate/520ede2f-fc82-4bb9-af96-4b4af7deabbd
guppy:
  esEndpoint: http://elasticsearch:9200
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  authFilterField: auth_resource_path
  configIndex: midrc_array-config
  indices:
    - index: midrc_case
      type: case
    - index: midrc_measurement
      type: measurement
    - index: midrc_annotation
      type: annotation
    - index: midrc_data_file
      type: data_file
    - index: midrc_imaging_study
      type: imaging_study
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/guppy
    tag: "2025.07"
indexd:
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  externalSecrets:
    serviceCreds: qa-midrc-indexd-service-creds
    dbcreds: qa-midrc-indexd-creds
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/indexd
    tag: "2025.07"
manifestservice:
  enabled: true
  externalSecrets:
    manifestserviceG3auto: qa-midrc-manifestservice-g3auto
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/manifestservice
    tag: "2025.07"
metadata:
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  externalSecrets:
    metadataG3auto: qa-midrc-metadata-g3auto
    dbcreds: qa-midrc-metadata-creds
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/metadata-service
    tag: "2025.07"
peregrine:
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/peregrine
    tag: "2025.07"
portal:
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  gitops:
    css: |
      :root {
        --primary-color: #421C52;
        --secondary-color: #421C52;

        --primary-color_light: #B7474D;
        --secondary-color_light: #90799b;

        --g3-color__bg-cloud: #F5F5F5;
        --g3-color__bg-coal: #4A4A4A;
        --g3-color__gray: #606060;
        --g3-color__lightgray: #9B9B9B;
        --g3-color__smoke: #D1D1D1;
        --g3-color__silver: #E7E7E7;
        --g3-color__black: #000000;
        --g3-color__white: #FFFFFF;

        --g3-primary-btn__color: var(--g3-color__white);
        --g3-primary-btn__bg-color: var(--secondary-color);
        --g3-primary-btn__bg-color--hover: var(--secondary-color_light);
        --g3-primary-btn__border-color: var(--g3-color__lightgray);
        --g3-primary-btn__border-color--hover: var(--g3-color__gray);
        --g3-primary-btn__border-color--active: var(--g3-color__lightgray);

        --g3-secondary-btn__color: var(--g3-color__white);
        --g3-secondary-btn__bg-color: var(--secondary-color);
        --g3-secondary-btn__bg-color--hover: var(--secondary-color_light);
        --g3-secondary-btn__border-color: var(--g3-color__lightgray);
        --g3-secondary-btn__border-color--hover: var(--g3-color__gray);
        --g3-secondary-btn__border-color--active: var(--g3-color__lightgray);

        --g3-default-btn__color: var(--g3-color__gray);
        --g3-default-btn__color--hover: var(--g3-color__black);
        --g3-default-btn__color--active: var(--g3-color_lightgray);
        --g3-default-btn__bg-color: var(--g3-color__white);
        --g3-default-btn__border-color: var(--g3-color__gray);
        --g3-default-btn__border-color--hover: var(--g3-color__black);

        --g3-disabled-btn__color: var(--g3-color__lightgray);
        --g3-disabled-btn__bg-color: var(--g3-color__white);
        --g3-disabled-btn__border-color: var(--g3-color__silver);

        --g3-dropdown-item__bg-color: var(--g3-color__gray);
        --g3-dropdown-item__color: var(--g3-color__white);
        --g3-dropdown-menu__border-color: var(--g3-color__gray);

        --g3-footer-color: var(--g3-color__bg-coal);
        --g3-font__medium-weight: 500;
        --g3-font__semi-bold-weight: 600;
      }

      /* Buttons */
      .data-dictionary__switch-button--active,
      .popup__title {
        background-color: var(--primary-color);
      }

      /* Nav Bars and Footer */
      .top-bar,
      .top-bar__header,
      .top-icon-button.body-typo {
        background-color: var(--secondary-color);
      }

      .top-bar__link {
        border-right: 2px solid #fff;
      }

      .nav-button:hover,
      .button-active {
        border-bottom: 3px solid var(--primary-color);
      }

      .nav-bar__link--right,
      .nav-bar__link--right:last-child {
        border: none;
      }

      .footer-container {
        background-color: var(--secondary-color);
      }

      .footer__nav {
        background-color: var(--secondary-color);
        align-items: center;
      }

      .footer__version-area {
        width: 300px;
      }

      .footer__logo-area {
        order: -1;
        width: auto;
      }

      /* Data Explorer */

      .aggregation-card .bucket-item .bucket-count {
        color: var(--secondary-color);
      }

      .aggregation-card input[type='checkbox']:checked {
        background: var(--secondary-color);
      }

      .g3-single-select-filter__checkbox:checked {
        background: var(--primary-color);
      }

      /* .input-range__track--active,
      .rc-slider-track,
      .g3-single-select-filter__count .g3-icon--under {
        background-color: var(--primary-color);
      } */

      /* Charts */

      tspan.special-number,
      .special-number,
      .form-special-number {
        color: var(--primary-color);
      }

      .special-number {
        fill: var(--primary-color);
      }

      .data-explorer__charts tspan.special-number,
      .data-explorer__charts .special-number,
      .data-explorer__charts .form-special-number {
        color: var(--secondary-color);
      }

      .data-explorer__charts .special-number {
        fill: var(--secondary-color);
      }

      /* MIDRC Index Changes */

      .index-button-bar {
        width: 100%;
        background-color: var(--g3-color__white);
      }

      .index-button-bar__thumbnail-button {
        background-color: inherit;
        border: none;
      }

      .index-button-bar__icon {
        filter: hue-rotate(45deg);
      }

      .index-button-bar__item, .index-button-bar__thumbnail-title {
        display: none;
      }

      @media screen and (max-width: 1170px) {
        .index-button-bar {
          padding: 0 10%;
        }
      }

      /* MIDRC Submission Page Changes */

      .project-dashboard__title {
        display: none;
      }

      .submission-header {
        display: none;
      }
    json: |
      {
        "gaTrackingId": "UA-119127212-1",
        "graphql": {
          "boardCounts": [
            {
              "graphql": "_case_count",
              "name": "Case",
              "plural": "Cases"
            },
            {
              "graphql": "_imaging_study_count",
              "name": "Imaging Study",
              "plural": "Imaging Studies"
            },
            {
              "graphql": "_ct_series_file_count",
              "name": "Computed Tomography (CT) Series",
              "plural": "Computed Tomography (CT) Series"
            },
            {
              "graphql": "_dx_series_file_count",
              "name": "Digital X-ray (DX) Series",
              "plural": "Digital X-ray (DX) Series"
            },
            {
              "graphql": "_cr_series_file_count",
              "name": "Computed Radiography (CR) Series",
              "plural": "Computed Radiography (CR) Series"
            },
            {
              "graphql": "_mr_series_file_count",
              "name": "Magnetic Resonance (MR) Series",
              "plural": "Magnetic Resonance (MR) Series"
            }
          ],
          "chartCounts": [],
          "projectDetails": "boardCounts"
        },
        "resourceBrowser": {
          "title": "Jupyter Notebook Tutorials",
          "public": true,
          "description": "The Jupyter notebooks contained in this notebook viewer pull data from various sources to generate and output useful tables, charts, graphs, and models. Each notebook is static, meaning the data being used by the notebooks is not updated in real time. Executable versions of these notebooks can be downloaded from <a href='https://github.com/MIDRC/tutorial_notebooks'> MIDRC's GitHub Repository</a>. If you’d like to browse the machine learning-related algorithms and code being developed by MIDRC, please visit <a href='https://midrc.org/algorithms'>the algorithms page</a> on our website.",
          "resources": [
            {
              "title": "Cohort Building Using LOINC Terms",
              "description": "This notebook demonstrates how to build a cohort of patients based on LOINC terms derived by harmonizing original DICOM study descriptions, modalities, and body parts examined using the LOINC playbook. Imaging study DICOM data element harmonization using the LOINC playbook is the result of an effort by MIDRC's Technology and Development Project 3b (TDP3b) and the Collaborative Research Project 12 (CRP-12). Links to the GitHub repository where the code for performing LOINC harmonization is maintained is included in the notebook.",
              "imageUrl": "/dashboard/Public/notebooks/Cohort_Building_Using_LOINC_Terms.png",
              "link": "/dashboard/Public/notebooks/Cohort_Building_Using_LOINC_Terms.html"
            },
            {
              "title": "Build a Patient Cohort and Access Chest CT Scans and Annotations",
              "description": "This notebook demonstrates how to build a cohort of MIDRC patients based on clinical and demographic data and then access all Chest CT scans and any related annotations.",
              "imageUrl": "/dashboard/Public/notebooks/Chest_CT_Images_for_Cohort.png",
              "link": "/dashboard/Public/notebooks/Chest_CT_Images_for_Cohort.html"
            },
            {
              "title": "Access Files for Specific Case IDs",
              "description": "This notebook demonstrates how to build a cohort of MIDRC patients based on clinical and demographic data and then obtain a file download manifest for x-ray and annotation files related to that cohort.",
              "imageUrl": "/dashboard/Public/notebooks/Access_Files_for_Specific_Case_IDs.png",
              "link": "/dashboard/Public/notebooks/Access_Files_for_Specific_Case_IDs.html"
            },
            {
              "title": "Cohort Selection Using Temporal COVID-19 Test Data",
              "description": "This tutorial demonstrates how to use the MIDRC data commons' APIs to access imaging study and COVID-19 test data, how to use temporal properties in those data to select a cohort of COVID-19 positive imaging studies, and how to access those image files using the Gen3 SDK.",
              "imageUrl": "/dashboard/Public/notebooks/Cohort_selection_Using_MIDRC_Temporal_COVID_Test_Data.png",
              "link": "/dashboard/Public/notebooks/Cohort_selection_Using_MIDRC_Temporal_COVID_Test_Data.html"
            },
            {
              "title": "Querying and Accessing MIDRC Data",
              "description": "This notebook is intended to demonstrate a variety of ways to access file objects and structured data, also known as metadata, in the MIDRC Data Commons using MIDRC APIs.",
              "imageUrl": "/dashboard/Public/notebooks/Querying_and_Accessing_MIDRC_Data.png",
              "link": "/dashboard/Public/notebooks/Querying_and_Accessing_MIDRC_Data.html"
            },
            {
              "title": "Exploring MIDRC CT Scans",
              "description": "In this demo we will review how to import MIDRC imaging data, how to convert CT scan images from dicom (dcm) formats to png and jpeg formats, and how to view these CT scan images. This demo will also show how to extract file and patient metadata from the header of dicom (dcm) files.",
              "imageUrl": "/dashboard/Public/notebooks/MIDRC_CT_Scan.png",
              "link": "/dashboard/Public/notebooks/MIDRC_CT_Scan.html"
            },
            {
              "title": "MIDRC Open-R1 Clinical Data Analysis",
              "description": "In this notebook we will visualize the distribution of subjects accross a variety demographics and their COVID-19 status in the Open-R1 dataset from The Medical Imaging and Data Resource Center.",
              "imageUrl": "/dashboard/Public/notebooks/MIDRC_Clinical_Data.png",
              "link": "/dashboard/Public/notebooks/MIDRC_Clinical_Data.html"
            },
            {
              "title": "Build Balanced Cohorts of Severe and Mild COVID-19 Cases",
              "description": "This notebook demonstrates how to build a cohort of severe COVID-19 cases using patient clinical data and AI research-based annotations in the MIDRC data commons. Our goal is to download structured data and files for 2 related cohorts: 1) severe COVID cases and 2) a control cohort of non-severe COVID cases. Additionally, we want the cohorts to be somewhat balanced and matched in terms of the demographics: age, sex, race, and ethnicity.",
              "imageUrl": "/dashboard/Public/notebooks/build_a_cohort_of_severe_covid_19_cases.png",
              "link": "/dashboard/Public/notebooks/build_a_cohort_of_severe_covid_19_cases.html"
            },
            {
              "title": "Cohort Building Using Queries of the MIDRC Data Commons",
              "description": "This notebook briefly demonstrates how to use the MIDRC open APIs to build a cohort of MIDRC imaging studies using patient clinical data and AI-research-based annotations in the MIDRC data commons and then access and view the X-ray image files associated with those imaging studies.",
              "imageUrl": "/dashboard/Public/notebooks/MIDRC_Cohort_Building-DLL_RSNA_2023.png",
              "link": "/dashboard/Public/notebooks/MIDRC_Cohort_Building-DLL_RSNA_2023.html"
            }
          ]
        },
        "useArboristUI": true,
        "showArboristAuthzOnProfile": true,
        "showFenceAuthzOnProfile": true,
        "hideSubmissionIfIneligible": true,
        "componentToResourceMapping": {
          "Workspace": {
            "resource": "/workspace",
            "method": "access",
            "service": "jupyterhub"
          },
          "Analyze Data": {
            "resource": "/workspace",
            "method": "access",
            "service": "jupyterhub"
          },
          "Query": {
            "resource": "/query_page",
            "method": "access",
            "service": "query_page"
          },
          "Query Data": {
            "resource": "/query_page",
            "method": "access",
            "service": "query_page"
          }
        },
        "components": {
          "appName": "The Medical Imaging and Data Resource Center Commons",
          "index": {
            "introduction": {
              "heading": "MIDRC Data Commons",
              "text": "The Medical Imaging & Data Resource Center (MIDRC) Data Commons supports the management, analysis and sharing of medical imaging data for the improvement of patient outcomes.\nThe data in MIDRC are open access in order to foster machine learning innovation through data sharing and include in addition to imaging files, patient demographic data, COVID-19 test results and other clinical data, harmonized study descriptions utilizing the LOINC playbook, and image DICOM tags for purposes of data filtering and selecting cohorts for analysis.",
              "link": "/submission"
            },
            "buttons": [
              {
                "name": "Explore Data",
                "icon": "data-explore",
                "body": "Use the Exploration tool for cohort building via faceted search and downloading of subsets of data from the MIDRC Data Commons.",
                "link": "/explorer",
                "label": "Explore Data"
              },
              {
                "name": "Data Dictionary",
                "icon": "data-field-define",
                "body": "The MIDRC Data Commons employs a data model to power queries and data submissions. Study the dictionary to send GraphQL queries or format your data submissions.",
                "link": "/DD",
                "label": "View Dictionary"
              },
              {
                "name": "Query Data",
                "icon": "data-access",
                "body": "Search and download subsets of data from the MIDRC Data Commons using GraphQL queries.",
                "link": "/query",
                "label": "Query Data"
              },
              {
                "name": "Analyze Data",
                "icon": "data-analyze",
                "body": "Perform analysis on the MIDRC Data Commons data using Jupyter Notebooks.",
                "link": "/workspace",
                "label": "Run Analysis"
              }
            ],
            "homepageChartNodes": [
              {
                "node": "case",
                "name": "Cases"
              },
              {
                "node": "imaging_study",
                "name": "Imaging Studies"
              },
              {
                "node": "ct_series_file",
                "name": "CT Series"
              },
              {
                "node": "dx_series_file",
                "name": "DX Series"
              },
              {
                "node": "cr_series_file",
                "name": "CR Series"
              },
              {
                "node": "mr_series_file",
                "name": "MR Series"
              }
            ]
          },
          "systemUse": {
            "systemUseTitle": "Data Use Agreement for Academic and Institutional Users",
            "systemUseText": [
              "Please see the below two Data Use Agreements: the first one is for Academic and Institutional users for non-commercial use; the second agreement is for commercial use.",
              "",
              "",
              "Data Use Agreement - Non-Commercial Research Use Only",
              "This Data Use Agreement for Academic and Institutional Users (this “Agreement”) is by and between you and the University of Chicago (the “University”) and governs your access to and use of the deidentified imaging and associated demographic and clinical data provided to you by the University (“MIDRC Data”). By accessing, using, or downloading any MIDRC Data, you are agreeing to be bound by the terms and conditions of this Agreement.",
              "1. The University is the legal entity that hosts Medical Imaging and Data Resource Center (MIDRC) data",
              "2. The University grants you a limited, personal, worldwide, non-exclusive, non-transferable, royalty-free license to view and use the MIDRC Data solely for your personal, Non-Commercial Research Purposes. Any commercial use, sale, or other monetization is prohibited. “Non-Commercial Research Purposes” means academic research or other not-for-profit scholarly purposes which are undertaken at a non-profit or government institution and publishing in connection therewith.",
              "3. Other than the rights granted herein, the University retains all rights, title, and interest in the MIDRC Dataset.",
              "4. You will use the MIDRC Data only in compliance with all applicable laws and regulations.",
              "5. You may make a verbatim copy of the MIDRC Data for personal, non-commercial research use. If another user within your organization wishes to use the MIDRC Data, they must separately download the data set and enter into an Agreement directly with the University.",
              "6. You may not distribute, publish, or reproduce a copy of any portion or all of the MIDRC Data to others without specific prior written permission from the University.",
              "7. You will promptly report to the University in writing any unauthorized access or use of the MIDRC Data",
              "8. You will register with and provide current contact information to the University. By accessing, using, or downloading the MIDRC Data, you consent to be contacted by the University. The University may use, and you hereby grant the University a non-exclusive, worldwide, perpetual, irrevocable license to use, any data you provide to the University, including any personally identifiable information.",
              "9. You will acknowledge your use of MIDRC Data in all oral or written presentations, disclosures, or publications arising from your use of the MIDRC Data",
              "10. You may not modify, reverse engineer, decompile, or create derivative works from the MIDRC Data. For avoidance of doubt, users may create research results, including any data analyses, results of algorithm validations, annotations and overlays, and outcomes or evaluations using the MIDRC Data. The University will have no right, title, or interest in any such research results. You must not remove or alter any copyright or other proprietary notices in the MIDRC Data. You are encouraged to submit any annotations or overlays created using the MIDRC data.",
              "11. The MIDRC Data has not been reviewed or approved by the Food and Drug Administration, and is for non-clinical, research use only. In no event shall data or images generated through the use of the MIDRC Data be used or relied upon in the diagnosis or provision of patient care",
              "12. THE MIDRC DATA IS PROVIDED ON AN ”AS IS”, “WHERE IS” BASIS. THE UNIVERSITY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NON INFRINGEMENT. THE UNIVERSITY WILL HAVE NO LIABILITY WHATSOEVER ARISING FROM YOUR ACCESS OR USE OF THE MIDRC DATA",
              "13. You will not make any attempt to re-identify any individual from the MIDRC Data. In the event that you identify any person whose data is included in the MIDRC Data, you will promptly delete the data and notify the University in writing.",
              "14. The University may terminate this Agreement at any time upon notice to you. The University shall have no liability in the event of any such termination. Upon such termination, the University may direct that you immediately return or destroy all copies of any MIDRC Data and, upon the University’s request, you will certify the foregoing to the University in writing.",
              "",
              "",
              "DATA USE AGREEMENT – COMMERCIAL USE PERMITTED",
              "This Data Use Agreement (this “Agreement”) is by and between you or the entity you represent (“you”) and the University of Chicago (the “University”) and governs your access to and use of the deidentified imaging and associated demographic and clinical data provided to you by the University (“MIDRC Data”). By accessing, using, or downloading any MIDRC Data, you are agreeing to be bound by the terms and conditions of this Agreement. If you are entering into this Agreement for an entity, such as the company you work for, you represent and warrant that you have legal authority to bind that entity",
              "1. The University is the legal entity that hosts Medical Imaging and Data Resource Center (MIDRC) data",
              "2. The University grants you a limited, personal, worldwide, non-exclusive, non-transferable, royalty-free license to view and use the MIDRC Data",
              "3. Other than the rights granted herein, the University retains all rights, title, and interest in the MIDRC Dataset.",
              "4. You will use the MIDRC Data only in compliance with all applicable laws and regulations",
              "5. You may make a verbatim copy of the MIDRC Data.",
              "6. You may not distribute any portion or all of the MIDRC Data to others without specific prior written permission from the University.",
              "7. You will promptly report to the University in writing any unauthorized access or use of the MIDRC Data.",
              "8. You will register with and provide current contact information to the University. By accessing, using, or downloading the MIDRC Data, you consent to be contacted by the University. The University may use, and you hereby grant the University a non-exclusive, worldwide, perpetual, irrevocable license to use, any data you provide to the University, including any personally identifiable information.",
              "9. You will acknowledge your use of MIDRC Data in all oral or written presentations, disclosures, or publications arising from your use of the MIDRC Data.",
              "10. You may not modify, reverse engineer, decompile, or create derivative works from the MIDRC Data. For avoidance of doubt, users may create research results, including any data analyses, results of algorithm validations, annotations and overlays, and outcomes or evaluations using the MIDRC Data. The University will have no right, title, or interest in any such research results. You must not remove or alter any copyright or other proprietary notices in the MIDRC Data. You are encouraged to submit any annotations or overlays created using the MIDRC data.",
              "11. The MIDRC Data has not been reviewed or approved by the Food and Drug Administration, and is for non-clinical, research use only. In no event shall data or images generated through the use of the MIDRC Data be used or relied upon in the diagnosis or provision of patient care.",
              "12. THE MIDRC DATA IS PROVIDED ON AN ”AS IS”, “WHERE IS” BASIS. THE UNIVERSITY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NON-INFRINGEMENT. THE UNIVERSITY WILL HAVE NO LIABILITY WHATSOEVER ARISING FROM YOUR ACCESS OR USE OF THE MIDRC DATA, INCLUDING WITHOUT LIMITATION ANY LIABILITY ARISING FROM LOST PROFITS, COSTS OF PROCURING SUBSTITUTE GOODS OR SERVICES, LOST BUSINESS, ENHANCED DAMAGES FOR INTELLECTUAL PROPERTY INFRINGEMENT, OR FOR ANY INDIRECT, INCIDENTAL, CONSEQUENTIAL, PUNITIVE, OR OTHER SPECIAL DAMAGES SUFFERED BY YOU OR YOUR SUBLICENSEES, JOINT VENTURES, OR AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT AND NON-EXCLUSIVE LICENSES GRANTED THEREUNDER FOR ALL CAUSES OF ACTION OF ANY KIND (INCLUDING TORT, CONTRACT, NEGLIGENCE, STRICT LIABILITY AND BREACH OF WARRANTY) EVEN IF THE UNIVERSITY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. ALSO, UNIVERSITY WILL NOT BE LIABLE FOR ANY DIRECT DAMAGES SUFFERED BY YOU OR YOUR SUBLICENSEES, JOINT VENTURES, OR AFFILIATES ARISING OUT OF OR RELATED TO YOUR USE OF THE MIDRC DATA.",
              "13. You will defend, indemnify, and hold harmless the University, its affiliates and licensors, and each of their respective employees, officers, directors, trustees, and representatives (“Representatives”) from and against any claims, damages, losses, liabilities, costs, and expenses (including reasonable attorneys’ fees and consultants’ fees) arising out of or relating to any third-party claim to the extent concerning or arising out of: (a) your use of the MIDRC Data; (b) breach of this Agreement or violation of applicable law by you; or (c) any allegation that your use of the MIDRC Data infringes or otherwise violates the patent, copyright, or other intellectual property rights of any third party.",
              "14. You will not make any attempt to re-identify any individual from the MIDRC Data. In the event that you identify any person whose data is included in the MIDRC Data, you will promptly notify the University in writing.",
              "15. The University may terminate this Agreement at any time upon notice to you. The University shall have no liability in the event of any such termination. Upon such termination, the University may direct that you immediately return or destroy all copies of any MIDRC Data and, upon the University’s request, you will certify the foregoing to the University in writing."
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
    sponsors:
      - 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
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/data-portal
    tag: "2025.07"
revproxy:
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/nginx
    tag: "2025.07"
  ingress:
    aws:
      group: devplanetv2
      sslPolicy: ELBSecurityPolicy-TLS13-1-2-FIPS-2023-04
sheepdog:
  autoscaling:
    enabled: true
    maxReplicas: 4
    minReplicas: 1
    targetCPUUtilizationPercentage: 40
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/sheepdog
    tag: "2025.07"
  externalSecrets:
    dbcreds: qa-midrc-sheepdog-creds
spark:
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/gen3-spark
    tag: "2025.07"
ssjdispatcher:
  enabled: true
  externalSecrets:
    credsFile: qa-midrc-ssjdispatcher-creds
    dbcreds: qa-midrc-ssjdispatcher-creds
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/ssjdispatcher
    tag: "2025.07"
  indexing: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/indexs3client:2024.09
tube:
  enabled: true
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/tube
    tag: "2025.07"
wts:
  enabled: true
  externalSecrets:
    wtsG3auto: qa-midrc-wts-g3auto
    dbcreds: qa-midrc-wts-creds
  image:
    repository: 707767160287.dkr.ecr.us-east-1.amazonaws.com/gen3/workspace-token-service
    tag: "2025.07"
etl:
  etlMapping:
    mappings:
      - name: midrc_case
        doc_type: case
        type: aggregator
        root: case
        props:
          - name: project_id
          - name: submitter_id
          - name: sex
          - name: race
          - name: age_at_index
          - name: index_event
          - name: zip
          - name: covid19_positive
          - name: ethnicity
        aggregated_props:
          - name: _imaging_studies_count
            path: imaging_studies
            fn: count
          - name: _ct_series_file_count
            path: imaging_studies.ct_series_files
            fn: count
          - name: _cr_series_file_count
            path: imaging_studies.cr_series_files
            fn: count
          - name: _dx_series_file_count
            path: imaging_studies.dx_series_files
            fn: count
          - name: _mr_series_file_count
            path: imaging_studies.mr_series_files
            fn: count
        parent_props:
          - path: datasets[dataset_submitter_id:submitter_id,license,data_url_doi,data_contributor]
        nested_props:
          - name: case_annotations
            path: annotations
            props:
              - name: annotation_method
              - name: annotator_id
          - name: imaging_study_annotations
            path: imaging_studies.annotations
            props:
              - name: airspace_disease_grading
              - name: class_covid19_pneumonia
              - name: annotation_name
              - name: midrc_mRALE_score
              - name: annotation_method
              - name: annotator_id
              - name: instance_uids
          - name: measurements
            path: measurements
            props:
              - name: test_days_from_index
              - name: test_method
              - name: test_name
              - name: test_result_text
          - name: medications
            path: medications
            props:
              - name: days_to_medication_end
              - name: days_to_medication_start
              - name: dose_sequence_number
              - name: medication_code
              - name: medication_code_system
              - name: medication_manufacturer
              - name: medication_name
              - name: medication_type
          - name: conditions
            path: conditions
            props:
              - name: condition_code
              - name: condition_code_system
              - name: condition_name
              - name: days_to_condition_end
              - name: days_to_condition_start
          - name: procedures
            path: procedures
            props:
              - name: breathing_support_type
              - name: days_to_procedure_end
              - name: days_to_procedure_start
              - name: procedure_name
          - name: imaging_studies
            path: imaging_studies
            props:
              - name: age_at_imaging
              - name: body_part_examined
              - name: days_from_study_to_neg_covid_test
              - name: days_from_study_to_pos_covid_test
              - name: days_to_study
              - name: image_data_modified
              - name: loinc_code
              - name: loinc_contrast
              - name: loinc_long_common_name
              - name: loinc_method
              - name: loinc_system
              - name: study_description
              - name: study_modality
              - name: study_year
              - name: study_uid
        joining_props:
          - index: data_file
            join_on: _case_id
            props:
              - name: object_id
                src: object_id
                fn: set
              - name: data_format
                src: data_format
                fn: set
              - name: data_type
                src: data_type
                fn: set
              - name: data_category
                src: data_category
                fn: set
              - name: data_file_image_data_modified
                src: image_data_modified
                fn: set
              - name: data_file_image_data_modification_name
                src: image_data_modification_name
                fn: set
              - name: data_file_image_data_modification_method
                src: image_data_modification_method
                fn: set
              - name: data_file_count
                src: _data_file_id
                fn: count
      - name: midrc_measurement
        doc_type: measurement
        type: aggregator
        root: measurement
        props:
          - name: project_id
          - name: submitter_id
          - name: case_ids
          - name: test_days_from_index
          - name: test_method
          - name: test_name
          - name: test_result_text
        parent_props:
          - path: cases.datasets[dataset_submitter_id:submitter_id,license,data_url_doi,data_contributor]
      - name: midrc_annotation
        doc_type: annotation
        type: aggregator
        root: annotation
        props:
          - name: project_id
          - name: submitter_id
          - name: case_ids
          - name: airspace_disease_grading
          - name: class_covid19_pneumonia
          - name: annotation_name
          - name: midrc_mRALE_score
          - name: annotation_method
          - name: annotator_id
          - name: instance_uids
      - name: midrc_imaging_study
        doc_type: imaging_study
        type: aggregator
        root: imaging_study
        props:
          - name: project_id
          - name: submitter_id
          - name: case_ids
          - name: age_at_imaging
          - name: body_part_examined
          - name: days_from_study_to_neg_covid_test
          - name: days_from_study_to_pos_covid_test
          - name: days_to_study
          - name: image_data_modified
          - name: loinc_code
          - name: loinc_contrast
          - name: loinc_long_common_name
          - name: loinc_method
          - name: loinc_system
          - name: study_description
          - name: study_modality
          - name: study_year
          - name: study_year_shifted
          - name: study_uid
        nested_props:
          - name: imaging_study_annotations
            path: annotations
            props:
              - name: airspace_disease_grading
              - name: class_covid19_pneumonia
              - name: annotation_name
              - name: midrc_mRALE_score
              - name: annotation_method
              - name: annotator_id
              - name: instance_uids
        aggregated_props:
          - name: _cr_series_file_count
            path: cr_series_files
            fn: count
          - name: _ct_series_file_count
            path: ct_series_files
            fn: count
          - name: _dx_series_file_count
            path: dx_series_files
            fn: count
          - name: _mr_series_file_count
            path: mr_series_files
            fn: count
        parent_props:
          - path: cases[sex,race,age_at_index,index_event,zip,covid19_positive,ethnicity].datasets[dataset_submitter_id:submitter_id,license,data_url_doi,data_contributor]
        joining_props:
          - index: data_file
            join_on: _imaging_study_id
            props:
              - name: object_id
                src: object_id
                fn: set
              - name: data_format
                src: data_format
                fn: set
              - name: data_type
                src: data_type
                fn: set
              - name: data_category
                src: data_category
                fn: set
              - name: data_file_source_node
                src: source_node
                fn: set
              - name: data_file_annotation_name
                src: annotation_name
                fn: set
              - name: data_file_annotation_method
                src: annotation_method
                fn: set
              - name: data_file_image_data_modified
                src: image_data_modified
                fn: set
              - name: data_file_image_data_modification_name
                src: image_data_modification_name
                fn: set
              - name: data_file_image_data_modification_method
                src: image_data_modification_method
                fn: set
      - name: midrc_data_file
        doc_type: data_file
        type: collector
        root: None
        category: data_file
        props:
          - name: source_node
          - name: project_id
          - name: submitter_id
          - name: series_uid
          - name: case_ids
          - name: object_id
          - name: md5sum
          - name: file_name
          - name: file_size
          - name: data_format
          - name: data_type
          - name: data_category
          - name: annotation_method
          - name: annotation_name
          - name: annotator_id
          - name: instance_uids
          - name: software_versions
          - name: acquisition_type
          - name: angio_flag
          - name: contrast_bolus_agent
          - name: convolution_kernel
          - name: detector_type
          - name: diffusion_b_value
          - name: diffusion_gradient_orientation
          - name: echo_number
          - name: echo_time
          - name: echo_train_length
          - name: exposure_modulation_type
          - name: image_data_modified
          - name: image_data_modification_method
          - name: image_data_modification_name
          - name: image_type
          - name: imaged_nucleus
          - name: imager_pixel_spacing
          - name: lossy_image_compression
          - name: manufacturer
          - name: manufacturer_model_name
          - name: modality
          - name: number_of_instances
          - name: number_of_temporal_positions
          - name: patient_position
          - name: pixel_spacing
          - name: radiopharmaceutical
          - name: repetition_time
          - name: scan_options
          - name: sequence_variant
          - name: series_description
          - name: slice_thickness
          - name: software_version
          - name: spacing_between_slices
          - name: spatial_resolution
          - name: transducer_type
          - name: view_position
        injecting_props:
          dataset:
            props:
              - name: _dataset_id
                src: id
                fn: set
              - name: dataset_submitter_id
                src: submitter_id
                fn: set
              - name: license
                src: license
                fn: set
              - name: data_url_doi
                src: data_url_doi
                fn: set
              - name: data_contributor
                src: data_contributor
                fn: set
          annotation:
            props:
              - name: _annotation_id
                src: id
                fn: set
          case:
            props:
              - name: _case_id
                src: id
                fn: set
              - name: age_at_index
                src: age_at_index
                fn: set
              - name: covid19_positive
                src: covid19_positive
                fn: set
              - name: ethnicity
                src: ethnicity
                fn: set
              - name: index_event
                src: index_event
                fn: set
              - name: race
                src: race
                fn: set
              - name: sex
                src: sex
                fn: set
              - name: zip
                src: zip
                fn: set
          imaging_study:
            props:
              - name: _imaging_study_id
                src: id
                fn: set
              - name: age_at_imaging
                src: age_at_imaging
                fn: set
              - name: body_part_examined
                src: body_part_examined
                fn: set
              - name: days_from_study_to_neg_covid_test
                src: days_from_study_to_neg_covid_test
                fn: set
              - name: days_from_study_to_pos_covid_test
                src: days_from_study_to_pos_covid_test
                fn: set
              - name: days_to_study
                src: days_to_study
                fn: set
              - name: study_description
                src: study_description
                fn: set
              - name: study_modality
                src: study_modality
                fn: set
              - name: study_year
                src: study_year
                fn: set
              - name: study_year_shifted
                src: study_year_shifted
                fn: set
              - name: study_uid
                src: study_uid
                fn: set
              - name: loinc_code
                src: loinc_code
                fn: set
              - name: loinc_contrast
                src: loinc_contrast
                fn: set
              - name: loinc_long_common_name
                src: loinc_long_common_name
                fn: set
              - name: loinc_method
                src: loinc_method
                fn: set
              - name: loinc_system
                src: loinc_system
                fn: set