diff --git a/midrcprod/staging.midrc.org/values/portal/gitops.json b/midrcprod/staging.midrc.org/values/portal/gitops.json
index df27c4df5..af17cce31 100644
--- a/midrcprod/staging.midrc.org/values/portal/gitops.json
+++ b/midrcprod/staging.midrc.org/values/portal/gitops.json
@@ -1,2076 +1,865 @@
{
- "gaTrackingId": "UA-119127212-1",
- "grafanaFaroConfig": {
- "grafanaFaroEnable": true,
- "grafanaFaroNamespace": "midrcstaging"
- },
+ "argoTemplate": "gwas-template",
"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": "CT Series",
- "plural": "CT Series"
- },
- {
- "graphql": "_dx_series_file_count",
- "name": "DX Series",
- "plural": "DX Series"
- },
- {
- "graphql": "_cr_series_file_count",
- "name": "CR Series",
- "plural": "CR Series"
- },
- {
- "graphql": "_mr_series_file_count",
- "name": "MR Series",
- "plural": "MR Series"
- },
- {
- "graphql": "_dicom_annotation_file_count",
- "name": "DICOM Annotation File",
- "plural": "DICOM Annotation Files"
- }
- ],
- "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 MIDRC's GitHub Repository. If you’d like to browse the machine learning-related algorithms and code being developed by MIDRC, please visit the algorithms page 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"
- }
- ]
+ "boardCounts": [
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+ "chartCounts": [
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+ "projectDetails": "boardCounts"
},
"useArboristUI": true,
"showArboristAuthzOnProfile": true,
- "showFenceAuthzOnProfile": true,
- "hideSubmissionIfIneligible": true,
+ "showFenceAuthzOnProfile": false,
"componentToResourceMapping": {
- "Query": {
- "resource": "/query_page",
- "method": "access",
- "service": "query_page"
- }
+ "Workspace": {
+ "resource": "/workspace",
+ "method": "access",
+ "service": "jupyterhub"
+ },
+ "Query": {
+ "resource": "/query_page",
+ "method": "access",
+ "service": "query_page"
+ },
+ "Send Queries": {
+ "resource": "/query_page",
+ "method": "access",
+ "service": "query_page"
+ },
+ "Data Dictionary": {
+ "resource": "/dictionary_page",
+ "method": "access",
+ "service": "dictionary_page"
+ },
+ "Dictionary": {
+ "resource": "/dictionary_page",
+ "method": "access",
+ "service": "dictionary_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": "Workspace",
- "icon": "data-analyze",
- "body": "Perform analysis on the MIDRC Data Commons data using Jupyter Notebooks.",
- "link": "/workspace",
- "label": "Run Analysis"
- }
- ],
- "homepageChartNodes": [
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- "node": "case",
- "name": "Cases"
- },
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- "node": "imaging_study",
- "name": "Imaging Studies"
- },
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- "node": "ct_series_file",
- "name": "CT Series"
- },
- {
- "node": "dx_series_file",
- "name": "DX Series"
- },
- {
- "node": "cr_series_file",
- "name": "CR Series"
- },
- {
- "node": "radiology_report",
- "name": "Radiology Reports"
- },
- {
- "node": "mr_series_file",
- "name": "MR Series"
- }
- ]
+ "appName": "BloodPAC Metadata Submission Portal",
+ "index": {
+ "introduction": {
+ "heading": "BloodPAC Data Commons",
+ "text": "The Blood Profiling Atlas in Cancer (BloodPAC) supports the management, analysis and sharing of liquid biopsy data for the oncology research community and aims to accelerate discovery and development of therapies, diagnostic tests, and other technologies for cancer treatment and prevention. The data commons supports cross-project analyses by harmonizing data from different projects through the collaborative development of a data dictionary, providing an API for data queries and download, and providing a cloud-based analysis workspace with rich tools and resources.",
+ "link": "/submission"
},
- "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."
- ],
- "displayUseMsg": "cookie",
- "expireUseMsgDays": 365,
- "showOnlyOnLogin": true
- },
- "navigation": {
- "items": [
- {
- "name": "Discovery",
- "link": "/discovery",
- "icon": "query",
- "tooltip": "Dataset discovery"
- },
- {
- "name": "Exploration",
- "link": "/explorer",
- "icon": "exploration",
- "tooltip": "The Exploration Page enables discovery of the data at the subject level and features a cohort builder."
- },
- {
- "name": "Dictionary",
- "link": "/DD",
- "icon": "dictionary",
- "tooltip": "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.",
- "color": "#a2a2a2"
- },
- {
- "name": "Query",
- "link": "/query",
- "icon": "query",
- "tooltip": "Query the databases using GraphQL."
- },
- {
- "name": "Example Analysis",
- "link": "/resource-browser",
- "icon": "bar-chart",
- "tooltip": "Learn how to use Jupyter Notebooks to explore and visualize data discovered in the MIDRC Data Commons by running a static tutorial notebook, or use one of these examples as a launching point for your own custom analysis.",
- "color": "#a2a2a2"
- },
- {
- "name": "Workspace",
- "link": "/workspace",
- "icon": "workspace",
- "tooltip": "The Workspace provides a secure cloud environment featuring Jupyter Notebooks and RStudio."
- }
-
- ]
+ "homepageChartNodes": [{
+ "node": "subject",
+ "name": "Subjects"
+ }
+ ],
+ "buttons": [{
+ "name": "Data Dictionary",
+ "icon": "data-field-define",
+ "body": "The BloodPAC 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": "Learn more"
+ },
+ {
+ "name": "Submit Data",
+ "icon": "data-submit",
+ "body": "Browse the list of submitted data projects, or find your project and submit data.",
+ "link": "/submission",
+ "label": "Submit data"
+ },
+ {
+ "name": "Explore Data",
+ "icon": "data-files",
+ "body": "The Exploration app enables faceted search for cohort building, getting file download manifests, and browsing data across projects.",
+ "link": "/explorer",
+ "label": "Exploration"
+ },
+ {
+ "name": "Send Queries",
+ "icon": "data-access",
+ "body": "Build and send your own custom GraphQL queries to the database to pinpoint specific data.",
+ "link": "/query",
+ "label": "Send Queries"
+ },
+ {
+ "icon": "analysis",
+ "link": "/analysis",
+ "color": "#a2a2a2",
+ "name": "Apps"
+ }
+ ]
+ },
+ "navigation": {
+ "title": "BloodPAC Data Commons",
+ "items": [
+ {
+ "icon": "query",
+ "link": "/discovery",
+ "name": "Discovery",
+ "tooltip": "Use free-text search and tags to rapidly find relevant studies, discover new datasets across multiple resources, and easily export selected data files to the analysis workspace."
+ },
+ {
+ "icon": "exploration",
+ "link": "/explorer",
+ "color": "#a2a2a2",
+ "name": "Exploration"
+ },
+ {
+ "icon": "query",
+ "link": "/study-viewer/clinical_trials",
+ "color": "#a2a2a2",
+ "name": "Study Viewer"
+ },
+ {
+ "icon": "workspace",
+ "link": "/workspace",
+ "color": "#a2a2a2",
+ "name": "Workspace"
+ },
+ {
+ "icon": "dictionary",
+ "link": "/DD",
+ "color": "#a2a2a2",
+ "name": "Dictionary"
+ },
+ {
+ "icon": "analysis",
+ "link": "/analysis",
+ "color": "#a2a2a2",
+ "name": "Apps"
+ },
+ {
+ "icon": "query",
+ "link": "/query",
+ "color": "#a2a2a2",
+ "name": "Query"
+ },
+ {
+ "icon": "profile",
+ "link": "/identity",
+ "color": "#a2a2a2",
+ "name": "Profile"
+ }
+ ]
+ },
+ "topBar": {
+ "items": [{
+ "link": "https://bloodpac.org/",
+ "name": "About"
+ },
+ {
+ "icon": "upload",
+ "link": "/submission",
+ "name": "Submit Data"
+ },
+ {
+ "link": "main@example.org",
+ "name": "Email Support"
+ }
+ ],
+ "useProfileDropdown": false
+ },
+ "login": {
+ "title": "BloodPAC Data Commons",
+ "subTitle": "Explore, Analyze, and Share Data",
+ "text": "This website combines liquid biopsy data from academic, government, and industry partners and aims to accelerate discovery and development of therapies, diagnostic tests, and other technologies for the treatment and prevention of cancer.",
+ "contact": "If you have any questions about access or the registration process, please contact ",
+ "email": "main@example.org"
+ },
+ "certs": {
+ "security_quiz": {
+ "hasCorrectAnswers": true,
+ "title": "BloodPAC User agreement",
+ "description": "",
+ "questions": [{
+ "name": "",
+ "question": "NOTICE: To protect the system from unauthorized use and to ensure that the system is functioning, activities on this system are monitored and recorded and subject to audit. Use of this system is express consent to such monitoring and recording. Any unauthorized access or use of this system is prohibited. You may only use this system if you have been designated as an Authenticated Individual by your company or institution. You may not use the system in any way that is inconsistent with the agreements between CCSR and your company or institution. Please pay particular attention to the restrictions on controlled access data and transfer it in an approved secure manner.",
+ "options": ["I agree"],
+ "answer": 0,
+ "hint": "Click on I agree"
+ }]
+ }
+ }
+ },
+ "featureFlags": {
+ "explorer": true,
+ "analysis": true,
+ "explorerPublic": true,
+ "discovery": true,
+ "discoveryUseAggMDS": true,
+ "studyRegistration": true
+ },
+ "analysisTools": [
+ {
+ "title": "OHDSI Atlas",
+ "description": "Use this App for cohort creation. These will be automatically populated in the Gen3 GWAS App",
+ "applicationUrl": "https://atlas.qa-mickey.planx-pla.net/atlas/",
+ "image": "/custom/sponsors/gitops-sponsors/atlas-logo.png"
+ },
+ {
+ "appId": "GWASUIApp",
+ "title": "Gen3 GWAS",
+ "description": "Use this App to perform high throughput GWAS on Million Veteran Program (MVP) data, using the University of Washington Genesis pipeline",
+ "image": "/src/img/analysis-icons/gwas.svg",
+ "needsTeamProject": true
+ },
+ {
+ "appId": "GWASResults",
+ "title": "GWAS Results",
+ "description": "Use this App to view status & results of submitted workflows",
+ "image": "/src/img/analysis-icons/gwasResults.svg",
+ "needsTeamProject": true
+ }
+ ],
+ "discoveryConfig": {
+ "features": {
+ "advSearchFilters": {
+ "enabled": false,
+ "field": "advSearchFilters",
+ "filters": [
+ { "key": "Research Focus Area" },
+ { "key": "Administering IC(s)" },
+ { "key": "Simulated vs. Real Data" },
+ { "key": "Year Grant Awarded" },
+ { "key": "Study Description" }
+ ]
},
- "topBar": {
- "items": [
- {
- "link": "https://www.midrc.org/",
- "name": "About"
- },
- {
- "link": "https://staging.midrc.org/dashboard/Public/documentation/Gen3_MIDRC_GetStarted.pdf",
- "name": "Get Started"
- },
- {
- "link": "https://www.midrc.org/midrc-acknowledgements",
- "name": "Cite MIDRC"
- },
- {
- "link": "https://staging.midrc.org/dashboard/Public/documentation/DUA.html",
- "name": "DUA"
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- "imager_pixel_spacing",
- "lossy_image_compression",
- "manufacturer",
- "manufacturer_model_name",
- "modality",
- "number_of_instances",
- "number_of_temporal_positions",
- "patient_position",
- "pixel_spacing",
- "radiopharmaceutical",
- "repetition_time",
- "scan_options",
- "sequence_variant",
- "series_description",
- "slice_thickness",
- "software_version",
- "spacing_between_slices",
- "spatial_resolution",
- "transducer_type",
- "view_position",
- "study_description",
- "age_at_imaging",
- "days_to_study",
- "study_year",
- "study_year_shifted",
- "days_from_study_to_pos_covid_test",
- "days_from_study_to_neg_covid_test",
- "license",
- "data_url_doi",
- "data_contributor",
- "loinc_code",
- "loinc_contrast",
- "loinc_long_common_name",
- "loinc_method",
- "loinc_system",
- "covid19_positive",
- "age_at_index",
- "index_event",
- "sex",
- "race",
- "zip",
- "data_format",
- "data_category",
- "data_type",
- "image_data_modified",
- "image_data_modification_name",
- "image_data_modification_method",
- "annotation_method",
- "annotation_name",
- "annotator_id",
- "software_versions",
- "series_uid",
- "study_uid",
- "case_ids",
- "object_id",
- "dicom_header_file_guid",
- "submitter_id",
- "project_id"
- ],
- "dicomViewerId": "submitter_id",
- "dicomViewerUrl": "ohif-viewer",
- "linkFields": [
- "submitter_id",
- "license",
- "data_url_doi"
- ]
- },
- "dropdowns": {
- "download-table": {
- "title": "Download Table"
- }
- },
- "buttons": [
- {
- "enabled": true,
- "type": "data-json",
- "title": "JSON",
- "dropdownId": "download-table",
- "leftIcon": "datafile",
- "rightIcon": "download",
- "fileName": "MIDRC_data_files_table.json"
- },
- {
- "enabled": true,
- "type": "data-tsv",
- "title": "TSV",
- "dropdownId": "download-table",
- "leftIcon": "datafile",
- "rightIcon": "download",
- "fileName": "MIDRC_data_files_table.tsv"
- },
- {
- "enabled": true,
- "type": "data-csv",
- "title": "CSV",
- "dropdownId": "download-table",
- "leftIcon": "datafile",
- "rightIcon": "download",
- "fileName": "MIDRC_data_files_table.csv"
- },
- {
- "enabled": true,
- "type": "file-manifest",
- "title": "Download File Manifest",
- "leftIcon": "datafile",
- "rightIcon": "download",
- "fileName": "MIDRC_data_files_manifest.json"
- },
- {
- "enabled": false,
- "type": "export-to-workspace",
- "title": "Export to Workspace",
- "leftIcon": "datafile",
- "rightIcon": "download"
- }
+ "table": {
+ "enabled": true,
+ "fields": [
+ "submitter_id",
+ "study_uid",
+ "case_ids",
+ "object_id",
+ "project_id"
],
- "loginForDownload": true,
- "guppyConfig": {
- "dataType": "data_file",
- "nodeCountTitle": "Data Files",
- "fieldMapping": [
- {
- "field": "project_id",
- "name": "Project ID"
- },
- {
- "field": "case_ids",
- "name": "Patient ID"
- },
- {
- "field": "study_uid",
- "name": "Study UID"
- },
- {
- "field": "series_UID",
- "name": "Series UID"
- },
- {
- "field": "license",
- "name": "License"
- },
- {
- "field": "data_url_doi",
- "name": "DOI"
- },
- {
- "field": "data_contributor",
- "name": "Data Contributor"
- }
- ],
- "manifestMapping": {
- "referenceIdFieldInResourceIndex": "object_id",
- "referenceIdFieldInDataIndex": "object_id"
- },
- "downloadAccessor": "object_id",
- "accessibleFieldCheckList": [
- "project_id"
- ],
- "accessibleValidationField": "project_id"
- }
- }
- ],
- "discoveryConfig": {
- "features": {
- "pageTitle": {
- "enabled": false,
- "text": "Dataset Discovery"
- },
- "tagsColumn": {
- "enabled": false
- },
- "tagsInDescription": {
- "enabled": true
- },
- "search": {
- "searchBar": {
- "enabled": true
- },
- "tagSearchDropdown": {
- "enabled": true,
- "collapsibleButtonText": "Dataset Filters"
- }
- },
- "authorization": {
- "enabled": true,
- "supportedValues": {
- "accessible": {
- "enabled": true,
- "menuText": "Available"
- },
- "unaccessible": {
- "enabled": true,
- "menuText": "Not Accessible"
- },
- "pending": {
- "enabled": true,
- "menuText": "Pending"
- },
- "notAvailable": {
- "enabled": true,
- "menuText": "Not Available"
- }
- }
- }
+ "dicomViewerId": "submitter_id",
+ "dicomViewerUrl": "ohif-viewer",
+ "linkFields": [
+ "submitter_id"
+ ]
},
- "aggregations": [
- {
- "name": "Datasets",
- "field": "_unique_id",
- "type": "count"
+ "dropdowns": {
+ "download-table": {
+ "title": "Download Table"
}
- ],
- "tagSelector": {
- "title": "Tags by category"
},
- "studyColumns": [
+ "buttons": [
+ {
+ "enabled": true,
+ "type": "data-json",
+ "title": "JSON",
+ "dropdownId": "download-table",
+ "leftIcon": "datafile",
+ "rightIcon": "download",
+ "fileName": "Imaging_Studies_table.json"
+ },
+ {
+ "enabled": true,
+ "type": "data-tsv",
+ "title": "TSV",
+ "dropdownId": "download-table",
+ "leftIcon": "datafile",
+ "rightIcon": "download",
+ "fileName": "Imaging_Studies_table.tsv"
+ },
{
- "name": "Title",
- "field": "short_name",
- "contentType": "string",
- "width": 200,
- "errorIfNotAvailable": false,
- "valueIfNotAvailable": "n/a"
+ "enabled": true,
+ "type": "data-csv",
+ "title": "CSV",
+ "dropdownId": "download-table",
+ "leftIcon": "datafile",
+ "rightIcon": "download",
+ "fileName": "Imaging_Studies_table.csv"
},
{
- "name": "Description",
- "field": "data_description",
- "contentType": "string",
- "width": 400,
- "errorIfNotAvailable": false,
- "valueIfNotAvailable": "n/a"
+ "enabled": true,
+ "type": "manifest",
+ "title": "Download File Manifest for Imaging Studies",
+ "leftIcon": "datafile",
+ "rightIcon": "download",
+ "fileName": "imaging_study_manifest.json"
},
{
- "name": "Publication URL",
- "field": "data_url",
- "contentType": "link",
- "width": 300,
- "errorIfNotAvailable": false,
- "valueIfNotAvailable": "n/a"
+ "enabled": false,
+ "type": "export-to-workspace",
+ "title": "Export to Workspace",
+ "leftIcon": "datafile",
+ "rightIcon": "download"
}
],
- "studyPreviewField": {
- "name": "Research Description",
- "field": "research_description",
- "contentType": "string",
- "includeName": true,
- "includeIfNotAvailable": false
- },
- "studyPageFields": {
- "showAllAvailableFields": false,
- "header": {
- "field": "short_name"
+ "loginForDownload": true,
+ "guppyConfig": {
+ "dataType": "imaging_study",
+ "nodeCountTitle": "Imaging Studies",
+ "fieldMapping": [
+ {
+ "field": "project_id",
+ "name": "Project ID"
},
- "downloadLinks": {
- "field": "data_download_links"
+ {
+ "field": "study_uid",
+ "name": "Study UID"
},
- "fieldsToShow": [
- {
- "groupName": "Dataset Identifiers",
- "includeName": false,
- "fields": [
- {
- "name": "DOI Title",
- "field": "doi_title",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Citation",
- "field": "doi_citation",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "Citation",
- "field": "data_citation",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "Abstract",
- "field": "abstract",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "Research Description",
- "field": "research_description",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "Data Description",
- "field": "data_description",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Creators",
- "field": "doi_creators",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Data Access Information",
- "field": "doi_access_information",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Data Access Information Link",
- "field": "doi_access_information_link",
- "contentType": "link",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Resolvable Link",
- "field": "doi_resolvable_link",
- "contentType": "link",
- "includeIfNotAvailable": false
- },
- {
- "name": "Dataset Information URL",
- "field": "data_url",
- "contentType": "link",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Contact",
- "field": "doi_contact",
- "contentType": "link",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Availability",
- "field": "doi_availability",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Description",
- "field": "doi_description",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Version",
- "field": "doi_version_information",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Resource Type",
- "field": "doi_resource_type",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Publication Year",
- "field": "doi_publication_year",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Funding References",
- "field": "doi_funding_references",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "DOI Publisher",
- "field": "doi_publisher",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "Publication DOI",
- "field": "doi_publication",
- "contentType": "link",
- "includeIfNotAvailable": false
- },
- {
- "name": "Primary Site",
- "field": "primary_site",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "Disease Type",
- "field": "disease_type",
- "contentType": "string",
- "includeIfNotAvailable": false
- },
- {
- "name": "Case Count",
- "field": "cases_count",
- "contentType": "number",
- "includeIfNotAvailable": false
- },
- {
- "name": "Files Count",
- "field": "files_count",
- "contentType": "number",
- "includeIfNotAvailable": false
- }
- ]
- },
- {
- "fields": [
- {
- "name": "Research Description",
- "field": "research_description",
- "contentType": "paragraphs",
- "includeName": true,
- "includeIfNotAvailable": false,
- "valueIfNotAvailable": "No description has been provided for this study."
- }
- ]
- }
- ]
- },
- "minimalFieldMapping": {
- "tagsListFieldName": "tags",
- "authzField": "authz",
- "uid": "_unique_id"
- },
- "tagCategories": [
{
- "name": "disease_type",
- "displayName": "Disease Type",
- "color": "#532565",
- "display": true
+ "field": "submitter_id",
+ "name": "Browse in DICOM viewer"
},
{
- "name": "primary_site",
- "displayName": "Primary Site",
- "color": "#981f32",
- "display": true
+ "field": "case_ids",
+ "name": "Patient ID"
}
- ]
- },
- "registrationConfigs": {
- "features": {
- "workspaceRegistrationConfig": {
- "workspacePolicyId": "workspace",
- "workspaceInfoMessage": "The MIDRC workspace provides a standardized computational environment for accessing and analyzing data from MIDRC studies. Please fill out this form to request access to the workspace and start computing!",
- "successRedirect": {
- "link": "/",
- "text": "Go to MIDRC Home Page"
- }
- }
- },
- "zendeskConfig": {
- "zendeskSubdomainName": "midrc-support"
+ ],
+ "manifestMapping": {
+ "resourceIndexType": "data_file",
+ "resourceIdField": "object_id",
+ "referenceIdFieldInResourceIndex": "_imaging_study_id",
+ "referenceIdFieldInDataIndex": "_imaging_study_id",
+ "useFilterForCounts": false
+ },
+ "accessibleFieldCheckList": [
+ "project_id"
+ ],
+ "accessibleValidationField": "project_id"
}
}
-}
+ ]
+ }