This guide helps organizers create a space within Synapse to host a crowd-sourced Challenge. Challenges are community competitions designed to crowd-source new computational methods for fundamental questions in systems biology and translational medicine. Learn more about Challenges and see examples of past and current projects by visiting Challenges and Benchmarking.
A Challenge space provides participants with a Synapse project to learn about the Challenge, join the Challenge community, submit entries, track progress, and view results. This article will focus on:
Setting up the Challenge infrastructure
Launching the Challenge space
Setting up the Challenge wiki
Updating the Challenge
Interacting with the submitted entries
Before You Begin
Computing Power
At Sage Bionetworks, we generally provision an EC2 Linux instance for a Challenge that leverages SynapseWorkflowOrchestrator to run CWL workflows. These workflows will be responsible for evaluating and scoring submissions (see model-to-data-challenge-workflow GitHub for an example workflow). If Sage Bionetworks is responsible for the cloud compute services, please give a general estimate of the computing power (memory, volume) needed. We can also help with the estimates if you are unsure.
By default, up to ten submissions can be evaluated concurrently, though this number can be increased or decreased accordingly within the orchestrator's .env file. Generally, the more submissions you want to run concurrently, the more power will be required of the instance.
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Example Let’s say a submission file that is very large and/or complex will require up to 10GB of memory for evaluation. If a max of four submissions should be run at the same time, then an instance of at least 40GB memory will be required (give or take some extra memory for system processes as well), whereas ten concurrent submissions would require at least 100GB. The volume of the instance will be dependent on variables such as the size of the input files and the generated output files. If running a model-to-data Challenge, Docker images should also be taken into account. On average, participants will create Docker images that are around 2-4 GB in size, though some have reached up to >10 GB. Always encourage participants to follow Dockerfile Best Practices to ensure they are submitting as optimal of images as possible. |
Using Sensitive Data
Synapse has the ability to apply access restrictions to sensitive data (e.g. human data), so that legal requirements are met before participants can access it. If human data are being used in the Challenge, or if you have any questions about the sensitivity of the Challenge data, contact the Synapse Access and Compliance Team (act@sagebase.org) for support with the necessary data access procedures.
If data is sensitive and cannot be hosted on Synapse (e.g. it cannot leave the external site or data provider), provide a remote server with the following:
Support for Docker and, if possible,
docker-composeIf Docker is not allowed, then support for Singularity and Java 8 is required
SynapseWorkflowOrchestrator repository
If Sage is not allowed access to the server, then it is the external site’s responsibility to get the orchestrator running in whatever environment chosen. If Docker is not supported by the system, please let us know as we do have solutions for workarounds (e.g. using Java to execute, etc.).
Challenge Infrastructure Setup
Requirements
Synapse account
Python 3.7+
(for local testing) CWL runner of choice, e.g. cwltool
Access to cloud compute services, e.g. AWS, GCP, etc.
Steps
1. Create a workflow infrastructure GitHub repository for the Challenge. For the orchestrator to work, the repository must be public.
We have created two templates in Sage-Bionetworks-Challenges that you may use as a starting point. Their READMEs outline what will need to be updated within the scripts (under Configurations), but we will return to this later in Step 10.
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Workflow Template
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Submission Type
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data-to-model-challenge-workflow
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Flat files (e.g. CSV)
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model-to-data-challenge-workflow
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Docker images
2. Create the Challenge site on Synapse with challengeutils' create-challenge:
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challengeutils create-challenge "challenge_name" |
This command will create two Synapse projects:
Staging - Organizers will use this project during the Challenge development to share files and draft the Challenge wiki. The
create-challengecommand initializes the wiki with the DREAM Challenge Wiki Template.Live - Organizers will use this project as the pre-registration page during Challenge development. When the Challenge is ready for launch, the project will then be replaced with the contents from staging.
You may think of these two projects as development (staging project) and production (live project), in that all edits must be done in the staging site, NOT the live site. Maintenance of both projects enables wiki content to be edited and previewed in the staging project before the content is published to the live project. Changes to the live site are synced over with challengeutils' mirror-wiki (see Update the Challenge below for more info).
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At first, the live site will be just one page where a general overview about the Challenge is provided. There will also be a pre-register button that Synapse users can click on if they are interested in the upcoming Challenge. |
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create-challenge will also create four /wiki/spaces/DOCS/pages/1985446029 for the Challenge:
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Participants - This Synapse team includes the individual participants and teams who register to the Challenge.
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Organizers - The Challenge organizers must be added to this list to provide the permissions to share files and edit the wiki on the staging project.
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Admin - The Challenge administrators have administrator access to both the live and staging project. Organizers do not need to be Administrators. Ideally, all admin must have a good understanding of Synapse.
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One of the features to the Synapse.org platform is the ability to host a crowd-sourced challenge. Hosting challenges are a great way to crowd-source new computational methods for fundamental questions in systems biology and translational medicine.
Learn more about challenges and see examples of past/current projects by visiting Challenges and Benchmarking.
Running a challenge on Synapse will require creating a challenge space for participants to learn about the challenge, join the challenge community, submit entries, and view results. This article is aimed at challenge organizers, and will focus on:
Setting up the infrastructure for submission evaluation
Launching the challenge
Updating the challenge
Closing the challenge
Monitoring the submissions
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Before You Begin
🖥️ Required Compute Power
At Sage Bionetworks, we generally provision an AWS EC2 Linux instance to run infrastructure of a challenge, leveraging the SynapseWorkflowOrchestrator to run CWL workflows. These workflows will be responsible for evaluating and scoring submissions.
To budget the cloud compute services: consider the computing power needed to validate and score the submissions (for example: memory, storage, GPU, network speed). If contracting with Sage Bionetworks, we can help estimate these costs as part of the Challenge budget.
📋 Using Sensitive Data as Challenge Data
Challenge data can be hosted on Synapse. If the data is sensitive (for example, human data), Synapse can apply access restrictions so that legal requirements are met before participants can access them. Contact the Synapse Access and Compliance Team (act@sagebase.org) for support with the necessary data access procedures for sensitive data.
🛑 Restricted Data Access
If data cannot leave the external site or data provider, it will be the data contributor’s responsibility to set up the challenge infrastructure. Contact the Challenges and Benchmarking team (cnb@sagebase.org) for consultations if needed.
To set up the infrastructure, you may follow Sage’s approach of using the SynapseWorkflowOrchestrator. The following will be required to use the orchestrator:
Support for Docker
(ideally) Support for
docker-composeIf Docker is not allowed, then support for Singularity and Java 8 will be a must
Note that the steps outlined in this article will assume the orchestrator will be used.
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Challenge Infrastructure Setup
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Requirements
One Sage account
Python 3.8+
(for local testing) CWL runner of choice, e.g. cwltool
Access to cloud compute services, e.g. AWS, GCP, etc.
Outcome
This infrastructure setup will continuously monitor the challenge’s evaluation queue(s) for new submissions. Once a submission is received, it will undergo evaluation including validation and scoring. All submissions will be downloadable to the challenge organizers, including the Docker image (if model-to-data challenge) and/or prediction files. Participants may periodically receive email notifications about their submissions (such as status, scores), depending on the infrastructure configurations.
Steps
1. Create a GitHub repository for the challenge workflow infrastructure. For the orchestrator to work, this repo must be public.
Two templates are available in Sage-Bionetworks-Challenges that you may use as a starting point. Their READMEs outline what will need to be updated within the scripts (under Configurations), but we will return to this later in Step 12.
Workflow Template | Submission Type |
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Flat files, like CSV files | |
Docker images |
2. Create the challenge space on Synapse with challengeutils' create-challenge:
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challengeutils create-challenge "challenge_name" |
This command will create two Synapse projects:
Staging - Organizers will use this project during challenge planning and development to share files and draft the wiki content.
create-challengewill intialize the wiki with the DREAM Challenge Wiki Template.Live - Organizers will use this project as the pre-registration page during challenge development. When the challenge is ready for launch, the project will then be replaced with the contents from staging.
We encourage you to use the staging project to make all edits and preview them before officially pushing the updates over to the live project.
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See Update the Challenge below to learn more about syncing changes from staging to live. |
create-challenge will also create four Synapse teams for the challenge:
Pre-registrants - This team is used when the challenge is under development. It allows interested Synapse users to join a mailing list to receive notification of Challenge challenge launch news.
Add Synapse users to the Organizers and Admin teams as needed.
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Participants - Once the challenge is launched, Synapse users will join this team in order to download the challenge data and make submissions.
Organizers - Synapse users added to this team will have the ability to share files and edit wikis on the staging project. Add users as needed.
Admin - Synapse users added to this team will have administrator access to both the live and staging projects. Organizers do not need to be Administrators. Ideally, all admins must have a good understanding of Synapse. Add users as needed.
3. On the live project, go to the Challenge tab and create as many evaluation queues as needed (for example, one per question/sub-challengetask) by clicking on Challenge Tools > Create Evaluation Queue. By default, create-challenge will create an one evaluation queue for writeupsby default.A writeup is something we require of all participants in order to be considered for final evaluation and ranking. A writeup should include all contributing persons, a thorough description of their methods and usage of data outside of the Challenge data, as well as all of their scripts, code, and predictions file(s)/Docker image(s). We require all of these so that we can ensure their code and final output is reproducible if they are a top-performer.
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The 7-digits in the parentheses following each evaluation queue name is the evaluation ID. You will need these ID(s) later in Step 11. |
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4. While still on the live project, go to the Files tab and create a new folder called “Logs” by clicking on the add-folder icon:
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The 7-digits in the parentheses following each evaluation queue name is its evaluation ID. You will need these IDs later in Step 9. |
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This folder will contain the participants' submission logs and prediction files (if any). Make note of its synID for use later in Step 11. |
5. On the staging project, go to the FILES Files tab and create a new folder called "Logs" by clicking on Files Tools > Add New Folder.
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This folder will contain the participants' submission logs and prediction files (if any). Make note of this Folder ID for use later in Step 9. |
5. On the staging site, go to the FILES tab and create a new file by clicking on Files Tools > Upload or Link to a File > Link to URL.
For "URL"click on the upload icon to Upload or Link to a File:
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6. In the pop-up window, switch tabs to Link to URL. For “URL”, enter the web address to the zipped download of the workflow infrastructure repositoryrepo. You may get this address by going to the repository repo and clicking on Code > right-clicking Download Zip > Copy Link Address:
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Name the file (e.g. "workflow"), then click Save.Click Save.
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This file will be what links the evaluation queue to the orchestrator. Make note of this File ID its synID for use later in Step 911. |
6. /wiki/spaces/DOCS/pages/2667708522 7. Add an annotation to the file called ROOT_TEMPLATE by clicking on Files Tools > Annotations > Edit. The "Value" will be the path to the workflow script, written as:
{infrastructure workflow repo}-{branch}/path/to/workflow.cwl
For example, this is the path to workflow.cwl of the model-to-data template repo:
. This annotation will be used by the orchestrator to determine which file among the repo is the workflow script. Click on the annotations icon, followed by Edit:
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8. For “Value”, enter the filepath to the workflow script as if you had downloaded the repo as a ZIP. For example, model-to-data-challenge-workflow would be downloaded and unzipped as model-to-data-challenge-workflow-main
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and the path to the workflow script is workflow.cwl:
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The ROOT_TEMPLATE annotation is what the orchestrator uses to determine which file among the repo is the workflow script. |
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In this example, “Value” will be model-to-data-challenge-workflow-main/workflow.cwl. For the most part, “Value” should look something like this:
{name of repo}-{branch}/workflow.cwl
9. Create a cloud compute environment with the required memory and volume specifications. Once it spins up, log into the instance and clone the orchestrator. Follow the , then log into the instance.
If you are a Sage employee: you can follow our internal instructions on /wiki/spaces/CHAL/pages/2806087732 here.
If you are not a Sage employee: follow the instructions listed under "Setting up linux environment"
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to install and run Docker as well as
docker-composeonto the
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compute environment of choice.
810. While still on On the instance, change directories clone the SynapseWorkflowOrchestrator repo if it’s not already available on the machine. Change directories to SynapseWorkflowOrchestrator/ and create a copy of the .envTemplate file as .env (or simply rename it to .env):
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cd SynapseWorkflowOrchestrator/ cp .envTemplate .env |
911. Open .env and enter values for the following property config variables:
Property | Description | Example |
| Synapse credentials under which the orchestrator will run. The provided user must have access to the evaluation queue(s) being serviced. |
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| Password for This can be found under My Dashboard > Settings. |
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| Synapse ID synID for "Logs" folder. Use the Synapse ID synID from Step 4. |
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| JSON map of evaluation IDs to the workflow repo archive, where the key is the evaluation ID and the value is the link address to the archive. Use the evaluation IDs from Step 3 as the key(s) and the Synapse ID synIDs from Step 5 as the value(s). |
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Refer to the "Running the Orchestrator with Docker containers" |
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README section for |
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additional configuration options. |
1012. Return to Clone the workflow infrastructure repository and clone it onto your local machine. Open the repo in your editor of choice and repo. Using a text editor or IDE, make the following edits updates to the following scripts:Data
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Push the changes up to GitHub when done.
1113. On the instance, change directories to SynapseWorkflowOrchestrator/ and kick-start the orchestrator with:
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docker-compose up |
To have it run in the background, add the -d flag (for detached mode):
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docker-compose up -d |
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It may be helpful to not run the orchestrator in detached mode at first, so that you will be made aware of any errors with the orchestrator setup right away. |
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-d |
where -d will run orchestrator in the background. This will allow you to exit the instance without terminating the orchestrator.
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14. To make changes to the .env file (such as updating the number of concurrent submissions), stop the orchestrator with:
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docker-compose down |
Once you are done making updates, save the file and restart the orchestrator to apply the changes.
Log Files
As it’s running, the orchestrator will upload logs and prediction files to the folder as specified by WORKFLOW_OUTPUT_ROOT_ENTITY_ID. The folder will be structured like this:
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“Logs” folder. For each user or team that submits to the challenge, two folders will be created:
<submitterid>/<submitterid>_LOCKED/
where Docker and TOIL logs are uploaded to <submitterid>/, and prediction files are uploaded to <submitterid>_LOCKED/. Note that the LOCKED folders will not be accessible to the participants, in order to prevent data leakage.
The directory structure of “Logs” will look something like this:
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Logs ├── submitteridA │ ├── submission01 │ │ ├── submission01_log.txt │ │ └── submission02submission01_logs.zip │ ├── submission02 │ │ ├── submission02_log.txt │ │ └── submission02_logs.zip │ ... │ ├── submitteridA_LOCKED │ ├── submission01 │ │ └── predictions.csv │ ├── submission02 │ │ └── predictions.csv │ ... │ ... |
If an error is encountered during any of the workflow steps, the orchestrator will update the submission status to INVALID and the workflow will stop. If, instead, the workflow finishes to completion, the orchestrator will update the submission status to ACCEPTED. Depending on how the workflow is set up (configured by step 10), participants may periodically be notified by email of their submission's progress.
For a visual reference, a diagram of the orchestrator and its interactions with Synapse is provided below:
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Display a Submissions Dashboard (Optional)
12. Go to the staging site and click on the TABLES tab. Create a new Submission View by clicking on Table Tools > Add Submission View. Under "Scope", add the evaluation queue(s) you are interested in monitoring (you may add more than one), then click Next. On the next screen, select which information to display - this is known as its schema. We recommend the following schema for a typical SubmissionView:
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Column Name
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Description
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Facet values?
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id
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Submission ID
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Not recommended
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createdOn
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Date and time of the submission (in Epoch, but rendered as MM/dd/yyyy, hh:mm:ss)
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Optional
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submitterid
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User or team who submitted (user or team ID, but rendered as username or team name)
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Recommended
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dockerrepositoryname
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(recommended for model-to-data) Docker image name
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Not recommended
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dockerdigest
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(recommended for model-to-data) Docker SHA digest
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Not recommended
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status
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Workflow status of the submission (one of [RECEIVED, EVALUATION_IN_PROGRESS, ACCEPTED, INVALID])
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Recommended
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submission_status*
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Evaluation status of the submission (one of [None, VALIDATED, SCORED, INVALID])
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Recommended
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submission_errors*
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(if any) Validation errors for the predictions file
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Not recommended
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orgSagebionetworksSynapseWorkflowOrchestratorSubmissionFolder*
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Synapse ID to the submission’s logs folder
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Not recommended
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(any annotations related to scores)*
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Submission annotations - names used depends on what annotations were used in the scoring step
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The latter columns, e.g. submission_status, submission_errors, etc., would need to be added manually by clicking the + Add Column button at the bottom of the Edit Columns window. |
Once you click Save, a table of the submissions and their metadata will become available for viewing and /wiki/spaces/DOCS/pages/2667642897. Changes to the information displayed can be edited by going to the SubmissionView, then clicking on Submission View Tools > Show Submission View Schema > Edit Schema.
Launch the Challenge (One-Time Only)
13. On the live site, go to the CHALLENGE tab and share the appropriate evaluation queues with the Participants team, giving them "Can submit" permissions.
14. Use synapseutils' copyWiki in a Python script to copy over all pages from the staging site to the live site. When using copyWiki, it is important to also specify the destinationSubPageId parameter. This ID can be found in the URL of the live site, where it is the integer following .../wiki/<some number>.
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Launch the Challenge
Requirements
One Sage account
Python 3.7+
Important TODOs:
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Following steps 1-5 should be done in the live project. |
Before proceeding with the launch, we recommend contacting Sage Governance to add a clickwrap for challenge registration. With a clickwrap in-place, interested participants can only be registered if they agree to the terms and conditions of the challenge data usage.
If you are a Sage employee: submit a Jira ticket to the Governance board with the synID of the live project, as well as the team ID of the participants team.
Share all needed evaluation queues with the participants team with
Can submitpermissions. Once the challenge is over, we recommend updating the permissions toCan viewto prevent late submissions.We also recommend sharing the evaluation queues with the general public so that the leaderboards are openly accessible.
After the challenge is launched, create a folder called “Data” and update its Sharing Settings. Share the “Data” folder with the participants team only. Do not make the folder public or accessible to all registered Synapse users. The sharing settings of the “Data” folder should look something like this:
Upload any challenge data that is to be provided to the participants to the “Data” Folder. DO NOT UPLOAD DATA until you have updated its sharing settings.
To launch the Challenge, that is, to copy the wiki pages of the staging project over to the live project, use synapseutils' copyWiki() in a Python script.
For example:
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import synapseclient import synapseutils syn = synapseclient.login() synapseutils.copyWiki( syn, "syn1234", # Synapse IDsynID of staging site destinationId="syn2345", # Synapse IDsynID of live site destinationSubPageId=999999 # ID following ../wiki/ of live siteproject URL ) |
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Important! After the initial copying, all changes to the live site should now be synced over with |
Stop the Orchestrator
15. On the instance, enter:
Ctrl + C or cmd + C
followed by:
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docker-compose down |
If you are running the orchestrator in the background, skip the first step and simply enter:
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docker-compose down |
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If the Challenge is currently active, but you need to stop the orchestrator for any reason, e.g. to make updates to the .env file, it may be helpful to first check whether any submissions are currently being evaluated. If you are running the orchestrator in the background, you can monitor its activity by entering:
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docker ps |
If only one image is listed, e.g. sagebionetworks/synapse-workflow-orchestrator, this will indicate that no submissions are currently running.
Otherwise, if you are not running the orchestrator in the background, read the logs on the terminal screen to determine whether there is current activity.
Wiki Setup
Use the following questions to help plan and set up the Challenge site and evaluation queues.
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Will the participants submit a single file/model to answer all sub-challenges or will they submit a different file/model per sub-challenge? |
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Will there be Challenge rounds? If so, how many? Using rounds may help increase participation levels throughout the Challenge, as submission activity is usually high near the end of rounds/phases. It is best to have end dates during the mid-week if possible; this will ensure that there will be someone on-hand to help monitor and resolve issues should they arise. |
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If so, should there be a limit in frequency? Examples: one submission per day, 3 submissions per week, 5 total, etc. Setting a limit may help with potential overfitting as well as limit a user/team from monopolizing the compute resources. |
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Common formats supported: prediction file (i.e. csv file), Docker image |
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Will the data be released upon the Challenge end? After the embargo? Never? |
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If so, will a clickwrap be needed? A clickwrap is an agreement between the participant and data provider that requires the participant to click a button agreeing to policies for data usage. Should log files be returned? Will there be a need to generate synthetic data? |
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If Sage will be responsible, please provide as many details regarding the format of a valid predictions file (for example, number of columns, names of column headers, valid values, etc.) and all exceptional cases. For scoring, please provide the primary and secondary metrics, as well as any special circumstances for evaluations, i.e. CTD2 BeatAML primary metric is an average Spearman correlation, calculated from each drug’s Spearman correlation. If not Sage will not be responsible, please provide the scripts in either Python or R. If needed, we do provide sample scoring models that you may use as a template, available in both Python and R. |
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A typical Challenge will immediately return the scores in an email upon evaluation completion, however, there have been past Challenges that did not return scores until after the end date. There is also an “hybrid” approach, in which scores are immediately returned during the Leaderboard/Testing Phase but withheld during the Final/Validation Phase (in which participants do not know their performance until after the Challenge end). |
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Some past Challenges had active leaderboards (i.e. participants could readily view their ranking throughout the evaluation round) whereas other Challenges did not release the leaderboards until the round/Challenge was over. |
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Should participants submit their writeups during submission evaluations or after the Challenge has closed? A writeup is a summary of all contributors, methods, scripts, code, and prediction files/Docker images that a team used for their submission. Writeups are required so that top-performing entries can be reproduced. |
Update the Challenge
Challenge Site and Wikis
Any changes to the Challenge site and its wiki/sub-wiki contents must be done in the staging site, not live. To update:
Make whatever changes needed to the staging project.
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Using the |
Evaluation Queue Quotas
To update the submission quotas, go to the Synapse live site, then head to the CHALLENGE tab. Edit the evaluation queues as needed:
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Example 1 A Challenge has 4 rounds, each round has a limit of 3 submissions per submitter/team. To implement this quota, click Edit on the desired queue, click Add Round and input the Duration and Submission Limits. |
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Example 2 A Challenge lasts for 4 months with a daily submission limit of 3. To implement this quota, click Edit on the desired queue, click Add Round and input the Duration and click Advanced Limits to pick daily/weekly/monthly limits. |
Workflow Steps
For any changes to the infrastructure workflow steps and/or scripts involved with the workflow (e.g. run_docker.py), simply make the edits to the scripts, then push the changes.
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Note: dry-runs should always follow a change to the workflow; this will ensure things are still working as expected. |
Interacting with Submissions
Throughout the Challenge, participants will continuously submit to the evaluation queues. To manage continuous submissions, organizers can automate validation and scoring with the Synapse python client evaluation commands.
Revealing Submissions and Scores
Organizers can create leaderboards when scores are ready to be revealed to participants using /wiki/spaces/DOCS/pages/2011070739.
Submission views are sorted, paginated, tabular forms that can display submission data and annotations (e.g. scores from the scoring application and other metadata) and update as annotations or scores change. A submission view can provide real-time insight into the progress of a Challenge
Learn more about adding leaderboards in the /wiki/spaces/DOCS/pages/1985151345When using copyWiki, it is important to specify the destinationSubPageId parameter. This ID can be found in the URL of the live project, where it is the number following .../wiki/.
Once copyWiki has been used once, DO NOT RUN IT AGAIN!
Once the wiki has been copied over, all changes to the live project should now be synced with challengeutils' mirrow-wiki.
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Learn more about how to Update the Challenge below. |
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Monitor the Submissions
As challenge organizers, we recommend creating a Submission View to track and monitor submissions as they come in. This table will especially be useful when participants need help with their submissions.
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Learn more about revealing scores and adding leaderboards in Evaluation Queues. |
Steps
1. Go to the staging project and click on the Tables tab. Create a new Submission View by clicking on Add New… > Add Submission View.
2. Under "Scope", add evaluation queue(s) you are interested in monitoring. More than one queue can be added. Click Next. On the following screen, select which information to display - this is known as the schema.
We recommend the following schema for monitoring challenge submissions:
Column Name | Description | Facet values? |
|---|---|---|
| Evaluation ID (evaluation ID, but rendered as evaluation name) – recommended for SubmissionViews with multiple queues in scope |
|
| Submission ID | |
| Date and time of the submission (in Epoch, but rendered as | |
| User or team who submitted (user or team ID, but rendered as username or team name) |
|
| Docker image name – recommended for model-to-data challenges |
|
| Docker SHA digest – recommended for model-to-data challenges |
|
| Workflow status of the submission (one of [ |
|
| Evaluation status of the submission (one of [None, |
|
| (if any) Validation errors for the predictions file |
|
| synID to the submission’s logs folder |
|
| synID to the predictions file (if any) |
|
(any annotations related to scores) | Submission annotations - names used depends on what annotations were used in the scoring step of the workflow |
| Info |
|---|
The highlighted columns would need to be added manually by clicking the + Add Column button at the bottom of the Edit Columns window. |
3. Click Save. A table of the submissions and their metadata will now be available for viewing and querying. Changes to the information displayed can be edited by clicking on the schema icon, followed by Edit Schema:
...
Update the Challenge
Updating Existing Wikis
1. Go to the staging project and navigate to the page(s) you wish to edit. Click on the pencil icon to Edit Project Wiki:
...
Make edits as needed, then click Save.
2. Use challengeutils' mirror-wiki to push the changes to the live project:
| Code Block |
|---|
challengeutils mirror-wiki staging_synid live_synid [--dryrun] |
Use --dryrun to optionally preview which pages will be updated prior to doing an official sync.
Adding a New Wiki Page
1. Go to the staging project, click on Wiki Tools > Add Wiki Subpage. Enter a page title, then click OK. A new page should now be available.
2. On the new page, click on the pencil icon to Edit Project Wiki:
...
Add the page content, then click Save.
3. Go to the live project and create a new wiki page with the same name as the new page in the staging project. mirror-wiki depends on the page titles to be the same for synchronization.
4. Use challengeutils' mirror-wiki to push the changes to the live project:
| Code Block |
|---|
challengeutils mirror-wiki staging_synid live_synid [--dryrun] |
Use --dryrun to optionally preview which pages will be updated prior to doing an official sync.
Extending the Deadline
It is not unheard of for there to be a change in the submission deadline. To extend the submission deadline date/time, you can either:
edit the Round End of an existing round; or
add a new round that will immediately start after the current one (note that this approach will reset everyone’s submission limit)
We also recommend notifying the participants of any changes to the timeline by posting an announcement.
| Panel | ||||||||
|---|---|---|---|---|---|---|---|---|
| ||||||||
Learn more posting announcements in Utilizing the Discussion Board. |
Updating the Workflow
For any changes to the CWL scripts or run_docker.py, make edits as needed to the scripts, then push the changes. We highly recommend conducting dryruns immediately after, so that errors are addressed in a timely manner.
Evaluation Docker Image
If your workflow is using a Docker image in validate.cwl and/or score.cwl, and updates were made, pull the latest changes on the instance with:
| Code Block |
|---|
docker pull <image name>:<version> |
...
Close the Challenge
Important TODOs:
Registration: remove/hide all "Register" buttons from the challenge site
Pages to search through: main page, Participation Overview, Submission Tutorial(s)
Past challenge as reference:
You can replace the registration button with an alert well like this:
...
| Code Block | ||
|---|---|---|
| ||
<div class="alert alert-info">
<h4><strong>Registration is closed.</strong></h4>
<p>Thank you to everyone who joined the challenge!</p>
</div> |
Data access: disallow users from joining the participant team, thus barring them from accessing the challenge data after the challenge has completed
Go to Participants team page
Click on Team Actions button > Edit Team
Under Access, select “Team is locked, users may not join or request access. New users must be invited by a team manager.”
Evaluation queues: update the participants team’s permissions from
Can submittoCan view
Writeups: link writeups to the final submissions
| Panel | ||||||||
|---|---|---|---|---|---|---|---|---|
| ||||||||
See Collecting Writeups for more information. |
Instances: stop and terminate all cloud compute instances for the challenge.
...
🌟 For additional assistance or guidance, contact the Challenges and Benchmarking team at cnb@sagebase.org.