There are 5 options to upload data:

• Import from local computer (including csv upload)
• Import from a previous project
• Import from Cloud storage (AWS S3, Google Cloud Storage, Microsoft Azure)
• Import from a Nucleus dataset
• Import from a sample dataset

Option 1: Import from local computer

Uploading local files

Select files from your computer to upload. For faster uploading, consider the other options that allow for async uploading. Please upload no more than 1000 files at one time.

Uploading CSV files

To upload from a local CSV file, you need to include either a column named "attachment_url" or a column named "text". "attachment_url" columns should be the data's publicly accessible remote urls.

"attachment_url"s will be used to fetch the data from that url for a website or file. For websites, the url will be displayed as a link for taskers to open.

In order for Scale to recognize an S3 url stored in a protected bucket integrated with Scale, the url must follow this format: "s3://<bucket_name>/<path_to_object>".

The values in the "text" column can be used for raw text or markdown for categorization and textcollection projects. As a result, we recommend also adding some step-by-step instructions as part of the markdown.

Another feature is that we support iframes as input in the "text" column. You can add an iframe to a native app that taskers use to interact with. You can additionally provide an optional "metadata" column to store extra data in JSON. If there are more than 200 assets in the upload, we will upload in the background.

Another feature is that we support iframes as input in the "text" column. You can add an iframe to a native app that taskers use to interact with.

Option 2: Import from a Previous Project

Import data from a previous project you had created in Studio or Rapid

Option 3: Import from Cloud Storage

AWS S3

Provide a S3 bucket and an optional prefix (folder path) and we will import the data directly. Note that you need to give us permission to do so. Check this document for instructions on setting up the permissions. You will need to grant permissions for 'GetObject' and 'ListBucket' actions. Additionally, AWS uploads are capped at 5,000 files.

We have also included instruction videos for setting up IAM delegated access.

Creating role and corresponding policy. You can see which values to input for the role on the Scale integrations page. You can also specify which resources to use with more granularity.

Assigning the read-only policy to the Scale integration role.

This is how a sample policy may look.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "scales3access",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Effect": "Allow",
            "Resource": [
              "arn:aws:s3:::YOUR_BUCKET_NAME/*",
              "arn:aws:s3:::YOUR_BUCKET_NAME"
            ],
        }
    ]
}

Google Cloud Storage

Provide a Google Cloud Storage bucket and an optional file prefix / delimiter and we will import the data directly. Note that you need to give us permission to do so. Check this document for instructions on setting up the permissions. You will need to setup permissions for Storage Legacy Bucket Reader and Storage Legacy Object Reader actions. Please ensure the bucket does not contain both files and folders.

We have also included instruction videos for setting up service account impersonation.

Adding a service account. Replace {uuid} with the value given to you on the Scale integrations page..

Adding bucket permissions for the service account.

Microsoft Azure

Provide an Azure account name, container, and an optional prefix and we will import the data. Check this document for instructions on setting up the permissions. You may need to grant permission for Storage Blob Data Reader.

Option 4 & 5: Import from a Nucleus dataset or sample dataset

Get started easily with pre-existing datasets. If you have already uploaded a dataset onto Scale Nucleus, you can import it directly into Studio. If you are getting started for the first time and just want to test out the platform, you can choose from a selection of our sample datasets.