Post-Term Use and Replication Requirements

What is a “Proprietary Dataset”?

The datasets on Dewey are considered proprietary or restricted. This means:

• Data is licensed, not sold

• Users receive access only while an active subscription is maintained

• Raw data cannot be transferred, published, or redistributed

• Users do not gain ownership of the raw data

In short: You may work with the data during your license, but cannot share or keep it beyond the allowed terms.

Post-term use: General rule

When your subscription ends, you must stop using, and destroy, all data you accessed through Dewey. That covers raw downloads, filtered or reformatted versions, derived datasets, and copies in AI tools or cloud storage. Dewey may ask for written confirmation that you've done this.

Summary insights you've already published, such as the tables, figures and statistics in a paper or presentation, aren't affected.

There's one important exception for papers under review.

Exception: Project submitted for publication

If your paper qualifies as a Pending Publication, you can keep the data it uses after your subscription ends. This is so you can see the paper through review, including revise-and-resubmit rounds.

To qualify, both of these must be true on or before the last day of your subscription:

1. You've submitted the paper to a named academic journal, conference or press, and you have a timestamped record of it, such as a confirmation email or portal receipt.

2. You've marked the project Submitted on the Dewey Platform.

If either one happens after your subscription ends, the paper doesn't qualify. Tip: update your project status the same day you submit.

What you can do:

• Keep only the data used in that paper, and only as long as needed to get it published.

What you can't do:

• Use the data for new projects or analyses outside that paper.

• Share or publish the raw data at any point: before, during or after submission.

All other license terms still apply.

When does this exception expire?

Your post-term right ends on whichever of these comes first:

• The paper is published.

• You withdraw the paper, or it's rejected with no further chance to revise and resubmit.

• Two years pass after the last day of your subscription.

When it ends, permanently delete the data. This right doesn't apply at all if your agreement is terminated because of a breach.

Raw data can never be published or shared

Even during peer review or R&R, raw data must not be shared with journals, editors, reviewers, collaborators outside your license, or any other external party.

Instead, the proper method is:

• Share the summary insights (aggregate tables, statistics and figures) that appear in or directly support your paper.

• Share your notebook or codebook showing how you produced those results from the raw data.

• Direct anyone who needs the raw data to Dewey. Include the dataset's DOI so they can find the exact dataset you used.

This ensures:

• Compliance with Dewey's terms and conditions and the terms of our data partners

• Consistent data handling and versioning

• Protection of the intellectual property of our data partners

• A standard replication path

Suggested language for publications or submissions:

"The data used in this study was produced by [Data Provider] and accessed through Dewey Data Inc. It is licensed, proprietary data and cannot be shared by the authors. To request access, contact Dewey at deweydata.io."

What data can be shared? (Summary insights)

We support open research. You can publish summary insights from your work, as long as they don't reveal or rebuild the raw data.

Allowed:

• Aggregate statistics (averages, medians, rates, measures)

• Summary tables by group or category (e.g., by county or month) where no individual records are visible

• Trends or patterns over time or across categories

• Regression results and model estimates reported in your paper (coefficients, standard errors, fit statistics)

• Visualizations (charts, maps, plots) based on aggregated data

• Summaries that can't be reverse-engineered

Not allowed:

• Row-level or record-level exports

• Small breakdowns that expose individual entries

• "Samples" of raw data, even if anonymized (unless explicitly approved)

• Derived datasets released as files (e.g., binned panels, extracted features, crosswalks, or cleaned versions of the data)

• Trained models, model weights or parameter files built from the data

• Any format that could allow reconstruction of the core proprietary value

Rule of thumb:

If someone could rebuild or closely approximate the raw dataset from what you shared, or if it replaces the need for someone else to access the raw data to do new research, it's too granular.

After publication

Once a paper is published:

• You may publish summary insights (aggregate results, statistics and figures) as part of your findings.

• If you've been using the post-term right, it ends at publication. Delete all retained data, including your R&R copy. If your subscription is still active, you can keep working with the data as usual.

• You may not provide raw data or derived datasets in supplementary materials.

• You may provide code or processing logic, as long as it doesn't include, expose or reconstruct the raw data.

Replication pathway (for transparency and reproducibility)

To enable replication while protecting proprietary data:

1. The authors publish summary insights and their methodology.

2. Code can be provided, without raw data included.

3. Reviewers or replicators are directed to Dewey, using the dataset's DOI, to obtain access.

4. Replicators license the dataset through Dewey under their own subscription.

5. Replication is performed within Dewey's permitted-use framework.

Heads up: Dewey keeps only the latest version of each dataset, and availability depends on the data provider. Record the Version DOI of the data you used so replicators know exactly which version your results come from.

This keeps research transparent and compliant.

Summary

Final Thoughts

These guidelines balance:

• Responsible data stewardship

• Licensing commitments

• Research transparency and reproducibility

• Protection of proprietary value

If you're unsure whether a particular use or sharing scenario is allowed, just ask—we’re here to help.