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BPL Database
BPL Database

Database Systems, Management, Libraries and more.

Fair Use of Database Content Explained

Jacob, November 4, 2025October 22, 2025

Fair use of database content can feel like a puzzle — what can you copy, and when will copying trigger a copyright claim?

Are you building products, pulling facts for research, or drafting policy? The U.S. framework pivots on Section 107’s four-factor test. It weighs purpose, nature, amount taken, and market effect. Courts look at transformation, the “heart” taken, and whether your work displaces a market.

Want clear steps? Start by documenting purpose, minimizing what you extract, and checking licenses. The Copyright Office’s Fair Use Index and PACER provide case summaries and opinions to back decisions.

Quick promise: this article gives practical guidance and resources so your teams answer tough questions with confidence and ship data-driven projects with fewer surprises.

Table of Contents

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  • What “database content” means in U.S. copyright law
    • Facts versus expression: why raw data often isn’t protected
    • When data becomes a copyrighted work
  • The legal backbone: Section 107 and the four-factor test
    • Purpose and character
    • Nature of the work
    • Amount and substantiality
    • Market effect
  • Databases versus data: separating structure from contents
    • Thin copyright in selection, coordination, and arrangement
    • Metadata, schemas, and creative choices that carry rights
  • Fair use of database content in practice
    • Research and scholarship: quoting, sampling, and analysis
    • News and commentary: context that transforms raw facts
    • Teaching and libraries: access with proportion and purpose
  • When licenses and terms overrule your fair use plans
    • Click-through contracts and EULAs that bind your use
    • Institutional licensing and access-controlled reposting
    • Linking safely when copying is restricted
  • Public domain and open licenses: lawful shortcuts to clarity
    • U.S. federal works and public domain materials
    • Creative Commons and rights statements you can rely on
  • Building a defensible workflow for data-driven projects
    • Document intent, transformation, and necessity
    • Minimize quantity: fields, rows, and resolution
    • Record sources, citations, and permissions
    • Plan for rights conflicts before publication
  • Risk signals courts watch for in database cases
    • Substitution risk and loss of licensing markets
    • Copying the “heart” of a compilation
  • Real-world patterns from the Fair Use Index
    • How courts weigh transformation in data contexts
    • When entire works or datasets still pass muster
  • Next steps to use database content with confidence today
  • FAQ
    • What does “database content” mean under U.S. copyright law?
    • When are facts protected and when are they not?
    • How does Section 107’s four-factor test apply to database use?
    • What makes a use “transformative” for data-driven projects?
    • How much can I copy from a dataset without crossing the line?
    • What market effects do courts care about?
    • Are database structures—schemas and metadata—copyrighted?
    • How does research or scholarship qualify as fair use with datasets?
    • What about news reporting and commentary?
    • How should educators and libraries handle database material?
    • When do license terms override fair use arguments?
    • Can I rely on linking instead of copying when licenses block reuse?
    • What role do public domain and open licenses play?
    • How do I build a defensible workflow for using datasets?
    • What are common risk signals courts track in database disputes?
    • What patterns have courts shown about transformation in data cases?
    • Can entire datasets ever be fair use?
    • What immediate steps can I take to use dataset material with confidence?

What “database content” means in U.S. copyright law

When you open a collection, ask: are you handling raw facts or expressive works? That question decides the legal path. Facts and most metadata are not copyrightable under U.S. law. You can often copy a factual number or date without copyright issues.

But creativity changes things. A photograph, essay, chart, or a crafted caption is a copyrighted work. Copying those items copies expression, not mere fact. Contracts can also restrict how you may use factual entries—even when copyright does not.

Facts versus expression: why raw data often isn’t protected

Telephone-style lists and numeric records typically report facts. Courts treat them as information, not authorship. If you retype a fact, copyright usually won’t block you. Still, check licenses and terms before commercial use.

When data becomes a copyrighted work

A curated list or an unusual arrangement can get “thin” protection for selection and structure. Minimal creativity — a unique layout or a distinctive caption — can cross the threshold into an original work.

  • Ask first: are you copying facts or expression?
  • Photographs and essays in a set remain individual works.
  • Schema and arrangement may carry limited copyright protection.
  • Document which fields are factual and which are expressive.

The legal backbone: Section 107 and the four-factor test

What test will courts apply when your team copies data for a report or product? Section 107 of the Copyright Act names four factors that judges weigh case‑by‑case. Follow them in order and document your reasoning.

Purpose and character

Ask: does your use add new meaning, critique, or analysis? Transformation favors a positive outcome. Educational or noncommercial aims help, but they do not guarantee a win.

Nature of the work

Factual materials prompt more leeway than highly creative works. Cite whether entries are raw data or a copyrighted work with expressive selection.

Amount and substantiality

Take only what your task needs. Avoid copying the “heart” even if it’s a small excerpt.

Market effect

Consider whether your feature would substitute for existing licenses or cut future revenue. Courts often treat this factor as decisive.

  • Do this: write a factor‑by‑factor memo before launch.
  • Do this: cite leading decisions and the Fair Use Index when you can.
  • Do this: limit quantity, prove necessity, and record research steps.
FactorKey questionPractical step
PurposeTransformative?Summarize added meaning
NatureFactual or creative?Flag expressive fields
MarketSubstitute risk?Model impact on licensing

Databases versus data: separating structure from contents

Think of the collection as two layers: the container and the entries inside. The container is the structure—fields, order, labels—and the entries are the raw facts that fill it. Treat these layers differently when you plan a project.

a detailed, technical illustration of a database in a minimalist, clean style. the foreground shows a central server rack or tower, with sleek metallic surfaces and subtle lighting accents. in the middle ground, there are rows of data storage devices and modular components, arranged in a precise, grid-like layout. the background features a plain, soft-toned backdrop, perhaps a studio environment with hints of architectural elements. the overall composition conveys a sense of order, efficiency, and the functional nature of database infrastructure, without extraneous details. the lighting is even and directional, highlighting the technical details of the database components.

Thin copyright in selection, coordination, and arrangement

A compilation can carry a thin copyright for creative selection and arrangement. Curating which records to include can reflect judgment that earns protection.

If you copy a layout or replicate selection wholesale, you risk copying that protected arrangement. Extract facts into a new schema to lower risk.

Metadata, schemas, and creative choices that carry rights

Field names, taxonomies, and ordering are often expressive choices. Those elements can be a form of copyright protection or other rights.

  • Separate container from contents: protect structure, but many rows are plain facts.
  • Map needed fields and relations—replicate only what is functionally necessary.
  • Contracts can govern access to factual materials even when copyright does not.
AspectLikely statusPractical step
Selection & arrangementThin copyrightCreate your own ordering
Raw factsUsually freeExtract into new structure
Schemas & labelsMay be expressiveRename and document choices

Fair use of database content in practice

Small choices—resolution, quantity, context—shape whether a lift is defensible. Keep decisions narrow. Record why each excerpt is needed. Short notes help later reviews.

Research and scholarship: quoting, sampling, and analysis

In research, quote tiny samples of expressive fields. Show only what proves your point. Pair excerpts with your own models or code to transform raw figures into analysis.

News and commentary: context that transforms raw facts

For data journalism, add visualization or critique. A chart that reframes numbers changes purpose. Thumbnails or low-resolution photographs can illustrate method without full reposting.

Teaching and libraries: access with proportion and purpose

In classrooms, link to licensed sources through your library instead of reposting materials. Use excerpts only as necessary and explain why each sample matters.

  • Limit exports to needed fields and rows.
  • Keep a log of examples, quantities, and rationale.
  • Credit sources—citation alone won’t replace a fair use analysis.
ScenarioPractical stepWhy it helps
Academic researchSample expressive fields; document necessityShows transformation and minimality
News reportingVisualize and critique raw figuresAlters purpose; reduces substitution risk
Teaching & libraryLink licensed access; use thumbnailsRespects licenses and preserves access

Bottom line: follow Section 107 factors in every project. Treat each excerpt as an example you must justify.

When licenses and terms overrule your fair use plans

Which written terms can strip away your legal options before you ever copy a record? Many sites post Terms that act as contracts. Clicking “I agree” often creates binding obligations that limit what you may do next.

Click-through contracts and EULAs that bind your use

Did you click a checkbox? That moment can impose limits on copying, scraping, and reposting. Read the license and the EULA. Note deletion, audit, or IP assignment clauses.

Institutional licensing and access-controlled reposting

Enterprise licenses often bar exports to external systems. Open reposting is usually banned. Access-controlled reposting may be allowed with conditions. Check with your library or contracts team before you proceed.

Linking safely when copying is restricted

When in doubt, link to the record instead of copying materials into your system. Linking preserves access and avoids violating a contract or copyright owner’s terms.

  • Did you click “I agree”? Track that contract in your project plan.
  • Confirm license scope, user counts, and permitted work with your library.
  • Keep screenshots minimal; verify that the terms permit them.
  • If a license conflicts with statutory rights, the license usually governs permitted use.
  • When planned use exceeds license limits, ask the copyright owner for permission.
RestrictionTypical clausePractical step
Copying rows or fieldsExport/scrape prohibitedRequest permission or link
Reposting materialsOpen reposting bannedUse access-controlled viewer or ask library
Audit & deletionRetention limits shownLog terms and renewal dates

Public domain and open licenses: lawful shortcuts to clarity

Searching for sources you can deploy with minimal legal friction?

Public domain materials give you a fast path. Works created by the U.S. federal government are public domain by statute. That means many NASA photos and federal reports are free to copy and transform—still verify exceptions and attribution rules.

U.S. federal works and public domain materials

Prefer public domain when timelines are tight and risk tolerance is low. Use CC0 datasets to remove hurdles. Even when attribution is not required, note provenance in your registry.

Creative Commons and rights statements you can rely on

Creative Commons licenses let you know exactly what you may do. Check ND, NC, and SA flags before integration. Filter sources with usage-rights tools—Google Advanced Image Search and government portals are good starting points.

  • Keep a verified list of open resources and portals your team trusts.
  • Record license version and URL at ingestion for every work you ingest.
  • Combine public-domain data with your proprietary models to build clear commercial advantages.
Source typeTypical statusPractical step
U.S. federal sites (NASA, USA.gov)Public domainVerify page notes; log URL
CC0 datasetsNo restrictionsIngest with attribution best practice
Creative Commons (CC BY/NC/SA)Conditional reuseFollow license terms; document version
Filtered image searchVaries by sourceUse filters; confirm original license

Building a defensible workflow for data-driven projects

Start every project with a one-page memo. State the goal, the transformation you will perform, and why each material is necessary. That memo becomes your first line of defense when questions arise.

Document intent, transformation, and necessity

Write clear intent: what you will change and why. Tie each excerpt to analysis or commentary. Cite MIT: crediting sources avoids plagiarism but does not cure infringement.

Minimize quantity: fields, rows, and resolution

Pre-specify exact needs. List fields, row counts, and image resolution. Use sampling, thumbnails, or summaries to limit what you pull.

Record sources, citations, and permissions

Log every source URL, license, and terms with dates and authorized users. Keep version notes in your registry.

Plan for rights conflicts before publication

Route gray-area uses to counsel early. Add license and rights checks to your pull request and release checklist. Prefer links over uploads when library licenses restrict redistribution.

  • One-page memo: goal, transformation, necessity.
  • Pre-specify: fields, rows, resolution.
  • Minimize: sample or thumbnail first.
  • Log: sources, license URLs, dates, users.
  • Escalate: counsel before publication.
StepActionWhy it helps
Intent memoWrite 1 pageDocuments purpose and necessity
Pre-specify dataList exact fields/rowsLimits quantity and substitution risk
Release checksInclude license & rights signoffPrevents last-minute legal surprises

Risk signals courts watch for in database cases

Courts flag a few concrete behaviors that predict trouble—spot them early.

Judges focus on market harm first. They ask whether your release replaces paid access or licenses. If it does, that signal favors a negative decision.

Substitution risk and loss of licensing markets

Does your product satisfy the same user need as the source? If yes, expect courts to weigh lost sales heavily. Bulk exports that mirror structure and selection look like substitution. At scale, similar projects can erode licensing revenue fast.

Copying the “heart” of a compilation

Even small excerpts can be fatal when they capture the core curated records. Lifting the heart of a work increases risk more than copying marginal rows. Republished material that satisfies identical demand is a red flag.

  • Does the release substitute for the source? High risk.
  • Bulk exports that reproduce selection or layout suggest copying.
  • Prefer analysis, models, or annotations over straight aggregation.
  • When multiple signals stack, get permission or redesign.
SignalWhy it mattersAction
SubstitutionLost licensing revenueLimit downloads; add paywall
Heart copiedCore curated value takenRedact key records; summarize
Mirrored structureSuggests replication beyond factsCreate new schema; rename fields

Real-world patterns from the Fair Use Index

What patterns emerge when judges catalog data rulings in a public index? The Index tracks Supreme, circuit, and district court decisions and lists categories like internet and digitization. It links to full opinions on Google Scholar, Justia, Westlaw, LEXIS, and PACER.

A well-lit, high-resolution image of a data visualization dashboard, showcasing real-world patterns and insights from the Fair Use Index. The dashboard features a sleek, minimalist design with clean lines and a neutral color palette. In the foreground, a series of interactive graphs and charts display key fair use metrics, such as the number of fair use cases, the types of works involved, and the factors considered by courts. The middle ground features a detailed timeline tracing the evolution of fair use doctrine over time. In the background, a subtle grid or matrix pattern evokes the underlying data and legal frameworks that shape fair use decisions. The overall mood is one of clarity, professionalism, and evidence-based analysis.

How courts weigh transformation in data contexts

Courts look for added analysis, context, or a new function. If your project changes how material works, that helps. Necessity matters—take only what the new purpose demands.

Pull citations from the Index. Read full opinions on Google Scholar or PACER for nuance. That step shows judges you considered section factors and copyright law.

When entire works or datasets still pass muster

Some decisions permit whole works when completeness is essential to the new work. Internet and digitization cases give many such examples. Track which materials were deemed excessive versus essential.

  • 1. Favor transformation that adds analysis or critique.
  • 2. Document necessity and minimality for each excerpt.
  • 3. Catalog examples internally to speed future reviews.
PatternWhy it mattersAction
TransformationShifts purposeAnnotate and analyze
NecessityLimits quantityRecord exact fields
CompletenessSometimes requiredNote citation & source

Next steps to use database content with confidence today

Ready to move from caution to practice with your next data project? Write a one‑page memo that states purpose and the transformation you will do. Keep it short. Keep it specific.

Then limit exports to the smallest slice needed. Prefer links and viewers rather than full uploads. Check license and terms. If anything is unclear, ask your library or counsel fast.

Prefer public domain or CC0 sources when speed and low risk matter. Log sources, rights, and approvals in a shared tracker. If scope grows, rerun your analysis before launch.

For edge cases, contact the copyright owner or seek alternative resources. Consult the Fair Use Index and read cited decisions for similar fact patterns. Bake these steps into product workflows and keep the playbook fresh.

FAQ

What does “database content” mean under U.S. copyright law?

In U.S. law, database material usually refers to collections—tables, lists, and records. Facts themselves aren’t protected; the protection may cover the original selection, coordination, or arrangement. So if you extract raw facts, you often face fewer copyright barriers than when you copy a creative compilation or a unique schema.

When are facts protected and when are they not?

Facts and pure data are not copyrightable; expression is. But a creative choice—how fields are arranged or which entries are included—can earn thin copyright. Courts focus on whether the element you copied reflects creativity rather than bare facts.

How does Section 107’s four-factor test apply to database use?

Judges weigh purpose and character, nature of the work, the amount used, and market effect. You increase your odds when your use is transformative, uses minimal portions, involves factual material, and does not replace a licensing market.

What makes a use “transformative” for data-driven projects?

Transformation happens when you add new meaning or new utility—analysis, annotation, or visualization that repurposes raw records. Merely copying records into a new format usually won’t qualify; adding insight, context, or novel processing helps.

How much can I copy from a dataset without crossing the line?

Copy only what’s necessary for your purpose—specific fields, selected rows, or lower resolution. The third factor demands proportionality. Courts examine whether you took the “heart” or full value of the compilation.

What market effects do courts care about?

Courts look for substitution—did your use supplant demand for the original? If your work undercuts a licensing market or harms expected revenue, that weighs against fair use. Preserve licensing value and avoid wholesale replication.

Are database structures—schemas and metadata—copyrighted?

Elements like metadata labels, schema design, and classification can show creativity and earn protection. Structural choices that reflect original selection or arrangement attract thin rights, so treat unique schemas cautiously.

How does research or scholarship qualify as fair use with datasets?

Academic analysis, quoted samples, and statistical processing often favor fair use—especially when you transform data to test hypotheses or produce commentary. Still, use minimal quantities and document your transformative purpose.

What about news reporting and commentary?

Reporting that incorporates data for context or analysis can be transformative. The key: add editorial value and avoid republishing full datasets that would substitute for the source product.

How should educators and libraries handle database material?

Limit copies to what’s pedagogically necessary, provide proper attribution, and use controlled access. Libraries can rely on preservation and scholarship exceptions in some cases, but licenses may restrict copying or redistribution.

When do license terms override fair use arguments?

Contracts—click-through agreements, EULAs, and institutional licenses—can impose obligations that bind users. Even if a use might qualify as fair under Section 107, breaching a signed license can trigger contract liability. Read terms and negotiate rights up front.

Can I rely on linking instead of copying when licenses block reuse?

Linking or embedding can avoid copying, but it’s not a universal fix. Some licenses forbid deep-linking or framing. Use links when permitted and prefer APIs or authorized feeds to reduce legal risk.

What role do public domain and open licenses play?

Public domain works and permissive licenses such as Creative Commons provide clear permissions. U.S. federal government works are generally public domain—use them freely. Always confirm license terms and attribute when required.

How do I build a defensible workflow for using datasets?

Document your purpose, how you transform data, and why each field is necessary. Minimize copied quantity, preserve provenance, and secure permissions when rights are unclear. Maintain logs and versioning to show intent and necessity.

What are common risk signals courts track in database disputes?

Courts flag substitution risk, reproduction of the compilation’s “heart,” and commercial exploitation that competes with licensing. High-volume copying or rehosting of datasets triggers scrutiny.

What patterns have courts shown about transformation in data cases?

The Fair Use Index shows courts favor transformation that adds analysis, visualization, or new interfaces. Uses that repurpose raw facts into new insights more often pass muster than straight republishing.

Can entire datasets ever be fair use?

Yes—when the use is highly transformative, necessary for the purpose, and does not harm the market. Courts have permitted full-dataset uses in narrow contexts such as critical research or public-interest reporting.

What immediate steps can I take to use dataset material with confidence?

Audit sources and licenses, limit extraction to essential fields, add unique analysis or transformation, record permissions, and consult counsel for high-risk projects. That approach minimizes legal exposure and preserves business value.
Citation, Licensing & Ethical Use Copyright Law BasicsData Distribution RightsDatabase Content OwnershipFair Use DoctrineFair Use GuidelinesIntellectual Property ProtectionLegal Use of Database InformationPrivacy and Data Rights

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