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Research & Academia

Structured, citable web data for serious studies

Computational social science, economics and information-systems research increasingly depends on web-scale observation — but ad-hoc scraping produces datasets that can't be replicated, audited or cited with confidence.

Heroku supports research programs with methodologically documented collection, stable schemas, observation timestamps and archive-oriented delivery. We work with research teams to define sampling frames and document limitations honestly, because a study is only as good as its weakest methodological link.

Use Cases

What teams actually do with this

Replicable collection design

Documented source profiles and sampling approaches suitable for methods sections and replication packages.

Longitudinal studies

Scheduled observation over semesters or years with consistent schemas and archival storage.

Custom corpora

Domain-specific public-web corpora built to research specifications, with provenance metadata.

Ethics-aligned practice

Public data only, respectful collection rates and no personal-data collection — aligned with institutional review expectations.

Signals we monitor

The observation layer

Methods documentation
Schema stability across waves
Archival & replication support
Ethics-first collection policy
Recommended practices

Where teams start

Most research & academia programs begin with monitoring and intelligence, then add delivery into internal systems.

Public-web intelligence for research & academia

Tell us the decisions your team is making this quarter. We'll map the signals that inform them — feasibility first.

1 comment

Sofia Marchetti

The replication-package framing is compelling. Our IRB’s biggest objection to web datasets is always methodology opacity.

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