Direct answer
An open-web sourcing stack combines multiple public evidence surfaces instead of relying on one network.
The stack layers
Use X-Ray for discovery, GitHub for technical evidence, OpenAlex or Semantic Scholar for research evidence, registries for healthcare, contact finders for professional contact paths, and ATS rediscovery for owned history.
Operating notes
- Map the role to evidence surfaces.
- Use at least two independent lanes.
- Separate discovery from contact enrichment.
- Save searches that produce signal.
Why this matters
Hard-to-fill candidates do not all express themselves in the same place. Engineers may show evidence on GitHub. Researchers may show evidence in papers. Clinicians may show evidence in licenses and registries.
Trust rules
Open-web does not mean anything goes. Respect terms, privacy, opt-outs, and manual-source boundaries.
SourcingOS workflow
SourcingOS helps keep the source lanes visible so you can show where the search worked and where it failed.
Copy-paste starting strings
site:github.com (Kubernetes OR Terraform) "Platform Engineer"
site:openalex.org "computer vision" "deep learning"
site:linkedin.com/in ("Data Engineer" OR "Analytics Engineer") (dbt OR Airflow)FAQ
Is open-web sourcing scraping?
Not inherently. It means using publicly accessible sources and respecting platform rules.
What is the best first lane?
For technical roles, usually GitHub plus X-Ray. For healthcare, registries and local market search.