docs(blog): data quality (#2675)

Author: andrewpollock

gcp/appengine/blog/content/posts/announcing-data-quality-initiatives/index.md

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+---
+title: "OSV's approach to data quality"
+date: 2023-09-30T09:00:00Z
+draft: false
+author: Andrew Pollock and Charl de Nysschen
+---
+OSV's mission is to enable developers to reduce security risk arising from known
+vulnerabilities in open source components they use.
+
+Part of the strategy to accomplish that mission is to provide a comprehensive,
+accurate and timely database of known vulnerabilities covering both language
+ecosystems and OS package distributions.
+
+Today, OSV.dev's coverage is fast approaching 30 ecosystems, while also
+importing records from almost as many disparate "[home databases](https://ossf.github.io/osv-schema/#id-modified-fields)".
+As this number of federated data sources continues to grow, so does the prospect
+of OSV records being expressed in ways that are detrimental to them being
+effectively utilized in aggregate.
+
+To ensure the accuracy and usability of OSV.dev's data at scale we have
+initiated a program of work to prevent future regression in data quality as the
+ecosystem of data contributions continues to grow.
+<!--more-->
+
+In our
+[experiences](https://www.first.org/conference/vulncon2024/program#pThe-Trials-and-Tribulations-of-Bulk-Converting-CVEs-to-OSV)
+from [interacting with the CVE Program and broader
+ecosystem](https://osv.dev/blog/posts/introducing-broad-c-c++-support/), we've
+found that the term "data quality" means different things to different people.
+
+For OSV.dev, the primary objective is to enable awareness and remediation of
+known vulnerabilities in open source components. To this end, "data quality"
+means being able to reason about and act upon vulnerability records at scale.
+This is why the OSV format was designed to enable machine-readability as its
+primary use case. In order to programmatically reason about OSV records at
+scale, a degree of consistent use of fields beyond what can be validated using
+JSON Schema validation alone is necessary.
+
+Problems that the OSV Data Quality Program seeks to address include:
+
+- No way for record providers to know there are problems with records they have already
+published
+- OSV.dev accepts non-schema-compliant records OSV.dev accepts records
+with other validity issues (such as invalid package names or non-existent
+package versions)
+- No turnkey way for an OSV record provider to bring the data
+quality problem forward, to earlier in the record publication lifecycle
+- No best practice tooling for OSV records to be created by a new OSV record provider
+- [Downstream data consumers often mistake OSV.dev as the originator for the data
+and provide feedback about it to us, rather than the record's originator](https://google.github.io/osv.dev/faq/#ive-found-something-wrong-with-the-data)
+- Git repository owners may not be following best-practice release processes (such as
+not using tags, or by using unusual tag naming conventions), confounding
+OSV.dev's ability to resolve fix commits for fix versions, which isn't known
+until the first time a vulnerability referencing the repository is published
+
+We have published our current opinion on the [Properties of a High Quality OSV
+Record](https://google.github.io/osv.dev/data_quality.html), which goes above
+and beyond JSON Schema compliance, and are working on an open source [OSV record
+linting tool](https://github.com/ossf/osv-schema/tree/main/tools/osv-linter) to
+programmatically validate records against these properties.
+
+Thereafter, we will begin gating record imports to records that meet the quality
+requirements.
+
+In order for the operators of home databases that OSV.dev imports from to be
+able to reason about the acceptability of records published, they will be able
+to:
+
+- run the OSV linter against their records as part of their publication
+workflow
+- review OSV.dev's import findings about their records
+
+You can follow our [progress on this journey on
+GitHub](https://github.com/orgs/google/projects/62). Input and contributions
+are, as always, appreciated.
+
+If you're responsible for an existing home database that OSV.dev imports records
+from, we will contact you directly before there are any changes to the record
+import process that may impact you. You can also consider proactively running
+our OSV record linter on your existing records to see how they rate.
+
+If you'd like to experiment with or help expand the capabilities of the OSV
+record linter, it's [currently residing in the OpenSSF OSV Schema GitHub
+repository](https://github.com/ossf/osv-schema/tree/main/tools/osv-linter).
+
+As an end-consumer of OSV.dev's data, we hope that this blog post encourages you
+to continue to have confidence in the capabilities enabled by that data into the
+future.