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GITHUB × STACK OVERFLOW × DATABASE, FOR SCIENTISTS

A failed experiment nobody wrote down gets repeated.

Somewhere else. By someone junior. Next month. SciCollab keeps the data, the code, the conditions and the argument in one place — including the runs that didn't work.

Connect ORCID → startBook a lab pilot

Free for individual researchers · institutional pilots start at one lab

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Product Method cards For institutions Pricing Docs
GITHUB × STACK OVERFLOW × DATABASE, FOR SCIENTISTS

A failed experiment nobody wrote down gets repeated.

Somewhere else. By someone junior. Next month. SciCollab keeps the data, the code, the conditions and the argument in one place — including the runs that didn't work.

Free for individual researchers · institutional pilots start at one lab
debug(research) → knowledge
NEGATIVE RESULT MC-0412 · v4 12 forks · 8 reproductions
Lipofection of HEK293T at low passage
A. Rivera · forked from MC-0288 · updated 2026-09-04
METHOD
Lipofectamine 3000
CELL LINE
HEK293T · p<12
CONDITIONS
37 °C · 5% CO₂ · 48 h
OUTCOME
38% ± 6 · below target
FAILS UNDER
Passage above 18, or serum-free medium at transfection. Both tried, both below 5%. Recorded so nobody in this lab loses another week to it.
This is a Method Card — structured, versioned, forkable, and it records the conditions under which the method fails.
TWO PEOPLE, ONE PLATFORM
THE RESEARCHER
Fast, credible context — before you repeat the failure.

Your literature review is fragmented across four tools. Your data, code and notes live in three more. Asking a colleague depends on who happens to be reachable. SciCollab collapses that into one search across people, projects, datasets, methods and discussions.

→Ask with the data attached, not a paraphrase of it
→Find the prior failure before you fund the repeat
→Measured on time-to-first-actionable-answer, not page views
RESEARCH OPS & R&D LEADERSHIP
A governed environment where lab knowledge outlives the postdoc.

Tacit knowledge leaves when researchers leave. Duplicated failures are invisible. Onboarding runs on informal memory. SciCollab makes reuse measurable and the record auditable — SSO, per-field access control, full audit log.

→SAML / eduGAIN SSO, provisioned per lab
→Onboarding time, internal reuse rate, audit readiness
→Start with one to three labs, expand on evidence
FOUR THINGS, ORGANISED
01
Artifact-rich questions

A question is never plain text. It carries the data, the code, the images and the context that produced it.

02
Structured metadata

Method, conditions, outcomes — captured as a first-class object, not a paragraph in a PDF.

03
Provenance

Versioning and timestamps on every artifact. Who changed what, when, and what it looked like before.

04
Retrieval

Find the relevant prior case — and the person behind it. AI surfaces and structures; the community validates.

FIRST-CLASS OBJECT
Negative and null results

Not a footnote. Not a graveyard section. A citable, reusable object with the same weight as a positive result — and its own scored axis on your profile. Orange, deliberately not red: a failure that reproduces is a contribution.

FIRST-CLASS OBJECT
Method Cards

Structured, versioned, forkable records of how something was actually done — including the conditions under which it failed. Fork one, run it, and your result attaches to the card whether it worked or not.

Science made easy.
debug(research) → knowledge