USDR Early Stewards / Advisors — Call for Interest (June 2026 Launch Sprint) #286
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📌 Early Stewards call — read this first (The opening post below is the outreach calendar archive; this comment is the live call for interest.) We're preparing the public launch of the Universal Science Discovery Repository (USDR) — an open, git-native, version-controlled catalog of science's unknowns, cross-domain mathematical bridges, and falsifiable hypotheses. Current scale (verified at launch):
To move from solo-seeded foundation to genuine community-owned infrastructure, we are calling for the first cohort of Early Stewards / Launch Advisors (target: 8–15 people). What the role actually is
Time commitment: 1–3 hours/month on average. Who we're looking forResearchers (any career stage) with depth in one or more scientific domains who want to help shape open cross-domain discovery infrastructure. We especially want voices from physics, biology/medicine, complex systems, network science, computational fields, and open science practice. What you get
How to express interestReply to this discussion with:
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Launch execution update (2026-06-21)Crosscheck story is live in-repo — we ran the first public Crosscheck repro for the habitat fragmentation ↔ percolation bridge on a laptop (~15s). Result: INCONCLUSIVE at quick-trial Monte Carlo settings (by design); increasing trial count is the documented next step to confirm or falsify ν ≈ 4/3.
Early Stewards charter: Maintainer action needed: Please pin this discussion and share the short X/LinkedIn version from Interested in stewarding? Reply with your field + one open problem you wish were in a global map. |
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Ready to post (2026-06-21)Launch copy is consolidated — copy/paste from
Crosscheck repro link (fixed): https://kr8zysho3.github.io/Universal-Science-Discovery/repro/p-b-habitat-percolation-ecology-fss/index.html Please pin this discussion if not already pinned. |
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Project: Universal Science Discovery Repository (USDR)
Launch Window: ~30 days from late May 2026 through mid-July 2026 (target public v0.5.0 on 2026-06-25)
Repo (use in all CTAs): https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Live Docs: https://kr8zysho3.github.io/Universal-Science-Discovery/
Primary Contribution CTA (Happy Path — always link this): https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
Contributing Guide: https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/CONTRIBUTING.md
Vision & Messaging: https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/VISION_COMMUNICATION.md
How to use this package:
All copy is launch-ready, professional, high-signal, and aligned with VISION_COMMUNICATION.md.
Copy-paste directly. Customize handles, dates, and current entry counts from LAUNCH_STATS_2026-06.md before posting.
Every major post includes: suggested timing (UTC and US timezones), hashtags, image/graphics ideas + alt text, primary + secondary CTAs.
Update numbers weekly from the live repo (2 seeded unknowns + 2 hypotheses in Physics/Biology as of late May baseline; grow during pre-launch).
Pair with the 30-day calendar below. Track performance in LAUNCH_STATS_2026-06.md.
Core 30-second pitch (use verbatim or lightly adapted):
"The Universal Science Discovery Repository (USDR) is a living, version-controlled map of every major unknown in science, plus structured, testable hypotheses to solve them. Think of it as arXiv + GitHub + a global to-do list for humanity's biggest open problems. The goal is to make scientific discovery faster, more collaborative, and more intentional."
Why Git (short version for every post): "Git gives us perfect versioning of knowledge evolution, safe forking of radical ideas, PR-based peer review with full attribution, and true decentralization — all while staying human-readable and forkable."
30-Day Launch Calendar (Late May – Mid-July 2026)
Assumptions & Notes:
Launch Day target: Wednesday, June 25, 2026 (strong mid-week engagement; adjust ±2 days for real calendar).
"Now" baseline: 2026-05-28. Pre-launch soft activities begin immediately.
All times are suggestions. Post when your audience is active (researchers: 9am–2pm local in major timezones; X is global).
Pre-launch = relationship building + content seeding + asset prep. No mass spam.
During launch week: stagger posts by 60–120 minutes across platforms for maximum organic spread.
Post-launch: 80% engagement/responding, 20% new value posts. Reply to every serious comment/DM within 24h using Response Playbook.
Channels covered: X/Twitter (primary velocity), LinkedIn (depth + professionals), Reddit (r/OpenScience flagship + targeted subs), Direct (email/DM — highest value), GitHub (owned), supporting (HN, Mastodon, academic lists).
Success = researchers taking the happy path and opening PRs/issues.
Pre-Launch Soft Phase (May 29 – June 20, 2026) — Build Momentum Quietly
May 29–31 (Thu–Sat): Kickoff & Asset Finalization
Audit & update all seed content (add 1–2 more high-quality entries if possible).
Finalize hero banner + 6 supporting graphics (see "Graphics Ideas" section below).
Create short 60–90s screen recording of happy path + contributor hub.
Personal 1:1 outreach begins to 10–15 warm researcher contacts (use email/DM templates below). Goal: private feedback + early commitments.
Update LAUNCH_STATS_2026-06.md with exact current counts.
Internal dry-run of response playbook with team.
June 1–7 (Sun–Sat): Targeted 1:1 Outreach Sprint + Teaser Content
Daily: Send 5–8 personalized researcher emails or DMs (physics, biology, CS/AI-for-science, open-science advocates). Track in private sheet.
June 2 (Mon): Soft teaser on personal X account: "Quietly building something researchers have needed for decades. More soon." (image: simple "map of unknowns" concept). No repo link yet.
June 4 (Wed): Post 1 LinkedIn short update (personal profile): "Spending the month stress-testing a new way to surface high-leverage research gaps. Excited by early conversations with colleagues in physics and aging biology."
June 6 (Fri): Seed 1 new cross-domain entry or expand a discipline README. Commit + small internal note.
Mid-week: Private Google Doc or Notion preview sent to 5–8 researchers who replied positively. Collect structured feedback.
End of week: 20+ 1:1 touches completed. At least 3 researchers agree to "review on launch day and consider contributing."
June 8–14 (Sun–Sat): Content Seeding + Graphics Lock + Broader Soft Teasers
Continue 1:1 outreach (another 15–20 researchers). Prioritize PIs and lab leads who can bring groups.
June 9 (Mon): Second personal X teaser with real seed example screenshot (dark matter unknown + hypothesis). "One of the first entries we're shipping at launch — explicit unknowns with proposed tests, fully versioned."
June 11 (Wed): LinkedIn long-ish post (personal + any institutional page if available): Share the "why Git for science" framing + one concrete example. Link to VISION_COMMUNICATION.md (public). Soft ask for intros.
June 12–13: Produce final graphics. Record 1 more short video (researcher explaining value of structured hypotheses).
June 14 (Sat): Internal launch rehearsal. Walk through full calendar, assign owners for each post, prepare reply templates in a shared doc.
Goal by end of week: 8–12 total structured entries in repo (up from baseline 4), 30+ 1:1 outreaches sent, 8–12 positive replies.
June 15–20 (Sun–Fri): Final Prep + Warm Launch List Building
Lock repo content for launch (no major structural changes).
Prepare v0.5.0 release notes draft (highlight seeded content, happy path, governance completeness).
June 16 (Mon): Third X teaser: "The first 10 researchers outside the founding group now have early access to the draft repo. Their feedback has been gold."
June 18 (Wed): Final LinkedIn short: "One week out from something I'm very proud of. If you're a researcher tired of rediscovering what your field already knows is unsolved, this is for you. DM me."
June 19–20: Send "launch day preview" email to warmest 15–20 contacts (use generic template + personalized note). Include one-pager PDF + exact launch timing.
GitHub: Ensure all issues/PR templates, labels, and branch protection are production-ready.
Final graphics + alt text review. Prepare scheduled posts where platform allows.
June 20 close: 40–50 total outreaches sent. 15–25 warm leads. Repo has 10–15 polished entries. All assets ready.
Launch Window (June 21–25, 2026) — Coordinated Public Debut
June 21–22 (Sat–Sun): Soft Public Teasers (Owned Channels Only)
GitHub Discussions: Enable and pin a "Welcome & Launch Megathread" (pre-written using response playbook language).
Personal X + LinkedIn: "Repo goes fully public Wednesday. Here's the one link every researcher should have bookmarked..." (link to happy path only — no hard sell).
Refresh LAUNCH_STATS with pre-launch final numbers.
June 23–24 (Mon–Tue): Pre-Launch Hype + Last 1:1
June 23 (Mon morning UTC): Post main X thread draft (dry run, no link or "link in bio" style if needed). Gather early quote tweets from warm contacts.
June 23 afternoon: Send final "go time tomorrow" note to warm list.
June 24 (Tue): Reddit r/OpenScience post scheduled or posted late (see full post below). LinkedIn long post scheduled for early Wednesday.
All owners confirm they can be online for first 4–6 hours of replies on launch day.
June 25, 2026 — LAUNCH DAY (Wednesday) — Full Coordinated Blast Recommended global stagger (adjust to your timezone):
13:00 UTC / 9:00 AM ET / 6:00 AM PT: GitHub v0.5.0 release published + pinned repo announcement (use release notes + README hero update).
13:30 UTC: X main thread posted (full thread below). Pin it.
14:00 UTC: LinkedIn long post published (long version below). Also post the short version as a follow-up or separate update.
14:30 UTC: Reddit r/OpenScience flagship post live (full post below). Monitor r/Physics, r/biology, r/MachineLearning, r/academia for natural crossposts or comments.
15:00–18:00 UTC: Email blast to warm list + any academic mailing lists you have access to (use generic template + personal note). Include direct links.
Throughout day: Repost supporting shorter X posts (see below). Engage every comment using Response Playbook. Like/quote positive researcher replies.
Evening UTC: One "first 12 hours" update post on X + LinkedIn with early metrics (stars, comments, first PRs if any).
Supporting actions on launch day:
Enable GitHub Sponsors (if not already) with clear "micro-grants for high-priority unknowns" note.
Post in 2–3 relevant open-science Slacks/Discords (as individual, not spam).
DM the 5–8 warmest contacts: "Live now — would love your thoughts and any unknowns you'd like to add."
Monitor LAUNCH_STATS and note first inbound interest.
Post-Launch Follow-Up Phase (June 26 – July 15, 2026) — Convert Interest to Contributions
June 26–28 (Thu–Sat): Immediate Engagement & Amplification
Daily "wins" posts: "First external researcher opened a PR today — here's the unknown they surfaced in CS theory." (with link to specific commit or PR).
X: 2–3 shorter supporting posts daily (see examples below). Reply to every @mention.
LinkedIn: Comment thoughtfully on 10–15 relevant posts in open science / research ops groups.
Reddit: Thoughtful, non-spammy comments in related threads (use playbook language). One additional value post in r/academia or r/GradSchool if natural.
Email: Personalized thank-yous + "here's how to contribute your specific gap" to everyone who replied positively.
June 29 – July 5 (Sun–Sat): Contributor Spotlights + Deep Value
June 30 (Mon): "Week 1 recap" long LinkedIn post + X thread: metrics, new seeded entries (credit contributors), top questions answered.
July 1–3: Spotlight 2–3 early contributors (with permission). "Dr. X just added the first hypothesis in quantum-biology cross-domain. Here's why it matters."
July 4 (Sat): "How to contribute in 30 minutes" walkthrough post (screenshots of happy path + live dashboard). Link the happy path doc heavily.
Continue 1:1 follow-ups with anyone who showed interest but hasn't contributed yet.
July 6–12 (Sun–Sat): Momentum & Next Milestones
X/LinkedIn: Announce first "Unknowns Hackathon" interest list (virtual, late Q3). Link simple Google Form.
Reddit: Value post in r/OpenScience or discipline subs: "What high-impact unknown in your field would you add first to a global map? (real examples from USDR launch week)"
Direct: Second wave of 20–30 targeted emails/DMs to researchers in adjacent fields (neuroscience, climate, chemistry) using personalized templates.
GitHub: Open or encourage "good first unknown" issues labeled clearly.
Mid-week metrics update post across channels.
July 13–15 (Sun–Tue): 30-Day Close & Transition
July 13–14: Full 30-day retrospective post (X thread + LinkedIn longform): exact stats vs targets from LAUNCH_STATS, lessons, new contributors highlighted, roadmap teaser for Phase 1.
July 15 (Tue): "The map is now live and growing. Here's how you can still be an early contributor." Final strong CTA push + link to happy path.
Archive or update this package with what worked.
Handoff notes to maintainers for steady-state growth (per ROADMAP.md and GOVERNANCE.md).
Plan content calendar for July–September (monthly "state of the unknowns" updates, etc.).
Ongoing Rhythm After July 15:
1 flagship value post per week (new entry highlight, contributor story, or methodology deep-dive).
Daily light engagement on X/LinkedIn.
Monthly metrics + new seed summary.
Quarterly Unknowns-focused events.
Graphics & Visual Asset Ideas (Use Across Calendar)
Primary Hero / Banner (all major posts):
Clean dark/light scientific aesthetic. Large title "USDR — The Map of What We Don't Know Yet". Sub: "arXiv + GitHub for open problems". Subtle line-art of connected nodes + Git commit graph. Include small YAML snippet and hypothesis icon.
Alt text: "Universal Science Discovery Repository launch graphic: a structured, version-controlled catalog of scientific unknowns and hypotheses."
Post-Specific Graphics:
"30-Minute Contribution" infographic: Step-by-step visual (Clone repo → Copy seed YAML example → Edit your unknown/hypothesis → Validate with one script → Open PR). Use happy path steps. Alt: "Contribute your first research gap to USDR in under 30 minutes following the documented happy path."
Before/After: Scattered PDF icons + "lost in literature" vs. clean YAML cards in Git + searchable catalog. Alt: "From fragmented papers to a living, versioned map of scientific unknowns."
Seed Example Cards: Beautiful cards for the two seeded pairs (dark matter + radio-axion hypothesis; aging translatability + metabolic bottlenecks). Show linked structure. Alt: "Example USDR entry: high-priority unknown in dark matter microphysics with a linked active hypothesis proposing targeted radio detection programs."
Contributor Hub Screenshot: Clean capture of dashboard/index.html running locally (hero + nav + links to unknowns/hypotheses). Alt: "USDR contributor hub — your starting point for exploring seeded content and the exact path to your first contribution."
Knowledge Graph Concept: Simple force-directed or hierarchical diagram showing disciplines + cross-domain bridges + unknowns/hypotheses as nodes. Even a hand-sketched or Mermaid version works for launch. Alt: "Early vision of the USDR knowledge graph: explicit unknowns and hypotheses connected across physics, biology, computer science, and emerging cross-domain areas."
"Why Git for Science" visual: Git logo + branching diagram labeled "Versioned knowledge evolution", "Safe forking of radical ideas", "PR peer review + attribution", "Decentralized & forkable forever".
Recommended tools: Canva, Figma, or simple code (Mermaid, matplotlib + nice styling) for reproducibility. Host images in repo under docs/outreach/assets/ or external CDN with permanent links. Always include descriptive alt text for accessibility.
Hashtags (use 3–6 per post, mix): #OpenScience #ScientificDiscovery #ResearchInfrastructure #GitForScience #USDR #OpenResearch #Hypothesis #Reproducibility #AcademicTwitter #PhDChat
Primary CTA (always first): Link to Happy Path doc + "Start here — contribute your first unknown or hypothesis in under an hour." Secondary CTAs: Repo link, Live docs, "DM me your field’s biggest open problem", "Star the repo to follow growth".
Ready-to-Post: Reddit r/OpenScience Post (Flagship Launch Post)
Suggested timing: Launch Day 2026-06-25, 14:30 UTC (morning US, afternoon Europe). Post once; do not spam other subs immediately. Crosspost to r/Physics, r/biology, r/MachineLearning only if organic and high-value (or let community do it).
Title (exact): USDR: A living, Git-versioned map of scientific unknowns + testable hypotheses (arXiv + GitHub for what we don't know yet). Early seed content live — feedback and contributions welcome.
Body (copy-paste ready):
Hi r/OpenScience,
I'm launching the Universal Science Discovery Repository (USDR) — an open-source, Git-based infrastructure project to make the highest-leverage open problems in science explicit, structured, versioned, and collaboratively actionable.
What it is:
A living catalog of unknowns (research gaps) with clear statements of what is not known, why it matters, and what has been tried (metadata + open links only).
Linked hypotheses — structured, testable statements with proposed experiments, evidence pointers, and falsification criteria.
Everything in clean YAML under Git, with schemas, validation, PR review, full attribution, and forkability.
Think arXiv + GitHub + a global, community-maintained "to-do list" for discovery.
Why now / why this format: Right now the most important unknowns live scattered across papers, grant proposals, and hallway conversations. Brilliant people waste years on problems others already knew were dead ends or low-leverage. Cross-domain insights are rare because no one has a shared map of the white space.
Git is unusually well-suited here: perfect versioning of how our understanding of a gap evolves, safe forking of speculative ideas, PRs as a lightweight peer-review mechanism, and permanent decentralized attribution. (Full reasoning in the repo.)
Current Phase 0 seed (live at launch):
2 high-priority unknowns + 2 linked active hypotheses in Physics (dark matter microphysics) and Biology (longevity intervention translatability across species).
3 discipline anchors (Physics, Biology, Computer Science).
Full governance, ethics, legal, and methodology framework.
usdr-ingest pilot (arXiv OAI-PMH metadata only — no PDFs).
Documented "happy path" to contribute your first unknown + hypothesis in under 60 minutes.
Concrete next step (this is the important part): If this resonates, the fastest way to see the quality bar and contribute is the documented happy path. Clone, copy a seed example, add one gap from your own field, validate, and open a PR. Everything is designed for researchers, not just programmers.
Full repo: https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Live documentation: https://kr8zysho3.github.io/Universal-Science-Discovery/
Genuine asks:
Researchers: What is the highest-impact unknown in your subfield right now that should be in a global map? (Open an issue or PR — templates provided.)
Feedback on the schemas, templates, and framing.
Intros to colleagues or labs who think in terms of open problems rather than just publishing the next paper.
This is infrastructure, not a research project. Early contributors will shape governance and have outsized visibility as the map grows. No hype — just disciplined, high-signal work on the actual bottlenecks to discovery.
Happy to answer any questions here or in the repo. Let's draw the map of what we don't know together.
Image to attach: "30-Minute Contribution" infographic or side-by-side seed example cards (dark matter + aging biology).
Flair / tags: Use "Open Science", "Infrastructure", "Discussion" if available.
Follow-up strategy: Reply to every top-level comment using the Response Playbook below. After 48h, post a "top questions from launch" comment or new thread.
Ready-to-Post: LinkedIn Posts
Long Version (Primary Launch Post)
Suggested timing: Launch Day 2026-06-25, ~14:00 UTC (good for US morning / EU afternoon professional readership). Post as personal profile + any relevant company/university page. Also schedule a short follow-up 4–6 hours later.
Post text:
I'm thrilled to announce the public launch of the Universal Science Discovery Repository (USDR) — open-source, Git-based infrastructure for discovery-first science.
For years I've watched brilliant researchers spend enormous effort rediscovering that a problem was already known to be unsolved, or miss high-leverage connections across fields simply because the "white space" isn't mapped anywhere.
USDR changes that.
It is a living, version-controlled catalog of explicit scientific unknowns paired with structured, testable hypotheses — all in clean YAML, fully attributed, forkable, and reviewable via standard Git workflows. Think of it as arXiv + GitHub + a global, community-curated map of the highest-impact open problems in science.
Current seed (live today):
High-priority unknowns in dark matter microphysics and cross-species translation of longevity interventions, each with linked active hypotheses proposing concrete next experiments.
Discipline anchors in Physics, Biology, and Computer Science.
Complete governance, ethics, legal, and reproducibility framework from day one.
A documented path for any researcher to contribute their first high-quality unknown + hypothesis in under an hour.
Why Git? It is the only widely adopted system that gives us versioning of knowledge evolution, safe forking of speculative ideas, PR-based lightweight peer review with permanent attribution, and true decentralization — without requiring new platforms or centralized gatekeepers.
The repo is now public: https://github.com/KR8ZYSHO3/Universal-Science-Discovery
If you are a researcher (especially in physics, biology, AI/ML for science, or any field where you regularly think "this gap is holding the whole area back"), I would love for you to take 30 minutes and try the happy path. Add one real unknown from your work. See the quality bar for yourself.
Early contributors will help shape how this evolves and will be recognized as founding participants in what I believe will become foundational scientific infrastructure.
This is not about replacing journals or peer review. It is about making the input into that system dramatically better: clearer problems, better awareness of prior attempts, and faster identification of high-leverage opportunities.
Full vision and careful framing (how we talk about this without unnecessary resistance): https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/VISION_COMMUNICATION.md
I am especially interested in:
Feedback from active researchers on the schemas and contribution experience
Intros to labs or PIs who want to steward a subdomain
Early ideas for the first virtual "Unknowns Hackathon" later this year
The map of what we don't know is waiting to be drawn — together.
Link in first comment for easy access.
Image: Primary hero banner + "30-Minute Contribution" infographic side-by-side (or the before/after scattered papers vs structured map visual).
Hashtags: #OpenScience #ScientificDiscovery #ResearchInfrastructure #USDR #GitForScience #OpenResearch #Reproducibility
Call to action in post + first comment: Primary happy path link + repo link + "Comment or DM me the biggest open problem in your field right now."
Short Version (Follow-up or Standalone Update)
Suggested timing: Launch Day +4 hours, or any weekday 10am–1pm in major research timezones during the 30-day window. Use for daily/every-other-day momentum.
Post text:
Just launched USDR — a Git-native, versioned map of scientific unknowns and testable hypotheses.
Seeded with real high-priority gaps in dark matter physics and aging biology translation, plus full contributor tooling and governance.
Researchers: the fastest way in is here → https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
What unknown in your field belongs on the global map? Drop it in the comments or a PR.
Repo: https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Image: Seed example card (one of the two seeded pairs) or contributor hub screenshot.
Hashtags: #OpenScience #USDR #ScientificDiscovery
CTA: Happy path + "Tag a colleague who should see this."
Ready-to-Post: Twitter/X Thread (Main Launch Thread + Shorter Supporting Posts)
Main Thread Timing: Launch Day 2026-06-25, 13:30 UTC (prime global overlap).
Thread (copy as separate tweets; number them):
1/ The Universal Science Discovery Repository (USDR) is now public.
We're building a living, Git-versioned map of the most important unknowns in science — paired with structured, testable hypotheses.
arXiv + GitHub + a global to-do list for discovery.
Repo: https://github.com/KR8ZYSHO3/Universal-Science-Discovery
2/ Right now the highest-leverage open problems are scattered across thousands of papers and conversations.
Researchers waste years on questions others already knew were low-value or already attempted.
Cross-domain breakthroughs stay rare because no shared map of the white space exists.
3/ USDR fixes the map.
Every entry is a clean YAML record: explicit unknown statement, why it matters, what has been tried (open links + DOIs only), linked hypotheses with proposed tests and falsification criteria.
Everything versioned. Everything attributed. Fully forkable.
4/ Why Git?
Because it is the only tool that naturally gives us:
Versioning of how our understanding of a gap evolves over time
Safe forking of radical or speculative ideas
PRs as lightweight, transparent peer review with permanent credit
Decentralization — no single platform owns the map
This is infrastructure that can last 50+ years.
5/ Phase 0 seed is live today:
• Dark matter microphysics unknown + radio/axion detection hypothesis (Physics) • Longevity intervention cross-species translatability unknown + metabolic bottlenecks hypothesis (Biology) • Computer Science anchor ready for expansion
Full governance, schemas, validation, and "add your first entry in <60 min" path included.
6/ The single best way to understand the quality bar and contribute immediately:
https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
Clone → copy an example → add one real gap from your field → validate → PR.
No gatekeeping. High standards.
7/ This is not about replacing journals, peer review, or arXiv.
It is about making the input into those systems dramatically better — clearer problems, less duplicate effort, faster recognition of high-impact opportunities.
Anchored in the same principles that made arXiv and Git successful.
8/ Who this is for:
Researchers who feel the current literature system wastes too much of their time
People who regularly think "the real bottleneck is that we don't even agree on what the open problems are"
Anyone who wants their work to have maximum leverage across fields
Early contributors shape governance and get lasting visibility.
9/ Genuine invitation:
If you're a researcher, open-science advocate, or lab lead — take 30 minutes and try the happy path.
Then tell me (or open an issue) what the highest-impact unknown in your subfield is that deserves a permanent, versioned home.
The map is only as good as the people drawing it.
10/ Links:
Repo (star & contribute): https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Happy path (start here): https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
Full vision & careful framing: https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/VISION_COMMUNICATION.md
Live docs: https://kr8zysho3.github.io/Universal-Science-Discovery/
Let's make scientific discovery faster and more intentional — together.
Image for tweet 1: Primary hero banner.
Image for tweet 5: Seed example cards (dark matter + aging side by side).
Image for tweet 6: "30-Minute Contribution" infographic.
Hashtags (end of tweet 10 or 1): #OpenScience #USDR #ScientificDiscovery #GitForScience
Follow-up shorter posts (use in days after launch or as daily momentum during 30-day window):
Post A (next day or launch +6h): "First 8 hours: strong researcher interest across physics and computational biology. Two external contributors already exploring the happy path.
The highest-leverage thing you can do today: add one unknown from your own work.
https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
#OpenScience"
Post B: "Common question: 'Why not just use a wiki or Notion?'
Because we need versioned evolution of the map itself, safe forks for radical ideas, and PR attribution that travels with the contributor forever. Git does all of that natively and has for 20 years.
Full reasoning in the repo."
Post C: "Researchers: what is one high-impact open problem in your field that almost everyone in your subfield agrees is important but chronically under-attacked?
Reply or open an issue. We'll help structure it properly for the catalog.
https://github.com/KR8ZYSHO3/Universal-Science-Discovery"
Post D (contributor spotlight style): "Day 3 highlight: [Name or @handle, with permission] just contributed the first cross-domain unknown bridging [field A] and [field B].
This is exactly why we built it.
Full happy path for your own contribution: [link]"
(Repeat with real early wins.)
Post E (metrics / momentum): "Week 1 numbers (transparent):
X new structured entries (unknowns + hypotheses)
Y external PRs / high-quality issues
Z researchers in active conversation
The map is growing because people are adding real gaps they care about.
Join them: [happy path link]"
Researcher Email / DM Pitch Templates
General notes for all outreach:
Personalize the first 2–3 sentences with specific reference to their recent paper, talk, or known interest (e.g. "I saw your work on X and the open question around Y...").
Keep under 150–200 words.
Always include 2 links: happy path + repo.
Subject lines for email: short, benefit-oriented, no hype.
Send from personal or project email. Follow up once after 7–10 days if no reply.
Track in a private spreadsheet (name, field, source of contact, date sent, response, next action).
Generic Template (Email or DM)
Subject (email): A structured map of open problems in [their field / science] — early feedback welcome
Hi [Name],
I came across your work on [specific paper/topic or "in [field]"] and have been thinking about how much time researchers lose because the most important unsolved questions aren't tracked in any shared, versioned, high-signal way.
I'm launching the Universal Science Discovery Repository (USDR) — a Git-native catalog of explicit scientific unknowns paired with structured, testable hypotheses. It uses the same principles that made arXiv and Git successful: open, versioned, attributable, forkable, and researcher-first.
Phase 0 seed is live with real entries in physics (dark matter microphysics) and biology (longevity intervention translation), plus complete governance and a documented path for anyone to contribute their own gaps in under an hour.
Would you be willing to take 20–30 minutes to look at the happy path and tell me what you think — or even add one unknown from your own research?
Repo: https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Start here (happy path): https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
No pressure at all — even a quick "this resonates / needs work" reply helps.
Thank you for the work you do.
Best,
[Your Name / @handle]
Personalized Example 1: Physics / Astrophysics Researcher (e.g., dark matter or cosmology adjacent)
Subject: Dark matter microphysics gap + a structured hypothesis approach — early USDR feedback
Hi [Name],
Your recent work on [specific constraint / haloscope / axion search] made me think of how many independent efforts are attacking overlapping parts of the same fundamental unknown without a shared, living map of the remaining parameter space and experimental approaches.
I'm launching USDR (Universal Science Discovery Repository) — a Git-based, version-controlled catalog of high-priority scientific unknowns with linked testable hypotheses.
One of the first seeded entries is exactly in this area: an explicit unknown on the particle/field microphysics of galactic dark matter, paired with a hypothesis around targeted radio-line and haloscope programs.
The structure is deliberately minimal and researcher-native (YAML + Git + PR review). The goal is to make it trivial for people doing the actual experiments to surface, refine, and connect gaps.
I'd value 15 minutes of your eyes on the current framing and any unknowns you think are higher priority or missing from the current literature synthesis.
Happy path (see the exact format): https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
Repo: https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Would love your candid take.
Best regards,
[Your Name]
Personalized Example 2: Biology / Aging / Longevity Researcher
Subject: Cross-species translation of longevity interventions — structured unknown + hypothesis catalog launching
Hi [Name],
I've followed your lab's work on [specific intervention class or model organism translation challenge] with great interest. The heterogeneity of endpoints and the difficulty of quantitative cross-species prediction feels like one of the highest-leverage open problems in the field right now.
I'm launching the Universal Science Discovery Repository — a Git-native system for making exactly these kinds of gaps explicit, versioned, and collaboratively attackable with structured hypotheses.
We seeded an early entry on the translatability of longevity and healthspan interventions validated in model organisms to human-relevant outcomes, with a linked hypothesis around conserved metabolic control nodes.
The format is designed for biologists (not just programmers): clean YAML, clear falsification criteria, proposed tests, and full provenance via Git.
If you have 20 minutes, I'd be grateful for your view on the current draft and — more importantly — what other high-impact unknowns in aging biology or related areas you would want surfaced in a global map.
Happy path: https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
Full repo (live today): https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Thank you for pushing this area forward.
Warmly,
[Your Name]
Personalized Example 3: Computer Science / AI-for-Science Researcher
Subject: AI for scientific discovery — mapping the unknown unknowns
Hi [Name],
Your work on [AI-driven hypothesis generation / literature synthesis / autonomous labs / etc.] highlights a meta-problem that keeps coming up: even the best AI systems are limited by how well we have captured what humanity actually does not know yet.
I'm launching USDR — the Universal Science Discovery Repository — a Git-based, structured catalog of scientific unknowns and testable hypotheses designed to be both human- and AI-consumable.
The early focus is on seeding high-signal content in physics and biology, but the architecture (schemas + cross-domain bridges + knowledge graph export plans) is explicitly built for the AI-for-science community to both contribute to and consume from.
One of the long-term bets is that grounding future models on an explicit, versioned map of ignorance (rather than just published findings) will dramatically improve hypothesis quality and reduce hallucinated "solved" problems.
Would you have time for a quick look at the current seed and schemas? I'm particularly interested in how people in your community would want to interact with or extend this.
Start here: https://github.com/KR8ZYSHO3/Universal-Science-Discovery/blob/main/docs/HAPPY_PATH_FIRST_RECORDS.md
Repo: https://github.com/KR8ZYSHO3/Universal-Science-Discovery
Appreciate any thoughts.
Best,
Brandon Shoemaker
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