The Dead Sea Scrolls Visualized

Hacker News

The Dead Sea Scrolls is one of the greatest archaeological discoveries in recent history, and its relevance is bolstered since it is of interest to Judaism, Christianity, and Islam. I had heard of the discovery as a kid, but was surprised to realize how little I knew about it once I started reading books and watching videos by Hebrew Bible scholars on the topic. I made deadseainsights.com to explore the discovery in an interactive and visually-engaging way. I was also very interested in the differences between the Dead Sea Scroll texts, which are dated to 250 BC - 150 AD, and the Masoretic text (specifically the Leningrad Codex), which is dated to around 1008 AD. To do this, I could not use information from the books I read, since the text and translations are under copyright. I was able to find permissively-licensed transcriptions of the Dead Sea Scrolls and the Leningrad Codex, for which I am grateful. You can find more information about that on the homepage. Since HN is probably interested in my tech-stack: I kept it simple and built a static website that uses Bootstrap and D3. It’s hosted on AWS S3 and distributed to 108 edge locations via AWS CloudFront. So far, hosting has been under the free-tier limits and has cost me nothing. Thank you for any feedback you’d like to give. -dandeto

Visit product View on Hacker NewsOct 26, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: codex, new, visual · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video, visualize, way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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