TheorIA – An Open Curated Physics Dataset (Equations,Explanations,JSON)
We’re building TheorIA— an open, high quality dataset of theoretical physics results: equations, derivations, definitions, and explanations — all in structured, machine- and human-readable JSON. Why? Physics is rich with beautiful, formal results — but most of them are trapped in PDFs, LaTeX, or lecture notes. That makes it hard to: - train symbolic/physics-aware ML models, - build derivation-checking tools, - or even just teach physics interactively. THEORIA fills that gap. Each entry includes: A result name (e.g., Lorentz transformations) Clean equations (AsciiMath) Straightforward…
What it does
In the maker’s words, at launch
We’re building TheorIA— an open, high quality dataset of theoretical physics results: equations, derivations, definitions, and explanations — all in structured, machine- and human-readable JSON. Why? Physics is rich with beautiful, formal results — but most of them are trapped in PDFs, LaTeX, or lecture notes. That makes it hard to: - train symbolic/physics-aware ML models, - build derivation-checking tools, - or even just teach physics interactively. THEORIA fills that gap. Each entry includes: A result name (e.g., Lorentz transformations) Clean equations (AsciiMath) Straightforward step-by-step derivation with reasoning Symbol definitions & assumptions Programmatic validation using sympy References, arXiv-style domain tags, and contributor metadata Everything is in open, self-contained JSON files. No scraping, no PDFs, just clear structured data for physics learners, teachers, and ML devs. Contributors Wanted: We’re tiny right now and trying to grow. If you’re into physics or symbolic ML: Add an entry (any result you love) Review others' derivations Build tools on top of the dataset GitHub https://github.com/theoria-dataset/theoria-dataset/ Licensed under CC-BY 4.0, and we welcome educators, students, ML people, or just anyone who thinks physics deserves better data.
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