adjacent-atlas

Methodology

Adjacent Atlas answers one question: within a field, which methods, instruments, and concepts are adjacent to the current frontier — close enough to be the next thing worked on — and which of those already have momentum?

What counts as a signal

Two public signal sources:

These are normalised into a graph of nodes (concepts, methods, instruments, datasets, implementations, results) connected by weighted edges (relates, depends, cites, implements, supersedes).

What “adjacency” means here

Adjacency is not novelty alone, nor popularity alone. It is a deliberate blend: something is adjacent when it is moving (momentum, recency), connected to the rest of the field (connectivity), not yet saturated (novelty), and buildable (feasibility). The scoring model in docs/scoring-model.md makes this concrete.

The reference domain

The shipped graph is extreme-precision radial velocity (EPRV) instrumentation. It was chosen because progress there is gated by instrument systematics as much as by ideas, so the difference between “interesting” and “reachable” is sharp.

Honesty about the seed

The bundled seed’s signals values (activity series, implementation counts, maturity) are illustrative scaffolding that exercise the model across a realistic range. They are not measured statistics. Live snapshots replace them with values from the fetch scripts.

Reading the scores honestly

The scoring is a transparent heuristic, and its boundary matters as much as its output. The honest limitations — attention versus merit, proxy noise, the subjectivity of the weights, and the absence of any predictive claim — are set out in field-notes/scoring-limitations.md.

Field notes

Authored, researcher-voice context lives alongside this document:

These are commentary, not data. The seed’s activity numbers are illustrative; real snapshots come from the ingestion pipeline (docs/data-sources.md).