tm-spec

TM-Spec — Landscape & Strategic Positioning

Date: 2026-05-10. Goal: honest assessment of where TM-Spec stands relative to existing declarative DFT/MD formats (AiiDA, atomate2, AiiDAlab, FireWorks, CWL, Snakemake, NOMAD inputs, PWmat). Used for:

  1. Strategic decisions (avoid distracting from the first paper using TM-Spec)
  2. Grant application context
  3. Paper #1 introduction (positioning vs reproducibility tools)
  4. Onboarding contributors

Comparison Landscape (2026)

Tool Format “Scientist without Python” Standard? Ephemeral compute?
AiiDA + plugins Python WorkChain inputs (dict) No (Python required) Yes, academic standard Difficult (daemon needs stable host)
AiiDAlab (web UI) YAML/JSON via web form Yes (web UI generates inputs) Growing, ~ aiidalab-qe No (requires AiiDA daemon backend)
atomate2 + jobflow Python Maker classes No (Python + jobflow) Materials Project ecosystem Moderate
FireWorks Python + YAML workflow Partial Was the standard (~2018), declining No
Common Workflow Language (CWL) YAML Yes (but generic) Bioinformatics standard, not DFT Via Toil/Cromwell
Snakemake Python-flavored DSL Partial Bioinformatics + reproducibility crowd Via wrappers
NOMAD’s “Tools and Inputs” JSON/YAML upload Yes (browser) NOMAD ecosystem No (submit raw inputs only)
PWmat / Materials Studio GUI proprietary Yes Industry (Chinese labs) No
DFT-FE web tools (NSF CI) Web form Yes US academic, narrow Via cluster allocations
TM-Spec (ours) YAML + recipe registry Yes (YAML, Recipe abstracts away Python) Nobody (yet) Yes (orchestrator + ephemeral cloud GPU)

Niches Where TM-Spec Can Claim a Position

Niche 1 — Paper SI Format

Niche 2 — Ephemeral Cloud Compute

Niche 3 — Domain-Specific Recipes

Niche 4 — Educational / Reproducibility


Honest Assessment: Can We Become a Standard?

No, if we compete head-to-head with AiiDA.

Yes, if we find a complementary niche and occupy it carefully.


Strategic Recommendations

  1. The first paper using TM-Spec is the test case. If the SI with TM-Spec YAML passes peer review well (reviewers say “convenient, readable, understood the setup immediately”) — that is a signal the niche is real.
  2. Do not build an AiiDA-killer. Recipe registry is for our lab + opt-in for the community. Do not position TM-Spec as “better than AiiDA”.
  3. Publish TM-Spec on GitHub under the MIT license. Schema + validator + extractor + lint + sanity_fill = standalone tool with no dependency on the orchestrator. Anyone can use it as paper SI tooling.
  4. AiiDA bridge — later. If someone in the community requests a “TM-Spec → AiiDA archive converter”, we will build it. Not preemptively.
  5. Possible long-term positioning: TM-Spec becomes the second standard for paper-grade reproducibility (vs AiiDA for lab-internal provenance). They coexist: AiiDA for the full provenance graph during active research, TM-Spec for the final paper SI artefact.

Precedents — How Small Declarative Formats Became Standards

All of these standards grew from simple text format + tool ecosystem + early adopters. TM-Spec follows the same pattern:


Key Risks

  1. Prescribing a scope we cannot sustain. TM-Spec as an “AiiDA-killer” → failure. TM-Spec as a “narrow Fe-S DSL” → may work.
  2. Recipe registry feature creep. Every author wants their own recipe. Solution: minimal core registry + community extensions via PyPI plugins.
  3. Schema versioning without a community. As the sole user, the schema can evolve freely. If other labs adopt it, a compatibility layer becomes necessary. Solution: SemVer + freeze v1.0 after the first paper is accepted.
  4. NOMAD competing. NOMAD has its own Metainfo schema. We leverage it via alignment (D-01..D-04), not competing. But if NOMAD introduces its own “submission template” YAML, we risk duplicating effort. Solution: track NOMAD development + stay compatible.

What We Are Doing Now (Before the First Paper Submission)

  1. ✅ TM-Spec v0.3 is ready (schema + 6 pilots + 5 tools).
  2. ⏳ Submission in ~one week — paper #1 SI appendix in TM-Spec format as the first publication-grade artefact.
  3. ⏳ After submission — monitoring reviewer feedback. If positive → publish TM-Spec on GitHub under MIT, write a blog post, post to Bluesky/Mastodon in the materials science community.
  4. ⏳ Q-TMSPEC-9..11 (recipe registry + orchestrator runtime) — after submission, as a medium-term investment.

What We Are NOT Doing Now


References