--- name: brycewang-stanford/earth-system-science-data source: https://app.decimal.ai/s/brycewang-stanford-earth-system-science-data@1/SKILL.md source_sha256: 784e5591f66f --- # Earth System Science Data (earth-system-science-data) ## Journal positioning Earth System Science Data (ESSD) is the Copernicus / European Geosciences Union venue for **data papers**: peer-reviewed articles whose primary product is an original, high-quality, openly deposited dataset of lasting value to earth-system science. The defining expectation is not a new scientific conclusion but a **reusable dataset**: the manuscript documents how the data were produced, calibrated, quality-controlled, and how others should reuse them, while the dataset itself lives in a FAIR public repository with its own persistent identifier (DOI). An analysis or interpretation paper that mines data toward a hypothesis, or a paper whose data are not openly and permanently available, is a fundamental misfit here. This skill is a **fit / venue-selection / re-framing** tool. It does not replace the journal's current author guidance. Before submitting, re-check the live ESSD / Copernicus author instructions and data policy. ## When to trigger - The author has produced an original dataset (observations, reanalysis, compilation, model output) and wants to publish it as a citable data paper rather than a research article. - A measurement campaign or long-term record needs a venue that rewards the data product itself, separate from any later analysis paper. - The author is choosing between ESSD as a data paper and a domain journal (e.g. `water-resources-research`, `global-biogeochemical-cycles`) for an analysis paper. - The author needs ESSD's open-deposition-with-DOI requirement and quality/reuse documentation bar. ## Scope & topic fit - Original observational datasets across the earth system: atmosphere, ocean, land surface, cryosphere, biosphere, solid earth, and human–environment interfaces. - Long-term monitoring records, field/campaign measurements, and instrument or station networks with documented provenance. - Harmonized compilations and syntheses that merge heterogeneous sources into a single consistent, value-added product. - Gridded products, reanalyses, and model output of broad reuse value, with versioning and uncertainty information. - Remote-sensing and retrieval datasets with algorithm description, validation, and quality flags. - Methodologically novel data-processing or quality-control workflows when the resulting dataset is the deliverable. ## Method & evidence bar - The dataset must be **original and reusable**, not a re-packaging of an already-published product; novelty lies in the data, not in an interpretation. - The data must be **openly deposited in a FAIR repository with a persistent DOI** before acceptance; a "data available on request" statement does not satisfy the journal. - Production must be fully documented: instruments, sampling, calibration, processing chain, versioning, and the exact contents and format of the deposited files. - Quality must be demonstrated with quantitative quality control, validation against independent references where possible, and explicit, traceable uncertainty. - Reuse must be enabled: clear metadata, variable definitions, units, flags, file structure, and guidance on appropriate and inappropriate uses. - The dataset's value and the user community it serves should be argued concretely, not asserted. ## Structure & house style - Copernicus data-paper format; the manuscript and the deposited dataset are reviewed together — re-check current article types and structure on the live guide. - The text must describe data generation and documentation, not advance a scientific hypothesis; interpretation belongs in a companion analysis paper elsewhere. - A prominent **data availability statement** must give the repository, DOI, version, and license; the DOI must resolve to the actual data. - Figures and tables should characterize the dataset (coverage maps, time–space sampling, validation scatter, uncertainty, flag distributions), not argue a result. - Open-access, open-review, and open-data are the norm; the deposited files must match what the paper describes exactly. ## Official-submission checklist - Before giving submission-ready advice, read `../../resources/source-basis.md` and `../../resources/official-source-map.md`; start from the Copernicus/ESSD anchors, then cite the current ESSD page you checked. - Search the live site for "Earth System Science Data author guidelines" and follow the current Copernicus version. - Confirm the dataset is deposited in an **approved FAIR repository with a resolving DOI, version, and an open license**, and that the deposited files match the manuscript. - Re-check the data-paper structure, abstract/format expectations, and any required dataset metadata or repository criteria. - Re-check open-access terms, interactive open-review procedure, competing-interests, funding, author-contribution, and AI-use disclosure. - If the live official instructions conflict with this skill, the official instructions win. ## Pre-submission self-check - [ ] The deliverable is a reusable dataset, not an analysis/interpretation paper. - [ ] The data are deposited in a FAIR repository with a resolving DOI, version, and open license. - [ ] Production, calibration, processing, and file contents are fully documented. - [ ] Quality is shown with quantitative QC, validation, and traceable uncertainty. - [ ] Metadata, variable definitions, units, and flags enable independent reuse. - [ ] The deposited files exactly match what the manuscript describes. ## Common desk-reject triggers - An analysis/interpretation paper submitted as if it were a data paper. - A dataset that is not openly available with a resolving DOI, or is "available on request." - Re-packaging of an already-published dataset with no original, value-added product. - Insufficient documentation of production, quality control, or uncertainty. - Metadata too sparse for independent reuse (missing units, flags, or variable definitions). - A mismatch between the deposited files and the dataset described in the manuscript. ## Re-routing decision - The dataset underpins a scientific conclusion → an analysis venue such as `communications-earth-and-environment` or a domain journal, with ESSD as the data citation. - Carbon/nutrient flux data feeding a budget analysis → `global-biogeochemical-cycles`. - Hydrologic data feeding a process/method study → `water-resources-research` / `journal-of-hydrology`. - Climate model/reanalysis output used for a climate-science argument → `journal-of-climate`. - Solid-earth/geochemical data interpreted as a process result → `earth-and-planetary-science-letters`. ## Output format ```text [Fit] High / Medium / Low (one-line reason) [Target] Earth System Science Data [Data product] [Deposition] [Quality/documentation] [Top risk] [Official items to re-check] [Re-route suggestion] ```