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README.md

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+---
+license: cc-by-4.0
+#User-Defined Tags
+tags:
+  - CMEMS
+  - Marine forecast
+  - Reanalysis
+  - Physical Ocean
+  - Global Ocean
+language:
+  - en
+  - zh
+---
+<p align="center">
+  <strong>
+    <span style="font-size: 30px;">CMEMS</span>
+  </strong>
+</p>
+
+
+## Dataset Description
+
+CMEMS is an HDF5 gridded dataset for global ocean forecasting tasks. By integrating satellite and in situ observations with numerical ocean models, it provides real-time analyses, forecasts, and historical reconstructions for a variety of variables.
+
+## Supported Tasks
+
+This standardized data repository contains 7 annual files covering 1993-1999. Each file provides ocean variable fields, global means, and global standard deviations, and can be used for XiHe model training, validation, testing, inference input, and evaluation.
+
+## Dataset Format and Structure
+
+Each annual file is in HDF5 format and follows the path pattern `data/<year>.h5`. Each file contains:
+
+| HDF5 Path | shape | dtype | Description |
+|---|---|---|---|
+| `fields` | `[3, 96, 2041, 4320]` | `float32` | 3 time samples, 96 variables, and a global grid |
+| `global_means` | `[1, 96, 1, 1]` | `float32` | Global means aligned with the variable order |
+| `global_stds` | `[1, 96, 1, 1]` | `float32` | Global standard deviations aligned with the variable order |
+
+`fields.attrs["variables"]` contains the names of 96 variables, and `fields.attrs["time_step"]` is 24. The detailed schema is provided in `metadata/schema.yaml`.
+
+## How to Use the Dataset
+
+This dataset is compatible with the `OneScience-Sugon/XiHe` model.
+
+
+Download the dataset:
+
+```bash
+hf download --dataset OneScience-Sugon/CMEMS --local-dir ./CMEMS
+```
+
+
+## Official OneScience Information
+
+| Platform | OneScience Main Repository | Skills Repository |
+|---|---|---|
+| Gitee  | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
+| GitHub  | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
+
+## Limitations and License
+
+CMEMS follows an open data policy consistent with CC-BY-4.0 principles (official license agreement), and the dataset is licensed under CC-BY-4.0.

README_zh.md

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+---
+license: CC-BY-4.0
+#用户自定义标签
+tags:
+  - CMEMS
+  - Marine forecast
+  - Reanalysis
+  - Physical Ocean
+  - Global Ocean
+language:
+  - en
+  - zh
+---
+<p align="center">
+  <strong>
+    <span style="font-size: 30px;">CMEMS</span>
+  </strong>
+</p>
+
+
+## 数据集描述
+
+CMEMS 是用于全球海洋预报任务的 HDF5 网格数据集。它通过整合卫星与现场观测数据并运行海洋数值模型，提供多种变量的实时分析、预报及历史重建数据。
+
+## 数据集支持的任务
+
+本标准化数据仓库包含 1993-1999 年 7 个年度文件，每个文件提供海洋变量场、全局均值和全局标准差，可用于 XiHe 模型训练、验证、测试、推理输入和评测。
+
+## 数据集的格式和结构
+
+每个年度文件为 HDF5，路径模式为 `data/<year>.h5` 文件内包含：
+
+| HDF5 路径 | shape | dtype | 说明 |
+|---|---|---|---|
+| `fields` | `[3, 96, 2041, 4320]` | `float32` | 3 个时间样本、96 个变量、全球网格 |
+| `global_means` | `[1, 96, 1, 1]` | `float32` | 与变量顺序对齐的全局均值 |
+| `global_stds` | `[1, 96, 1, 1]` | `float32` | 与变量顺序对齐的全局标准差 |
+
+`fields.attrs["variables"]` 包含 96 个变量名，`fields.attrs["time_step"]` 为 24。详细 schema 在 `metadata/schema.yaml`。
+
+## 数据集使用方式
+
+本数据集适配 `OneScience-Sugon/XiHe`模型。
+
+
+下载数据集：
+
+```bash
+hf download --dataset OneScience-Sugon/CMEMS --local-dir ./CMEMS
+
+```
+
+
+## OneScience 官方信息
+
+| 平台 | OneScience 主仓库 | Skills 仓库 |
+|---|---|---|
+| Gitee  | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
+| GitHub  | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
+
+## 限制与许可证
+
+CMEMS 采用与 CC-BY-4.0 原则一致的开放数据政策（官方许可协议），许可证同CC-BY-4.0。

data/1993.h5

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data/1994.h5

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manifest.yaml

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+onescience_manifest_version: "0.1"
+resource_type: dataset
+resource:
+  id: OneScience/CMEMS
+  name: CMEMS
+  domain: earth
+  domain_tags: [earth, ocean, cmems]
+  task: ocean_forecasting
+  task_tags: [ocean_forecast, train_data, eval_data]
+  modalities: [gridded_field]
+  input_formats: [hdf5]
+  output_formats: []
+  summary: CMEMS 是适配 OneScience/XiHe 的 1993-1999 年全球海洋预报 HDF5 数据集。
+
+platform_resource:
+  primary:
+    platform: modelscope
+    repo_id: OneScience/CMEMS
+    repo_type: dataset
+    url: https://modelscope.cn/datasets/OneScience/CMEMS
+    revision: main
+    readme_path: README.md
+    manifest_path: manifest.yaml
+  mirrors: []
+  access:
+    visibility: public
+    license: null
+
+website_integration:
+  enabled: true
+  click_target:
+    platform: modelscope
+    resource_url: https://modelscope.cn/datasets/OneScience/CMEMS
+  llm_handoff:
+    readme_required: true
+    manifest_required: true
+    download_readme_first: true
+    resolve_related_models: true
+    default_run_goal: dataset_validation
+
+runtime:
+  enabled: true
+  onescience_domain: earth
+  min_onescience_version: null
+  supported_execution: [local, local_slurm, remote_slurm, scnet_mcp]
+
+onescience:
+  repo: https://gitee.com/onescience-ai/onescience
+  official_links:
+    gitee:
+      doc: https://gitee.com/onescience-ai/onescience-doc
+      onescience: https://gitee.com/onescience-ai/onescience
+      skills: https://gitee.com/onescience-ai/oneskills
+    github:
+      doc: https://github.com/onescience-ai/OneScience-doc
+      onescience: https://github.com/onescience-ai/OneScience
+      skills: https://github.com/onescience-ai/oneskills
+  install:
+    required_by_default: false
+    command: bash install.sh earth
+  source_paths: []
+  compatibility:
+    examples_path: null
+    status: standard_first
+
+environment:
+  install_mode: onescience_domain
+  python: "3.11"
+  hardware:
+    cpu: supported
+    gpu: optional
+    dcu: optional
+  extra_dependencies: [h5py, numpy, pyyaml]
+
+runtime_package:
+  kind: dataset_package
+  package_root: .
+  standard_layout:
+    workdir: .
+    config_dir: metadata
+    checkpoint_dir: null
+    data_dir: data
+    output_dir: null
+  apply_policy:
+    mode: direct_use
+    target: session_workdir
+    overwrite: true
+    protect_installed_onescience: true
+  entry_files:
+    - metadata/schema.yaml
+    - metadata/file_checksums.sha256
+    - scripts/validate_dataset.py
+  entrypoints:
+    preflight: scripts/validate_dataset.py
+    inference: null
+    train: null
+    finetune: null
+    evaluate: null
+    visualize: null
+    deploy: null
+
+files:
+  model_files: []
+  dataset_files:
+    - id: cmems_1993_h5
+      path: data/1993.h5
+      role: train_data
+      description_zh: 1993 年 CMEMS HDF5 年份文件，包含 fields、global_means 和 global_stds。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source:
+        platform: modelscope
+        repo_id: OneScience/CMEMS
+        repo_type: dataset
+        path: data/1993.h5
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset
+      mirrors: []
+      local_path: CMEMS/data/1993.h5
+      size: 10157335296
+      checksum: sha256:57c694c0faf46cb5762751fffca473aeba783fb029288c2c1dea62c50a4b16e8
+      large_file: true
+    - id: cmems_1994_h5
+      path: data/1994.h5
+      role: train_data
+      description_zh: 1994 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1994.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1994.h5
+      size: 10157335296
+      checksum: sha256:d31d57c292518b799f2dafac6e57663ee5bdb2128c5f7286ae9b4afdc4a51859
+      large_file: true
+    - id: cmems_1995_h5
+      path: data/1995.h5
+      role: train_data
+      description_zh: 1995 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1995.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1995.h5
+      size: 10157335296
+      checksum: sha256:f86f6a02ebaa852b7ed88ceafc0dd4d4def09ec53269d1aba71031bd3ac0f7fe
+      large_file: true
+    - id: cmems_1996_h5
+      path: data/1996.h5
+      role: train_data
+      description_zh: 1996 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1996.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1996.h5
+      size: 10157335296
+      checksum: sha256:ffe95335363b97d97744b310af22f1fc9b79a77446bf0c8981dd27e77e3b0098
+      large_file: true
+    - id: cmems_1997_h5
+      path: data/1997.h5
+      role: train_data
+      description_zh: 1997 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1997.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1997.h5
+      size: 10157335296
+      checksum: sha256:2d9c427a4fe6e9ee621edff3a641c088e506b7c5ee0d9ab0928d98d2aacfb5fc
+      large_file: true
+    - id: cmems_1998_h5
+      path: data/1998.h5
+      role: eval_data
+      description_zh: 1998 年 CMEMS HDF5 年份文件，XiHe 标准配置用于验证。
+      required: true
+      required_for: [preflight, train, evaluate]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1998.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1998.h5
+      size: 10157335296
+      checksum: sha256:c25a62f81c720663fddec49a081568e7a5a46e767204e67ab9945e7c121d6e43
+      large_file: true
+    - id: cmems_1999_h5
+      path: data/1999.h5
+      role: inference_input
+      description_zh: 1999 年 CMEMS HDF5 年份文件，XiHe 标准配置用于测试、推理和评测。
+      required: true
+      required_for: [preflight, inference, evaluate]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1999.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1999.h5
+      size: 10157335296
+      checksum: sha256:a3a8040afb56ad2bee79d19fb8bd6b44d47411c8417ada95b063ef91cfbb08de
+      large_file: true
+    - id: cmems_schema
+      path: metadata/schema.yaml
+      role: schema
+      description_zh: HDF5 结构、shape、dtype、attrs、变量列表和划分说明。
+      required: true
+      required_for: [preflight]
+      format: yaml
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: metadata/schema.yaml, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/metadata/schema.yaml
+      size: null
+      checksum: null
+      large_file: false
+    - id: cmems_checksums
+      path: metadata/file_checksums.sha256
+      role: checksum
+      description_zh: 数据文件 SHA256 校验清单。
+      required: true
+      required_for: [preflight]
+      format: text
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: metadata/file_checksums.sha256, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/metadata/file_checksums.sha256
+      size: null
+      checksum: null
+      large_file: false
+  config_files:
+    - id: validate_dataset_script
+      path: scripts/validate_dataset.py
+      role: preflight_script
+      description_zh: 数据集读取、schema、attrs、shape、dtype 和可选 SHA256 校验脚本。
+      required: true
+      required_for: [preflight]
+      format: python
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: scripts/validate_dataset.py, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/scripts/validate_dataset.py
+      size: null
+      checksum: null
+      large_file: false
+  sample_files: []
+
+dataset:
+  format: [hdf5]
+  sample_unit: one daily ocean state transition sample per time index
+  schema:
+    path: metadata/schema.yaml
+  checksums:
+    path: metadata/file_checksums.sha256
+    algorithm: sha256
+  splits:
+    train: [1993, 1994, 1995, 1996, 1997]
+    validation: [1998]
+    test: [1999]
+  structure:
+    hdf5_datasets: [fields, global_means, global_stds]
+    fields_shape: [3, 96, 2041, 4320]
+    stats_shape: [1, 96, 1, 1]
+    dtype: float32
+    time_step_hours: 24
+
+relations:
+  required_datasets: []
+  optional_datasets: []
+  compatible_models:
+    - id: OneScience/XiHe
+      role: train_data
+      required_for: [preflight, train, inference, evaluate, visualize]
+      resource_ref:
+        platform: modelscope
+        repo_id: OneScience/XiHe
+        repo_type: model
+        url: https://modelscope.cn/models/OneScience/XiHe
+        revision: main
+        readme_path: README.md
+        manifest_path: manifest.yaml
+      expected_local_path: XiHe/data/data
+      adapter: XiHe/scripts/prepare_runtime_data.py
+
+run_matrix:
+  scenarios:
+    - name: dataset_validation
+      capability: preflight
+      default: true
+      description_zh: 验证 CMEMS 数据集目录结构、HDF5 schema、shape、dtype、attrs 和统计量。
+      required_datasets:
+        - id: OneScience/CMEMS
+          role: self
+          local_path: .
+      required_model_files: []
+      required_data_files: [data/1993.h5, data/1994.h5, data/1995.h5, data/1996.h5, data/1997.h5, data/1998.h5, data/1999.h5]
+      preconditions:
+        - cwd 为下载后的 CMEMS 数据集仓库根目录。
+      command_refs:
+        - commands.preflight.validate_structure
+      outputs: []
+    - name: dataset_checksum_validation
+      capability: preflight
+      description_zh: 在结构验证基础上读取全部 7 个大文件并校验 SHA256，耗时较长。
+      required_datasets:
+        - id: OneScience/CMEMS
+          role: self
+          local_path: .
+      required_model_files: []
+      required_data_files: [data/*.h5, metadata/file_checksums.sha256]
+      preconditions:
+        - cwd 为下载后的 CMEMS 数据集仓库根目录。
+      command_refs:
+        - commands.preflight.validate_with_checksums
+      outputs: []
+    - name: prepare_for_xihe
+      capability: prepare
+      description_zh: 与 OneScience/XiHe 模型配合时，由模型包脚本将本数据集整理到 XiHe/data/data。
+      required_datasets:
+        - id: OneScience/CMEMS
+          role: train_data
+          local_path: CMEMS
+      required_model_files: [XiHe/scripts/prepare_runtime_data.py, XiHe/conf/config.yaml]
+      required_data_files: [CMEMS/data/*.h5]
+      preconditions:
+        - OneScience/XiHe 下载到 ./XiHe。
+        - OneScience/CMEMS 下载到 ./CMEMS。
+      command_refs:
+        - commands.prepare.prepare_for_xihe
+      outputs:
+        - XiHe/data/data/*.h5
+        - XiHe/data/stats/global_means.npy
+        - XiHe/data/land_mask.npy
+
+capabilities:
+  inference: false
+  train: false
+  finetune: false
+  evaluate: false
+  visualize: false
+  deploy: false
+
+commands:
+  download:
+    - name: download_dataset
+      description: 下载 CMEMS 数据集标准仓库。
+      target: dataset
+      repo_id: OneScience/CMEMS
+      source: .
+      local_path: ./CMEMS
+      required: true
+      required_for: [preflight, train, inference, evaluate]
+      command: modelscope download --dataset OneScience/CMEMS --local_dir ./CMEMS
+    - name: download_compatible_model
+      description: 下载适配模型 XiHe。
+      target: model
+      repo_id: OneScience/XiHe
+      source: .
+      local_path: ./XiHe
+      required: false
+      required_for: [train, inference, evaluate]
+      command: modelscope download --model OneScience/XiHe --local_dir ./XiHe
+  prepare:
+    - name: prepare_for_xihe
+      description: 调用 XiHe 模型包脚本，把 CMEMS 数据组织成 XiHe 运行布局。
+      cwd: ./XiHe
+      command: python scripts/prepare_runtime_data.py --dataset-root ../CMEMS --runtime-data-dir ./data
+      required_files: [../CMEMS/data/1993.h5, scripts/prepare_runtime_data.py]
+      required_env: [python, h5py, numpy]
+      expected_outputs:
+        - path: data/data/1993.h5
+          type: file
+      success_criteria: [exit_code == 0, output_path_exists]
+  preflight:
+    - name: validate_structure
+      description: 快速读取每个 HDF5 文件的结构、变量、shape、dtype 和统计量。
+      cwd: .
+      command: python scripts/validate_dataset.py --dataset-root .
+      required_files: [metadata/schema.yaml, metadata/file_checksums.sha256, data/1993.h5, data/1999.h5]
+      required_env: [python, h5py, numpy, pyyaml]
+      expected_outputs: []
+      success_criteria: [exit_code == 0]
+    - name: validate_with_checksums
+      description: 完整读取所有 HDF5 文件并校验 SHA256。
+      cwd: .
+      command: python scripts/validate_dataset.py --dataset-root . --verify-checksums
+      required_files: [metadata/file_checksums.sha256, data/1993.h5, data/1999.h5]
+      required_env: [python, h5py, numpy, pyyaml]
+      expected_outputs: []
+      success_criteria: [exit_code == 0]
+  inference: []
+  train: []
+  finetune: []
+  evaluate: []
+  visualize: []
+  deploy: []
+
+expected_outputs:
+  - path: stdout
+    type: text
+    produced_by: commands.preflight.validate_structure
+    contains: CMEMS dataset validation passed.
+  - path: XiHe/data/stats/global_means.npy
+    type: file
+    produced_by: commands.prepare.prepare_for_xihe
+
+diagnostics:
+  - name: missing_hdf5
+    match: "missing file"
+    explanation_zh: 数据集未完整下载或当前工作目录不是 CMEMS 仓库根目录。
+    fix_zh: 执行 modelscope download --dataset OneScience/CMEMS --local_dir ./CMEMS，并在 ./CMEMS 中运行验证命令。
+  - name: schema_mismatch
+    match: "variables attr does not match schema"
+    explanation_zh: HDF5 文件变量顺序或变量名与 schema.yaml 不一致。
+    fix_zh: 重新校验上传文件是否来自同��批 CMEMS 数据，必要时重新生成 schema 和 checksum。
+  - name: checksum_mismatch
+    match: "sha256 mismatch"
+    explanation_zh: 数据文件内容与上传前校验清单不一致。
+    fix_zh: 重新下载或重新上传对应年份文件。
+
+domain_extension:
+  earth:
+    subdomain: ocean
+    source_family: CMEMS
+    grid:
+      lat_size: 2041
+      lon_size: 4320
+      spatial_resolution: [0.0833333333, 0.0833333333]
+    time:
+      years: [1993, 1994, 1995, 1996, 1997, 1998, 1999]
+      time_step_hours: 24
+      samples_per_year_file: 3
+    variables_count: 96

metadata/file_checksums.sha256

@@ -0,0 +1,7 @@
+57c694c0faf46cb5762751fffca473aeba783fb029288c2c1dea62c50a4b16e8  data/1993.h5
+d31d57c292518b799f2dafac6e57663ee5bdb2128c5f7286ae9b4afdc4a51859  data/1994.h5
+f86f6a02ebaa852b7ed88ceafc0dd4d4def09ec53269d1aba71031bd3ac0f7fe  data/1995.h5
+ffe95335363b97d97744b310af22f1fc9b79a77446bf0c8981dd27e77e3b0098  data/1996.h5
+2d9c427a4fe6e9ee621edff3a641c088e506b7c5ee0d9ab0928d98d2aacfb5fc  data/1997.h5
+c25a62f81c720663fddec49a081568e7a5a46e767204e67ab9945e7c121d6e43  data/1998.h5
+a3a8040afb56ad2bee79d19fb8bd6b44d47411c8417ada95b063ef91cfbb08de  data/1999.h5

metadata/schema.yaml

@@ -0,0 +1,127 @@
+dataset: CMEMS
+resource_id: OneScience/CMEMS
+format: hdf5
+file_pattern: data/{year}.h5
+years:
+  train: [1993, 1994, 1995, 1996, 1997]
+  validation: [1998]
+  test: [1999]
+sample_unit: one daily ocean state transition sample per time index
+hdf5:
+  required_datasets:
+    fields:
+      shape: [3, 96, 2041, 4320]
+      dtype: float32
+      attrs:
+        time_step: 24
+        variables_count: 96
+    global_means:
+      shape: [1, 96, 1, 1]
+      dtype: float32
+      attrs:
+        note: "global stats aligned with fields.attrs['variables']"
+    global_stds:
+      shape: [1, 96, 1, 1]
+      dtype: float32
+      attrs:
+        note: "global stats aligned with fields.attrs['variables']"
+variables:
+  - sea_surface_temperature
+  - sea_surface_height_above_geoid
+  - 10m_u_component_of_wind
+  - 10m_v_component_of_wind
+  - eastward_sea_water_velocity_1
+  - eastward_sea_water_velocity_2
+  - eastward_sea_water_velocity_3
+  - eastward_sea_water_velocity_4
+  - eastward_sea_water_velocity_5
+  - eastward_sea_water_velocity_6
+  - eastward_sea_water_velocity_7
+  - eastward_sea_water_velocity_8
+  - eastward_sea_water_velocity_9
+  - eastward_sea_water_velocity_10
+  - eastward_sea_water_velocity_11
+  - eastward_sea_water_velocity_12
+  - eastward_sea_water_velocity_13
+  - eastward_sea_water_velocity_14
+  - eastward_sea_water_velocity_15
+  - eastward_sea_water_velocity_16
+  - eastward_sea_water_velocity_17
+  - eastward_sea_water_velocity_18
+  - eastward_sea_water_velocity_19
+  - eastward_sea_water_velocity_20
+  - eastward_sea_water_velocity_21
+  - eastward_sea_water_velocity_22
+  - eastward_sea_water_velocity_23
+  - northward_sea_water_velocity_1
+  - northward_sea_water_velocity_2
+  - northward_sea_water_velocity_3
+  - northward_sea_water_velocity_4
+  - northward_sea_water_velocity_5
+  - northward_sea_water_velocity_6
+  - northward_sea_water_velocity_7
+  - northward_sea_water_velocity_8
+  - northward_sea_water_velocity_9
+  - northward_sea_water_velocity_10
+  - northward_sea_water_velocity_11
+  - northward_sea_water_velocity_12
+  - northward_sea_water_velocity_13
+  - northward_sea_water_velocity_14
+  - northward_sea_water_velocity_15
+  - northward_sea_water_velocity_16
+  - northward_sea_water_velocity_17
+  - northward_sea_water_velocity_18
+  - northward_sea_water_velocity_19
+  - northward_sea_water_velocity_20
+  - northward_sea_water_velocity_21
+  - northward_sea_water_velocity_22
+  - northward_sea_water_velocity_23
+  - sea_water_salinity_1
+  - sea_water_salinity_2
+  - sea_water_salinity_3
+  - sea_water_salinity_4
+  - sea_water_salinity_5
+  - sea_water_salinity_6
+  - sea_water_salinity_7
+  - sea_water_salinity_8
+  - sea_water_salinity_9
+  - sea_water_salinity_10
+  - sea_water_salinity_11
+  - sea_water_salinity_12
+  - sea_water_salinity_13
+  - sea_water_salinity_14
+  - sea_water_salinity_15
+  - sea_water_salinity_16
+  - sea_water_salinity_17
+  - sea_water_salinity_18
+  - sea_water_salinity_19
+  - sea_water_salinity_20
+  - sea_water_salinity_21
+  - sea_water_salinity_22
+  - sea_water_salinity_23
+  - sea_water_potential_temperature_1
+  - sea_water_potential_temperature_2
+  - sea_water_potential_temperature_3
+  - sea_water_potential_temperature_4
+  - sea_water_potential_temperature_5
+  - sea_water_potential_temperature_6
+  - sea_water_potential_temperature_7
+  - sea_water_potential_temperature_8
+  - sea_water_potential_temperature_9
+  - sea_water_potential_temperature_10
+  - sea_water_potential_temperature_11
+  - sea_water_potential_temperature_12
+  - sea_water_potential_temperature_13
+  - sea_water_potential_temperature_14
+  - sea_water_potential_temperature_15
+  - sea_water_potential_temperature_16
+  - sea_water_potential_temperature_17
+  - sea_water_potential_temperature_18
+  - sea_water_potential_temperature_19
+  - sea_water_potential_temperature_20
+  - sea_water_potential_temperature_21
+  - sea_water_potential_temperature_22
+  - sea_water_potential_temperature_23
+notes:
+  - 每个年份文件包含 3 个 24 小时间隔样本。
+  - global_means 和 global_stds 内置在每个 HDF5 文件中，XiHe 运行前可由模型包脚本提取为 data/stats/*.npy。

onescience_relations.yaml

@@ -0,0 +1,16 @@
+required_datasets: []
+optional_datasets: []
+compatible_models:
+  - id: OneScience/XiHe
+    role: train_data
+    required_for: [preflight, train, inference, evaluate, visualize]
+    resource_ref:
+      platform: modelscope
+      repo_id: OneScience/XiHe
+      repo_type: model
+      url: https://modelscope.cn/models/OneScience/XiHe
+      revision: main
+      readme_path: README.md
+      manifest_path: manifest.yaml
+    expected_local_path: XiHe/data/data
+    adapter: XiHe/scripts/prepare_runtime_data.py

onescience_run_manifest.yaml

@@ -0,0 +1,431 @@
+onescience_manifest_version: "0.1"
+resource_type: dataset
+resource:
+  id: OneScience/CMEMS
+  name: CMEMS
+  domain: earth
+  domain_tags: [earth, ocean, cmems]
+  task: ocean_forecasting
+  task_tags: [ocean_forecast, train_data, eval_data]
+  modalities: [gridded_field]
+  input_formats: [hdf5]
+  output_formats: []
+  summary: CMEMS 是适配 OneScience/XiHe 的 1993-1999 年全球海洋预报 HDF5 数据集。
+
+platform_resource:
+  primary:
+    platform: modelscope
+    repo_id: OneScience/CMEMS
+    repo_type: dataset
+    url: https://modelscope.cn/datasets/OneScience/CMEMS
+    revision: main
+    readme_path: README.md
+    manifest_path: manifest.yaml
+  mirrors: []
+  access:
+    visibility: public
+    license: null
+
+website_integration:
+  enabled: true
+  click_target:
+    platform: modelscope
+    resource_url: https://modelscope.cn/datasets/OneScience/CMEMS
+  llm_handoff:
+    readme_required: true
+    manifest_required: true
+    download_readme_first: true
+    resolve_related_models: true
+    default_run_goal: dataset_validation
+
+runtime:
+  enabled: true
+  onescience_domain: earth
+  min_onescience_version: null
+  supported_execution: [local, local_slurm, remote_slurm, scnet_mcp]
+
+onescience:
+  repo: https://gitee.com/onescience-ai/onescience
+  official_links:
+    gitee:
+      doc: https://gitee.com/onescience-ai/onescience-doc
+      onescience: https://gitee.com/onescience-ai/onescience
+      skills: https://gitee.com/onescience-ai/oneskills
+    github:
+      doc: https://github.com/onescience-ai/OneScience-doc
+      onescience: https://github.com/onescience-ai/OneScience
+      skills: https://github.com/onescience-ai/oneskills
+  install:
+    required_by_default: false
+    command: bash install.sh earth
+  source_paths: []
+  compatibility:
+    examples_path: null
+    status: standard_first
+
+environment:
+  install_mode: onescience_domain
+  python: "3.11"
+  hardware:
+    cpu: supported
+    gpu: optional
+    dcu: optional
+  extra_dependencies: [h5py, numpy, pyyaml]
+
+runtime_package:
+  kind: dataset_package
+  package_root: .
+  standard_layout:
+    workdir: .
+    config_dir: metadata
+    checkpoint_dir: null
+    data_dir: data
+    output_dir: null
+  apply_policy:
+    mode: direct_use
+    target: session_workdir
+    overwrite: true
+    protect_installed_onescience: true
+  entry_files:
+    - metadata/schema.yaml
+    - metadata/file_checksums.sha256
+    - scripts/validate_dataset.py
+  entrypoints:
+    preflight: scripts/validate_dataset.py
+    inference: null
+    train: null
+    finetune: null
+    evaluate: null
+    visualize: null
+    deploy: null
+
+files:
+  model_files: []
+  dataset_files:
+    - id: cmems_1993_h5
+      path: data/1993.h5
+      role: train_data
+      description_zh: 1993 年 CMEMS HDF5 年份文件，包含 fields、global_means 和 global_stds。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source:
+        platform: modelscope
+        repo_id: OneScience/CMEMS
+        repo_type: dataset
+        path: data/1993.h5
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset
+      mirrors: []
+      local_path: CMEMS/data/1993.h5
+      size: 10157335296
+      checksum: sha256:57c694c0faf46cb5762751fffca473aeba783fb029288c2c1dea62c50a4b16e8
+      large_file: true
+    - id: cmems_1994_h5
+      path: data/1994.h5
+      role: train_data
+      description_zh: 1994 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1994.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1994.h5
+      size: 10157335296
+      checksum: sha256:d31d57c292518b799f2dafac6e57663ee5bdb2128c5f7286ae9b4afdc4a51859
+      large_file: true
+    - id: cmems_1995_h5
+      path: data/1995.h5
+      role: train_data
+      description_zh: 1995 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1995.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1995.h5
+      size: 10157335296
+      checksum: sha256:f86f6a02ebaa852b7ed88ceafc0dd4d4def09ec53269d1aba71031bd3ac0f7fe
+      large_file: true
+    - id: cmems_1996_h5
+      path: data/1996.h5
+      role: train_data
+      description_zh: 1996 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1996.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1996.h5
+      size: 10157335296
+      checksum: sha256:ffe95335363b97d97744b310af22f1fc9b79a77446bf0c8981dd27e77e3b0098
+      large_file: true
+    - id: cmems_1997_h5
+      path: data/1997.h5
+      role: train_data
+      description_zh: 1997 年 CMEMS HDF5 年份文件。
+      required: true
+      required_for: [preflight, train]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1997.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1997.h5
+      size: 10157335296
+      checksum: sha256:2d9c427a4fe6e9ee621edff3a641c088e506b7c5ee0d9ab0928d98d2aacfb5fc
+      large_file: true
+    - id: cmems_1998_h5
+      path: data/1998.h5
+      role: eval_data
+      description_zh: 1998 年 CMEMS HDF5 年份文件，XiHe 标准配置用于验证。
+      required: true
+      required_for: [preflight, train, evaluate]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1998.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1998.h5
+      size: 10157335296
+      checksum: sha256:c25a62f81c720663fddec49a081568e7a5a46e767204e67ab9945e7c121d6e43
+      large_file: true
+    - id: cmems_1999_h5
+      path: data/1999.h5
+      role: inference_input
+      description_zh: 1999 年 CMEMS HDF5 年份文件，XiHe 标准配置用于测试、推理和评测。
+      required: true
+      required_for: [preflight, inference, evaluate]
+      format: hdf5
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: data/1999.h5, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/data/1999.h5
+      size: 10157335296
+      checksum: sha256:a3a8040afb56ad2bee79d19fb8bd6b44d47411c8417ada95b063ef91cfbb08de
+      large_file: true
+    - id: cmems_schema
+      path: metadata/schema.yaml
+      role: schema
+      description_zh: HDF5 结构、shape、dtype、attrs、变量列表和划分说明。
+      required: true
+      required_for: [preflight]
+      format: yaml
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: metadata/schema.yaml, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/metadata/schema.yaml
+      size: null
+      checksum: null
+      large_file: false
+    - id: cmems_checksums
+      path: metadata/file_checksums.sha256
+      role: checksum
+      description_zh: 数据文件 SHA256 校验清单。
+      required: true
+      required_for: [preflight]
+      format: text
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: metadata/file_checksums.sha256, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/metadata/file_checksums.sha256
+      size: null
+      checksum: null
+      large_file: false
+  config_files:
+    - id: validate_dataset_script
+      path: scripts/validate_dataset.py
+      role: preflight_script
+      description_zh: 数据集读取、schema、attrs、shape、dtype 和可选 SHA256 校验脚本。
+      required: true
+      required_for: [preflight]
+      format: python
+      source: {platform: modelscope, repo_id: OneScience/CMEMS, repo_type: dataset, path: scripts/validate_dataset.py, revision: main, url: null, download_method: command_ref, command_ref: commands.download.download_dataset}
+      mirrors: []
+      local_path: CMEMS/scripts/validate_dataset.py
+      size: null
+      checksum: null
+      large_file: false
+  sample_files: []
+
+dataset:
+  format: [hdf5]
+  sample_unit: one daily ocean state transition sample per time index
+  schema:
+    path: metadata/schema.yaml
+  checksums:
+    path: metadata/file_checksums.sha256
+    algorithm: sha256
+  splits:
+    train: [1993, 1994, 1995, 1996, 1997]
+    validation: [1998]
+    test: [1999]
+  structure:
+    hdf5_datasets: [fields, global_means, global_stds]
+    fields_shape: [3, 96, 2041, 4320]
+    stats_shape: [1, 96, 1, 1]
+    dtype: float32
+    time_step_hours: 24
+
+relations:
+  required_datasets: []
+  optional_datasets: []
+  compatible_models:
+    - id: OneScience/XiHe
+      role: train_data
+      required_for: [preflight, train, inference, evaluate, visualize]
+      resource_ref:
+        platform: modelscope
+        repo_id: OneScience/XiHe
+        repo_type: model
+        url: https://modelscope.cn/models/OneScience/XiHe
+        revision: main
+        readme_path: README.md
+        manifest_path: manifest.yaml
+      expected_local_path: XiHe/data/data
+      adapter: XiHe/scripts/prepare_runtime_data.py
+
+run_matrix:
+  scenarios:
+    - name: dataset_validation
+      capability: preflight
+      default: true
+      description_zh: 验证 CMEMS 数据集目录结构、HDF5 schema、shape、dtype、attrs 和统计量。
+      required_datasets:
+        - id: OneScience/CMEMS
+          role: self
+          local_path: .
+      required_model_files: []
+      required_data_files: [data/1993.h5, data/1994.h5, data/1995.h5, data/1996.h5, data/1997.h5, data/1998.h5, data/1999.h5]
+      preconditions:
+        - cwd 为下载后的 CMEMS 数据集仓库根目录。
+      command_refs:
+        - commands.preflight.validate_structure
+      outputs: []
+    - name: dataset_checksum_validation
+      capability: preflight
+      description_zh: 在结构验证基础上读取全部 7 个大文件并校验 SHA256，耗时较长。
+      required_datasets:
+        - id: OneScience/CMEMS
+          role: self
+          local_path: .
+      required_model_files: []
+      required_data_files: [data/*.h5, metadata/file_checksums.sha256]
+      preconditions:
+        - cwd 为下载后的 CMEMS 数据集仓库根目录。
+      command_refs:
+        - commands.preflight.validate_with_checksums
+      outputs: []
+    - name: prepare_for_xihe
+      capability: prepare
+      description_zh: 与 OneScience/XiHe 模型配合时，由模型包脚本将本数据集整理到 XiHe/data/data。
+      required_datasets:
+        - id: OneScience/CMEMS
+          role: train_data
+          local_path: CMEMS
+      required_model_files: [XiHe/scripts/prepare_runtime_data.py, XiHe/conf/config.yaml]
+      required_data_files: [CMEMS/data/*.h5]
+      preconditions:
+        - OneScience/XiHe 下载到 ./XiHe。
+        - OneScience/CMEMS 下载到 ./CMEMS。
+      command_refs:
+        - commands.prepare.prepare_for_xihe
+      outputs:
+        - XiHe/data/data/*.h5
+        - XiHe/data/stats/global_means.npy
+        - XiHe/data/land_mask.npy
+
+capabilities:
+  inference: false
+  train: false
+  finetune: false
+  evaluate: false
+  visualize: false
+  deploy: false
+
+commands:
+  download:
+    - name: download_dataset
+      description: 下载 CMEMS 数据集标准仓库。
+      target: dataset
+      repo_id: OneScience/CMEMS
+      source: .
+      local_path: ./CMEMS
+      required: true
+      required_for: [preflight, train, inference, evaluate]
+      command: modelscope download --dataset OneScience/CMEMS --local_dir ./CMEMS
+    - name: download_compatible_model
+      description: 下载适配模型 XiHe。
+      target: model
+      repo_id: OneScience/XiHe
+      source: .
+      local_path: ./XiHe
+      required: false
+      required_for: [train, inference, evaluate]
+      command: modelscope download --model OneScience/XiHe --local_dir ./XiHe
+  prepare:
+    - name: prepare_for_xihe
+      description: 调用 XiHe 模型包脚本，把 CMEMS 数据组织成 XiHe 运行布局。
+      cwd: ./XiHe
+      command: python scripts/prepare_runtime_data.py --dataset-root ../CMEMS --runtime-data-dir ./data
+      required_files: [../CMEMS/data/1993.h5, scripts/prepare_runtime_data.py]
+      required_env: [python, h5py, numpy]
+      expected_outputs:
+        - path: data/data/1993.h5
+          type: file
+      success_criteria: [exit_code == 0, output_path_exists]
+  preflight:
+    - name: validate_structure
+      description: 快速读取每个 HDF5 文件的结构、变量、shape、dtype 和统计量。
+      cwd: .
+      command: python scripts/validate_dataset.py --dataset-root .
+      required_files: [metadata/schema.yaml, metadata/file_checksums.sha256, data/1993.h5, data/1999.h5]
+      required_env: [python, h5py, numpy, pyyaml]
+      expected_outputs: []
+      success_criteria: [exit_code == 0]
+    - name: validate_with_checksums
+      description: 完整读取所有 HDF5 文件并校验 SHA256。
+      cwd: .
+      command: python scripts/validate_dataset.py --dataset-root . --verify-checksums
+      required_files: [metadata/file_checksums.sha256, data/1993.h5, data/1999.h5]
+      required_env: [python, h5py, numpy, pyyaml]
+      expected_outputs: []
+      success_criteria: [exit_code == 0]
+  inference: []
+  train: []
+  finetune: []
+  evaluate: []
+  visualize: []
+  deploy: []
+
+expected_outputs:
+  - path: stdout
+    type: text
+    produced_by: commands.preflight.validate_structure
+    contains: CMEMS dataset validation passed.
+  - path: XiHe/data/stats/global_means.npy
+    type: file
+    produced_by: commands.prepare.prepare_for_xihe
+
+diagnostics:
+  - name: missing_hdf5
+    match: "missing file"
+    explanation_zh: 数据集未完整下载或当前工作目录不是 CMEMS 仓库根目录。
+    fix_zh: 执行 modelscope download --dataset OneScience/CMEMS --local_dir ./CMEMS，并在 ./CMEMS 中运行验证命令。
+  - name: schema_mismatch
+    match: "variables attr does not match schema"
+    explanation_zh: HDF5 文件变量顺序或变量名与 schema.yaml 不一致。
+    fix_zh: 重新校验上传文件是否来自同��批 CMEMS 数据，必要时重新生成 schema 和 checksum。
+  - name: checksum_mismatch
+    match: "sha256 mismatch"
+    explanation_zh: 数据文件内容与上传前校验清单不一致。
+    fix_zh: 重新下载或重新上传对应年份文件。
+
+domain_extension:
+  earth:
+    subdomain: ocean
+    source_family: CMEMS
+    grid:
+      lat_size: 2041
+      lon_size: 4320
+      spatial_resolution: [0.0833333333, 0.0833333333]
+    time:
+      years: [1993, 1994, 1995, 1996, 1997, 1998, 1999]
+      time_step_hours: 24
+      samples_per_year_file: 3
+    variables_count: 96

scripts/validate_dataset.py

@@ -0,0 +1,95 @@
+#!/usr/bin/env python3
+"""Validate the standardized OneScience/CMEMS dataset package."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+from pathlib import Path
+
+import h5py
+import numpy as np
+import yaml
+
+
+YEARS = [1993, 1994, 1995, 1996, 1997, 1998, 1999]
+EXPECTED_FIELD_SHAPE = (3, 96, 2041, 4320)
+EXPECTED_STATS_SHAPE = (1, 96, 1, 1)
+
+
+def sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as handle:
+        for chunk in iter(lambda: handle.read(1024 * 1024 * 16), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def load_schema(path: Path) -> dict:
+    with path.open("r", encoding="utf-8") as handle:
+        return yaml.safe_load(handle)
+
+
+def load_checksums(path: Path) -> dict[str, str]:
+    checksums = {}
+    with path.open("r", encoding="utf-8") as handle:
+        for line in handle:
+            if not line.strip():
+                continue
+            digest, relpath = line.strip().split(maxsplit=1)
+            checksums[relpath] = digest
+    return checksums
+
+
+def normalize_attr_strings(values) -> list[str]:
+    return [value.decode() if isinstance(value, bytes) else str(value) for value in values]
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Check CMEMS HDF5 files, schema, attrs and optional checksums.")
+    parser.add_argument("--dataset-root", default=".")
+    parser.add_argument("--verify-checksums", action="store_true")
+    args = parser.parse_args()
+
+    root = Path(args.dataset_root).resolve()
+    schema = load_schema(root / "metadata" / "schema.yaml")
+    expected_variables = schema["variables"]
+    checksums = load_checksums(root / "metadata" / "file_checksums.sha256")
+
+    for year in YEARS:
+        relpath = f"data/{year}.h5"
+        path = root / relpath
+        if not path.exists():
+            raise FileNotFoundError(f"missing file: {path}")
+        if path.stat().st_size != 10157335296:
+            raise AssertionError(f"{path} size mismatch: {path.stat().st_size}")
+        with h5py.File(path, "r") as handle:
+            for key in ("fields", "global_means", "global_stds"):
+                if key not in handle:
+                    raise KeyError(f"{path} missing dataset {key}")
+            fields = handle["fields"]
+            if tuple(fields.shape) != EXPECTED_FIELD_SHAPE:
+                raise AssertionError(f"{path} fields shape {fields.shape}")
+            if fields.dtype != np.dtype("float32"):
+                raise AssertionError(f"{path} fields dtype {fields.dtype}")
+            if int(fields.attrs["time_step"]) != 24:
+                raise AssertionError(f"{path} time_step attr mismatch")
+            variables = normalize_attr_strings(fields.attrs["variables"])
+            if variables != expected_variables:
+                raise AssertionError(f"{path} variables attr does not match schema")
+            for stat_key in ("global_means", "global_stds"):
+                stat = handle[stat_key]
+                if tuple(stat.shape) != EXPECTED_STATS_SHAPE:
+                    raise AssertionError(f"{path} {stat_key} shape {stat.shape}")
+                if stat.dtype != np.dtype("float32"):
+                    raise AssertionError(f"{path} {stat_key} dtype {stat.dtype}")
+        if args.verify_checksums:
+            actual = sha256(path)
+            if actual != checksums[relpath]:
+                raise AssertionError(f"{path} sha256 mismatch: {actual} != {checksums[relpath]}")
+
+    print("CMEMS dataset validation passed.")
+
+
+if __name__ == "__main__":
+    main()