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GCRI · 登记册

Registry 的数据工程

Data engineering, interoperability and stewardship are the working base of a registry: the schemas that define a record, the pipelines that ingest and transform it, the identifiers and crosswalks that link it to other 系统, and the stewardship that keeps it accurate over time. Every provenance, correction and rights commitment on this platform depends on them.

提出咨询 Back to STEM foundation of Registry
01登记

Data engineering at Registry on the record.

方法记录STEM 方法
  1. 方法数据工程、互操作性与数据管护
  3. 应用于登记册
  6. 规范页面STEM 公共资源
02申请

What data engineering, interoperability and stewardship does here.

Data engineering, interoperability and stewardship cover the pipelines, standards and governance that make data usable and trustworthy. They determine whether information from different sectors can be combined for joint 风险评估. In governance and institutions and research and evidence, sound data engineering allows hazard, exposure and financial data to be linked consistently. It supports transparent and repeatable analysis of interconnected risk. The canonical description is on STEM Commons.

Schema-validated ingestion

Incoming records are validated against a versioned schema before they enter the registry. Records that fail are quarantined with the reasons, not partially loaded, so a malformed field never reaches a public view.

Persistent identifier reconciliation

Free-text names of people, organisations and works are matched to ORCID, ROR and DOI records. The match method and confidence are stored with each link, and uncertain matches are routed to a steward.

Lineage capture in pipelines

Each transformation records its inputs, code version, responsible agent and time as PROV statements, so any published field can be traced back to the source rows that produced it.

03方法与证据

How Data engineering at Registry is modelled, measured and tested.

模型、其假设、数据和不确定性，以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意，不是研究发现。

数据集与来源追溯

The data classes behind Data engineering at Registry and what is recorded about each before it is used.

数据类别已记录溯源已说明分辨率许可已核查
卫星影像，光学与雷达传感器、处理级别、获取日期像元大小和重访周期每景
再分析与气候模式输出模型、实验、成员、版本格网与时间步长每次发布
原位传感器和测量站测站、仪器、校准记录点位与采样率每个网络
人口与资产暴露方法、版本年份、输入来源单元大小和单位每次发布
边界与参考地理制作者、版本、日期比例尺每个版本
沿袭
从来源到图表的 W3C PROV 记录
原则
FAIR：可查找、可访问、可互操作、可复用
缺口
显示为缺失，绝不悄然填充
数据类别及为每类记录的来源追溯字段；数据集只有在其许可允许该用途之后才按名称列出。
FAIR 指导原则 · GO FAIR 和 FORCE11W3C PROV · 万维网联盟关于一致处理不确定性的指南 · IPCCCEOS 分析就绪数据 · 地球观测卫星委员会
04数据

该方法使用的输入。

Datasets and records used by data engineering, interoperability and stewardship on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.

数据角色标签
Crossref and DataCite metadataReference metadata for registered works and outputs已报告
ORCID recordsContributor identity and linked works已声明
ROR registryOrganisation identifiers, name variants and relationships已报告
Partner programme recordsIngested programme and participation records已报告
Pipeline run logsLineage and transformation history观测
05流程

流程如何运行。

Process explorer · Process

Data engineering at Registry: Build, sign and accept

10 steps4 个阶段2 道关口

流程

Data engineering at Registry: Build, sign and accept

获准的任务成为周期项目；构建版本经过固定、验证和签名，全球风险论坛（Global Risks Forum，GRF）记录的是用于演练的验收，而不是部署许可。

  1. 01 请求与来源

    1. 01已准入的任务成为周期项目记录 · 宇宙 到 Foundry已准入的任务成为附决策案例的周期项目。
    2. 02对数据来源与资源进行资格审查步骤 · Global Centre for Risk and Innovation (GCRI)GCRI 对数据来源与资源提供进行资格审查，并构建情景模型。提供不等于分配。

  2. 02 构建与验证

    1. 03来源快照记录 · NXS-FAC （蓝图、构建与签署）快照固定了提交、依赖项与生成器版本。
    2. 04构建合同记录 · NXS-FAC（蓝图、构建与签署）构建合同声明制品类型、环境与可复现性范围。
    3. 05整合与构建模型 · GCRIGCRI 整合软件与数据、签署构建版本，并测试安全性与互操作性。
    4. 06验证套件关口 · NXS-FAC（蓝图、构建与签署）必需检查与建议性检查相互分开。可复现性要求固定输入、声明非确定性并进行独立重建。

  3. 03 签署与准入

    1. 07签署确切的制品步骤 · NXS-FAC（蓝图、构建与签署）NXS-FAC 通过限定范围的签名者身份进行构建、证明并请求签名。它不持有任何密钥材料。
    2. 08资料包准入步骤 · NXS-NXQ （软件、模型与能力生命周期）NXS-NXQ 接收已签名的软件包，并保存将任务、数据类别、评估套件与有效期绑定在一起的准入证据。

  4. 04 接受

    1. 09核心构建报告记录 · GCRI核心构建报告是通过或不通过的记录。Universe 组装核心，并持有演练的决定权。
    2. 10G3 · 构建被接受用于演练关口 · Global Risks ForumGRF 记录构建版本是否被接受用于演练。已签名的构建版本或候选发布版本并不意味着获准部署到生产环境。

计划年度 · NXS-FAC · UniverseDesigned programme process, not a record of operation. No cycle has run and every programme is at service level R0. A gate is a programme decision, never a public-authority approval, certification or deployment authorisation. The record order follows the Builds and Releases room lists of NXS-FAC.

06验证

结果如何核查。

Pipelines are tested with automated quality checks, schema validation and lineage audits. Reconciliation against source 系统 confirms completeness.

核查如何开展
Schema validationEvery record is validated against the published schema version; failures are counted and reported, never dropped silently
Reconciliation against sourceRecord counts and checksums are compared with the source system after every load
Lineage auditA sample of published fields is traced back through the provenance graph to its source rows
Round-trip testRecords are exported, re-imported and compared field by field to expose lossy mappings

Incompatible standards, missing metadata and restrictive licences block integration. Legacy systems and undocumented transformations introduce silent errors.

07关联

依赖该方法的主题。

08管理责任

由谁维护该方法。

数据与算力 stewards data engineering, interoperability and stewardship for the Consortium and reviews how it is applied across platforms.

Canonical page: Data engineering, interoperability and stewardship

09已关联

本页在整个联合体中通向何处。

10问题

问题与解答。

What are the limits of data engineering, interoperability and stewardship in this field?
Incompatible standards, missing metadata and restrictive licences block integration. Legacy systems and undocumented transformations introduce silent errors.
结果如何核查？
Pipelines are tested with automated quality checks, schema validation and lineage audits. Reconciliation against source systems confirms completeness.
本页面上的数值是真实的吗？
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
该方法还应用于何处？
维持社会运转的 规范方法页面 列出应用该方法的每个平台。
报告贡献

从本页贡献证据。

报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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