International Data Spaces Information Model
国际数据空间信息模型

Scope  范围

 

The Information Model primarily aims at describing, publishing and detecting data products (Data Assets) and reusable data processing software (Data Apps) in the International Data Space. Data Assets and Data Apps are the core resources of the International Data Space, and are hereinafter referred to as resources . By means of a structured semantic annotation it is ensured only relevant resources are provided (i.e., resources appropriate to meet the requirements of the Data Consumer). Once the resources are identified, they can be exchanged and consumed via semantically defined service interfaces and protocol bindings in an automated way. Apart from those core commodities, the Information Model describes essential properties of International Data Space entities, its participants, its infrastructure components, and its processes.
信息模型主要旨在描述、发布和检测国际数据空间中的数据产品（数据资产）和可重用数据处理软件（数据应用）。数据资产和数据应用是国际数据空间的核心资源，以下统称为资源。通过结构化语义标注，确保只提供相关资源（即满足数据消费者需求的资源）。一旦识别出资源，它们可以通过语义定义的服务接口和协议绑定以自动化的方式进行交换和消费。除了这些核心商品外，信息模型还描述了国际数据空间实体、参与者、基础设施组件和流程的基本属性。

 

The Information Model is a generic model, with no commitment to any particular domain. Domain modeling is delegated to shared vocabularies and data schemata, as provided e.g. by domain-specific communities of the International Data Space. The Information Model does not provide a meta-model for defining custom structured datatypes comparable to the OData or OPC-UA standards. Considerations beyond the scope of modeling digital assets and their interchange are considered out-of-scope. The Information Model does not deal with the side effects of data exchange (on Data Consumer's side), for example in scenarios where data is used for real-time machine control. RPC (remote procedure call) semantics of data messages is also not covered by the Information Model.
信息模型是一个通用的模型，不对任何特定领域做出承诺。领域建模委托给共享词汇和数据模式，例如由国际数据空间特定领域的社区提供。信息模型不提供用于定义自定义结构化数据类型的元模型，这些数据类型与 OData 或 OPC-UA 标准相当。超出建模数字资产及其交换范围的因素被视为超出范围。信息模型也不处理数据交换的副作用（在数据消费者方面），例如在数据用于实时机器控制等场景中。数据消息的 RPC（远程过程调用）语义也不在信息模型范围内。

 

Figure 3.13 Representations of the Information Model
图 3.13 信息模型的表示

3.1. Representation  3.1. 表示

 

The Information Model has been specified at three levels of formalization. Each level corresponds to a digital representation, ranging from a high-level, conceptual document up to the level of operational code, as depicted in Figure 3.13.
信息模型已在三个形式化级别中进行了指定。每个级别对应一个数字表示，从高级概念文档到操作代码级别，如图 3.13 所示。

The Declarative Representation (IDS Vocabulary) is the only normative specification of the Information Model. A set of auxiliary resources, among others, guidance documents, reference examples, validation, and editing tools is intended to support a competent, appropriate, and consistent usage of the IDS Vocabulary.
声明性表示（IDS 词汇表）是信息模型的唯一规范性规范。一套辅助资源，包括指导文档、参考示例、验证和编辑工具等，旨在支持对 IDS 词汇表的熟练、适当和一致的使用。

 

Conceptual Representation
概念表示

The Conceptual Representation of the Information Model (CRIM) provides an analysis and a high-level overview of the main, largely invariant concepts of the Information Model, with no commitment to a particular technology or domain. It mainly targets the general public as well as management boards of organizations by means of a textual document and an understandable visual notation. The descriptions at this level are generic, providing basic information, allowing comparative analysis, and promoting a shared understanding of the concepts. References to the Declarative Representation and the Programmatic Representation are provided, encouraging the reader to take a look into these representations as well in order to learn more details.
信息模型的概念表示（CRIM）提供了对信息模型主要、很大程度上不变的概念的分析和高级概述，不对特定技术或领域做出承诺。它主要通过文本文档和易于理解的视觉符号针对一般公众以及组织的董事会。在此级别上的描述是通用的，提供基本信息，允许比较分析，并促进对概念的共同理解。提供了对声明性表示和程序性表示的引用，鼓励读者查看这些表示以了解更多细节。

 

Visual Notation  视觉符号

Alongside with figurative, explanatory images, a simplified version of UML class diagrams is used throughout the document, as described in Table 2.
文档中使用了简化的 UML 类图，如图 2 所示，与图解性、解释性图像并列。

 

 

 

Declarative Representation
声明表示

The Declarative Representation of the Information Model (DRIM) defines the normative Information Model of the International Data Space. It has been developed along the analysis, findings and requirements of the Conceptual Representation. Based on a stack of W3C technology standards ( RDF , RDFS, OWL , etc. ) and standard modeling vocabularies ( DCAT , ODRL , etc.), it provides a formal, machine-interpretable specification of concepts envisaged by the Conceptual Representation. Furthermore, it details out and formally defines entities of the International Data Space in order to be able to share, search for, and reason upon their structured meta-data descriptions. As such, it comprises a complete referential model allowing to derive a number of Programmatic Representations. The ontology is typically used and instantiated by Knowledge Engineers, and Ontology Experts. The Declarative Representation defines a reusable, domain-agnostic “core model”. It relies on third party standard and custom vocabularies in order to express domain-specific facts. According to the common practice, existing domain vocabularies and standards are reused where possible fostering acceptance, and interoperability.
信息模型声明表示（DRIM）定义了国际数据空间的规范性信息模型。它是根据概念表示的分析、发现和要求开发的。基于 W3C 技术标准堆栈（RDF、RDFS、OWL 等）和标准建模词汇表（DCAT、ODRL 等），它为概念表示所设想的概念提供了正式、机器可解释的规范。此外，它详细说明了并正式定义了国际数据空间的实体，以便能够共享、搜索和对其结构化元数据描述进行推理。因此，它包含了一个完整的参考模型，允许推导出多个程序表示。本体通常由知识工程师和本体专家使用和实例化。声明表示定义了一个可重用、领域无关的“核心模型”。它依赖于第三方标准和自定义词汇表来表达领域特定事实。 根据惯例，尽可能重用现有领域词汇表和标准，以促进接受和互操作性。

 

Programmatic Representation
程序表示

The Programmatic Representation of the Information Model (PRIM) targets Software Providers (developers) by supporting a seamless integration of the Information Model with a development infrastructure they are familiar with. This representation comprises a programming language data model (e.g., Java, Python, C++ classes) shipped as a set of documented software libraries (e.g., JAR files). The Programmatic Representation provides best-effort mapping of the Declarative Model onto native structures of a target programming language. This approach supports type-safe development, well-established unit testing, and quality assurance processes. It allows developers to easily create instances of the Information Model that are compliant with the Declarative Representation, relieving them from intricacies of the RDF graph model and ontology processing.
信息模型程序表示（PRIM）针对软件提供商（开发者），通过支持信息模型与开发者熟悉的开发基础设施的无缝集成。这种表示包括一组文档化的软件库（例如 JAR 文件）中的编程语言数据模型（例如 Java、Python、C++类）。程序表示提供了对声明性模型到目标编程语言原生结构的最佳努力映射。这种方法支持类型安全的开发、成熟的单元测试和质量保证流程。它允许开发者轻松创建符合声明性表示的信息模型实例，从而减轻了他们处理 RDF 图模型和本体处理的复杂性。

3.2. Facets  3.2. 级别

 

Each of the three representations outlined above expresses the complete Information Model in a particular way. For the purpose of this document, the overall view was divided into logical groups of concepts (hereinafter called facets), addressing different static and dynamic aspects of the International Data Space. Most of the facets were named after the key concept they contain. Unqualified citations refer to the concept, unless explicitly addressing the facet. Facets do not necessarily correspond to a physical organization of the model (e.g., modules or namespaces), but rather identify the core assets and the different modeling concerns:
上述三种表示法分别以特定方式表达了完整的信息模型。为了本文件的目的，整体视图被划分为概念（以下简称方面）的逻辑组，涉及国际数据空间的各个方面静态和动态方面。大多数方面都是以包含的关键概念命名的。除非明确提及方面，否则未加限定的引用指的是该概念。方面不一定对应于模型的物理组织（例如模块或命名空间），而是识别核心资产和不同的建模关注点：

• Resource: Concepts related to the description, provision, commoditization, and usage of resources, i.e., Data Assets and Data Apps, exchanged as digital commodities by participants of the International Data Space.
资源：与资源的描述、提供、商品化和使用相关的概念，即数据资产和数据应用，由国际数据空间参与者作为数字商品进行交换。

• Data: Concepts particular to Data Assets, beyond the scope of general resources
数据：超出一般资源的范围，特定于数据资产的概念

• Application: Concepts particular to Data Apps, beyond the scope of general resources, that are installed within the infrastructure in order to communicate or process data on behalf of participants of the International Data Space.
• 应用：特定于数据应用的概念，超出一般资源范围，安装在基础设施中，以便代表国际数据空间参与者进行数据通信或处理。

The following Information Model facets deal with the description of entities constituting the International Data Space:
以下信息模型方面涉及描述构成国际数据空间实体的内容：

• Infrastructure: Concepts related to description and verification of certified components used by participants in the International Data Space in order to perform business interactions, or be managed as part of maintenance processes.
• 基础设施：与描述和验证国际数据空间参与者使用的认证组件相关，这些组件用于执行业务交互或作为维护流程的一部分进行管理。
• Participant: Concepts related to the description, and verification of legal or natural persons that interact using the infrastructure of the International Data Space, assuming certain roles and adhering to formal regulations.
• 参与者：与描述和验证使用国际数据空间基础设施互动的法律或自然人的概念相关，假定某些角色并遵守正式规定。
• Regulation: Concepts related to the description, formal definition, and enforcement of contracts and usage policies governing the interactions of participants and their use of resources.
• 规范：与描述、正式定义和执行合同以及规范参与者互动和资源使用的使用政策相关的概念。

The remaining facets deal with the description of dynamic scenarios, i.e. the value generating interactions and the maintenance of internal resources and the IDS infrastructure:
剩余的方面涉及动态场景的描述，即价值生成交互以及内部资源和 IDS 基础设施的维护：

• Interaction: Concepts related to description, instantiation, and evolution of business interactions between participants of the International Data Space, leading to the exchange and consumption of resources in compliance with defined regulations.
• 交互：与国际数据空间参与者之间业务交互的描述、实例化和演变相关概念，导致在符合定义的规范下交换和消费资源。
• Maintenance: Concepts related to the description, execution, monitoring, and clearing of the operational processes within the infrastructure of the International Data Space and the life-cycle management of resources.
• 维护：与国际数据空间基础设施中操作流程的描述、执行、监控和清除以及资源生命周期管理相关的概念。

Figure 3.14 illustrates the facets, depicted as high-level concepts, involved in various relationships. Being a mere abstraction, the resource facet was omitted from the figure.
图 3.14 展示了涉及各种关系的方面，这些方面被表示为高级概念。作为一个抽象，资源方面在图中被省略了。

 

Figure 3.14: Facets of the Information Model
图 3.14：信息模型方面

A set of illustrative examples will be introduced per facet in order to motivate and demonstrate its application. These examples are reused as a reference across the representations of the Information Model and expressed as ontology instances (DRIM) or Java objects (PRIM).
每个方面将引入一组示例，以激发和展示其应用。这些示例在信息模型的各种表示中作为参考被重复使用，并以本体实例（DRIM）或 Java 对象（PRIM）的形式表达。

 

Facet 1: Resource  方面 1：资源

The resource concept is the root of a simple taxonomy of International Data Space assets, comprising the Data Asset and Data App concepts (see Figure 3.15). A resource, as defined here, is an identifiable, valuable, digital (non-physical) commodity traded and exchanged among participants by means of the infrastructure of the International Data Space. Examples of Data Assets are, among others, textual documents, time series of sensor values, communication messages, archives of image files, or media streams. Data Assets are subject to forwarding, processing, or consumption, with a particular demand for the modeling of related aspects (i.e., context and provenance, structure and usage control). On the contrary, the usage of Data Apps is rather straightforward and largely determined by their functionality. The Data App concept therefore emphasizes a formal description of the function, deployment prerequisites, and maintenance life-cycle (updates).
资源概念是国际数据空间资产简单分类法的根，包括数据资产和数据应用概念（见图 3.15）。在这里定义的资源是一种可识别的、有价值的、数字的（非物理）商品，通过国际数据空间的基础设施在参与者之间进行交易和交换。数据资产的一些例子包括文本文件、传感器值的时间序列、通信消息、图像文件存档或媒体流。数据资产需要转发、处理或消费，对相关方面的建模有特别需求（即上下文和来源、结构和使用控制）。相反，数据应用的使用相当直接，主要取决于其功能。因此，数据应用概念强调对功能、部署前提条件和维护生命周期（更新）的正式描述。

 

Figure 3 .15: Taxonomy of the resource concept
图 3.15：资源概念分类法

 

Despite these differences, both resource types, the Data Asset and Data App, may uniformly be modeled in their capacity as a shared, digital commodity. As depicted in Figure 3.16, a stratified approach was chosen in order to disaggregate the spectrum of concerns related to their interchange. It resulted in the definition of dedicated views looking at the Content , Communication, and Commodization of resources (here termed as "3C Principle").
尽管存在这些差异，数据资产和数据应用这两种资源类型在作为共享的数字商品的能力上可以统一建模。如图 3.16 所示，为了分解与它们交换相关的各种关注点，选择了分层的方法。这导致了定义了专门的视图，从内容、通信和商品化（以下简称“3C 原则”）的角度来观察资源。

 

Figure 3.16: Views of the resource (3C principle)
图 3.16：资源视图（3C 原则）

The Content V iew describes the inherent substance of a resource. The Communication V iew defines the means to communicate that content in terms of service operations. Legal, contractual, and commercial aspects complementing the resource concept are described by the Commodization V iew. Each view introduces a particular, new perspective on the resource. In order to cope with its complexity, a view may be refined into complementary layers, each one providing level of detail that build upon another, as illustrated in Figure 3.17.
内容视图描述了资源的固有实质。通信视图定义了以服务操作为手段来传达该内容的方式。法律、合同和商业方面补充资源概念的描述由商品化视图完成。每个视图都为资源引入了特定的、新的视角。为了应对其复杂性，一个视图可以被细化成互补的层，每一层都提供比另一层更详细的细节，如图 3.17 所示。

Figure 3.17: Relation of Views and Layers
图 3.17：视图和层的关系

 

Content View  内容视图

The Content V iew considers the resource per se, regardless of its distribution, at three distinct Layers. The kind layer addresses the abstract content structure, e.g. "image", "table", "data record", "application", or collection of above, independently of a physical representation. The Representation Layer concretizes a related content kind by introducing further dimensions and constraints unique to its particular serialization, e.g. JPEG image, Excel sheet, SenML XML document or Debian software package. Both layers represent prototypical "blueprints" of content, i.e., a set of virtual instances that may comply with those models. The Artifact layer concentrates on individuals (deliverable artifacts), and such it allows to express aspects that are specific to a concrete resource instance, e.g., a particular document, image or application build.
内容视图考虑资源本身，无论其分布如何，在三个不同的层次上进行。种类层处理抽象的内容结构，例如“图像”、“表格”、“数据记录”、“应用程序”或上述集合，独立于物理表示。表示层通过引入进一步维度和约束，具体化相关的内容种类，例如 JPEG 图像、Excel 表格、SenML XML 文档或 Debian 软件包。这两个层次代表内容的原型“蓝图”，即一组可能符合这些模型的虚拟实例。工件层专注于个体（可交付的工件），因此它允许表达特定于具体资源实例的方面，例如特定文档、图像或应用程序构建。

 

Figure 3.18: Layers of the Content view
图 3.18：内容视图的层次

 

Kind Layer  种类层级

For modeling purposes, different, generic Kinds of Content are assumed. Named k ind of content has a permanent identifier that is unique within a context or collection . There is no identifier (name) for anonymous content. Both kinds of content are disjoint , i.e., there is no single entity that is simultaneously an instance of both concepts.
为了建模目的，假设了不同、通用的内容种类。命名内容种类具有在上下文或集合内唯一的永久标识符。匿名内容没有标识符（名称）。这两种内容是互斥的，即不存在同时是这两种概念实例的单个实体。

 

Raw Data is an opaque sequence of bytes which is either bounded (e.g., a binary file) or unbounded (e.g., a media stream). No assumptions are made about its internal nature. Data Point consists of a single, primitive value which is an instance of a simple, basic data type. Record corresponds to a complex data type composed of nested structures and terminal primitives.
原始数据是一串不透明的字节序列，它要么是有限的（例如，二进制文件），要么是无限的（例如，媒体流）。对其内部性质不做任何假设。数据点由一个单一的基本值组成，该值是简单基本数据类型的一个实例。记录对应于由嵌套结构和终端原语组成的复杂数据类型。

 

Collections are a utility kind of content used to internally organize and enable access to groups of the aforementioned content kinds without interfering with the definition of the included elements. Lists are collections ordered according to a sort criterion allowing for a position/index-based access to elements, their sorting and grouping. Lists of resources may be ordered according to one or more dimensions. Data Points are usually ordered by time(stamps) or the element values. Records further allow for ordering by the attributes of embedded structures. Standalone elements (files) allow for ordering by file properties. Maps are collections that support a random, key-based access relying on a persistent identifier given to a resource. Whereas the concepts of Raw Data, Data Point and Data Record distinguish different levels of structuring – which often coincide with various stages of processing that data has undergone – collections are generic containers for bundling those kinds of content. Standardized serializations of the collection concept should be defined to comply with the respective representation of content.
收藏品是一种用于内部组织和访问上述内容种类组的工具类型内容，而不干扰包含元素的定义。列表是根据排序标准排序的集合，允许通过位置/索引访问元素、它们的排序和分组。资源列表可以按一个或多个维度排序。数据点通常按时间戳或元素值排序。记录进一步允许按嵌入结构的属性排序。独立元素（文件）允许按文件属性排序。映射是支持随机、基于键的访问的集合，依赖于分配给资源的持久标识符。而原始数据、数据点和数据记录的概念区分了不同的结构级别——这通常与数据所经历的各种处理阶段相对应——集合是捆绑这些内容类型的通用容器。应定义标准化的集合概念序列化以符合内容的相应表示。

 

Figure 3.19: Partial taxonomy of content kinds
图 3.19：内容类型的部分分类

 

The content kind of a resource and the type of collection determine the strategies to address the resource, or to select a range of (one or more) elements out of the collection. Table 3 summarizes some envisaged reference strategies.
资源的内容类型和集合类型决定了处理资源或从集合中选择（一个或多个）元素的策略。表 3 总结了预期的一些参考策略。

Table 3 : Summary of referencing strategies
表 3：引用策略概要

 

 

The following table summarizes the relation of the Content Kind, Collection type, referencing strategies, and operations available.
以下表格总结了内容类型、集合类型、引用策略和可用操作之间的关系

 

Table 4 : Summary of referencing strategies per content kind
表 4：按内容类型总结的引用策略

 

 

 

Representation Layer  表示层

The Representation L ayer defines serializations, i.e. physical representations of a related Content Kind. For example, the "image" Kind of Content might be provided as a raster (JPEG, PNG, GIF) or a vector graphics Representation (SVG). Developers of an "application for image anonymization" might provide alternative software Representations (Windows EXE, Debian DEB, or Java JAR) supporting different software environments and operating systems.
表示层定义了序列化，即相关内容类型的物理表示。例如，内容类型的“图像”可能以光栅（JPEG、PNG、GIF）或矢量图形表示（SVG）的形式提供。为“图像匿名化应用程序”的开发者可能提供支持不同软件环境和操作系统的替代软件表示（Windows EXE、Debian DEB 或 Java JAR）。

 

Figure 3.20: Outline of the Representation concept
图 3.20：表示概念的概述

 

A Representation of a content Kind is defined, among others, by a Data Type specified in terms of a Schema (i.e., formal description of the structure of data), and a Media Type, optionally augmented by Profiles (i.e., additional informal specifications and constraints that may apply). A Reference to a standard specifying that type of information should be provided, when existent. The Representation might specify a Mapping to an equivalent, but syntactically incompatible serialization. The Representation may further indicate available Packaging options to combine contents into a single Archive (tar), apply Compression (gzip) and Encryption algorithms (AES).
内容类型的表示由数据类型定义，数据类型以模式（即数据结构的正式描述）和媒体类型来指定，媒体类型可以由配置文件（即可能适用的附加非正式规范和约束）进行补充。当存在时，应提供指定该类型信息的标准引用。表示可能指定映射到等效但语法不兼容的序列化。表示还可以进一步指示可用的打包选项，将内容组合成单个存档（tar），应用压缩（gzip）和加密算法（AES）。

 

Artifact Layer  工件层

The Artifact layer focuses on the description of deliverable resource instances. Going beyond the prototypical Kind and representation models, it captures properties that are unique to individual materializations of the resource. Such, for example, a particular assembly of data might be individually referenced and associated with a custom Commodization model. The Artifact view of an application build would, for example, define its inherent characteristics, the distribution size, configuration options or software dependencies etc.
文物层专注于描述可交付资源实例。它不仅关注典型种类和表示模型，还捕捉资源个别具体化所特有的属性。例如，某种特定的数据组合可能被单独引用，并关联到定制的商品化模型。例如，应用程序构建的文物视图将定义其固有特性、分布大小、配置选项或软件依赖等。

 

The previous sections introduced the Content Layers of a resource. Aspects that apply to a description of Content in general are presented in the following. They will be augmented later on by aspects of Data Asset and Data App that apply only to the respective subclass of the resource concept.
前几节介绍了资源的内容层。以下将介绍适用于内容描述的一般方面。这些方面将在后续内容中通过仅适用于资源概念相应子类的数据资产和数据应用方面进行补充。

 

Provenance  原因

Provenance is concerned with the origin of the Content, as well as with the traceability of the processing steps the Content has undergone, and finally, also with the Agents that are responsible for those Activities. The main goal of provenance tracking is to ensure the reliability of the Content, so that modifications are made explicit, comprehensible and may be analyzed for defects.
原因涉及内容的来源，以及内容所经历的处理步骤的可追溯性，最后，还包括对这些活动负责的代理。原因跟踪的主要目标是确保内容的可靠性，以便修改明确、易懂，并且可以分析缺陷。

 

Figure 3.21 : Outline of the Provenance concept
图 3.21：原因概念概述

 

Communication View  通信视图
The Communication View deals with the (dynamic) communication of resource content. Similarly to the Content View, it is defined at multiple levels of detail. The Interface Layer conceptualizes the interchange of digital artifacts as a set of uniform operations (interactions primitives). The Service Layer defines bindings of such generic operations to concrete communication protocols turning them into operable resource endpoints.
通信视图处理资源内容的（动态）通信。与内容视图类似，它在多个细节级别上进行定义。接口层将数字实体的交换概念化为一系列统一操作（交互原语）。服务层将此类通用操作绑定到具体的通信协议，将它们转化为可操作的资源端点。

 

Figure 3.22: Layers of the Communication view
图 3.22：通信视图的层次

 

Interface Layer  接口层
Following the Service-oriented Architecture paradigm (SOA) this Layer defines the Interface concept comprising a set of Operations. There are multiple reasons motivating the definition of such an abstract service contract:
遵循面向服务的架构范式（SOA），此层定义了接口概念，包括一系列操作。定义此类抽象服务合同有多种原因：

• Separating a service interface from its implementation is a common practice and mandated by standards like [WSDL2].
• 将服务接口与其实现分离是常见的做法，并且由像 [WSDL2] 这样的标准所强制规定。
• A high-level description of a service interface (with a focus on functionality) allows Data Consumers to easily identify and interpret the interaction logic (i.e., operational capabilities).
• 对服务接口进行高级描述（侧重于功能）使数据消费者能够轻松识别和解释交互逻辑（即操作能力）。
• Protocol-specific interface definition languages may either not exist (e.g., [MQTT]), or require reverse engineering in order to infer such information (e.g., [Open API]).
• 特定协议的接口定义语言可能不存在（例如 [MQTT]），或者需要逆向工程来推断此类信息（例如 [Open API]）。
• Conventions and best practices in resource interchange have been informally established within several technological communities (e.g., REST-architecture paradigm). The concept of an abstract, technology-agnostic interaction interface may help to formalize those implicit patterns and foster their re-usability beyond the scope of protocols originally designed for this task (HTTP).
• 在多个技术社区中，资源交换的惯例和最佳实践已经非正式地建立（例如，REST-架构范式）。抽象的、与技术无关的交互接口的概念有助于正式化这些隐含的模式，并促进它们在最初为这项任务设计的协议（HTTP）范围之外的复用。

 

Figure 3.23: Outline of the Interface concept
图 3.23：接口概念概述

 

Inspired by the REST-architecture paradigm the set of operations available in resource interactions has been restricted to a selection of generic, reusable interaction primitives. The expressiveness of the resultant Resource Interaction Interfaces (RII) has been purposefully limited in favor of designing simple, uniform interfaces that could be easily interpreted by generic, automated clients.
受 REST 架构范式启发，资源交互中可用的操作已被限制为一系列通用、可重用的交互原语。为了设计简单、统一的接口，有意限制了结果资源交互接口（RII）的表达能力，以便于通用、自动化的客户端易于解释。

 

Operations  操作

Operations are the building blocks of an Interface. The operation signature lays down the expected input, its content promise (output parameters) and functional errors that might occur during the invocation (fault parameters).
操作是接口的构建块。操作签名规定了预期的输入、其内容承诺（输出参数）以及在调用过程中可能发生的功能错误（故障参数）。

 

Figure 3.24: Outline of the Operation concept
图 3.24：操作概念概述

 

Depending on operations, the interface may support various ways of data provision (Data Source), data reception (Data Sink), and meta-queries allowing the Data Consumer to introspect the interface as depicted by Table 5. Some descriptions refer to Parameter types subsequently defined in the Table 6.
根据操作，接口可能支持各种数据提供（数据源）、数据接收（数据汇）和元查询的方式，允许数据消费者如表格 5 所示内省接口。一些描述随后将参照表格 6 中定义的参数类型。

 

Table 5 : Operation types of the Resource Interaction Interface
表 5：资源交互接口的操作类型

 

 

 

Parameters  参数

Parameters are named slots of data exchange via operations of the resource Interaction Interface. They are defined in terms of a Content type, Parameter type, and a Representation (serialization). The Content Type designates the semantics of the data passed through (not to be confused with the homonymic HTTP header). Parameters might refer to structures of the resource content, that are mediated by the Parameter, (e.g. a table column) in order to re-use their semantics definition.
参数是通过资源交互接口的操作进行数据交换的命名槽位。它们在内容类型、参数类型和表示（序列化）的术语下定义。内容类型指定通过的数据的语义（不要与同名的 HTTP 头混淆）。参数可能指的是由参数介导的资源内容结构（例如，表列），以便重用其语义定义。

 

Figure 3.25: Outline of the Parameter concept
图 3.25：参数概念概述

 

Parameters share the Representation definition provided above. This is useful when mediating transient data which is not modeled as part of the resource content. The Parameter type provides hints to interface clients about the purpose and intended usage of the Parameter, and may e.g. support e.g. a query generation process. Table 6 provides a listing of currently envisaged, standard Parameter types.
参数共享上述提供的表示定义。这在调解作为资源内容一部分未建模的临时数据时很有用。参数类型为接口客户端提供有关参数目的和预期使用的提示，例如，可以支持查询生成过程。表 6 提供了目前设想的标准参数类型的列表。

 

Table 6 : Resource Interaction Interface – overview of parameter types
表 6：资源交互接口 - 参数类型概述

 

 

Service Layer  服务层
The resource Interaction Interface can be turned into an executable service by binding it to a concrete communication protocol. A protocol binding provides a vocabulary to map the abstract operation signatures onto the concrete structures (e.g., HTTP headers or query parameters), configuration parameters (e.g., MQTT broker), and interaction patterns (e.g., WSDL [Message Exchange Patterns]) of a protocol. Each instance of a Protocol Binding defines a resource Endpoint, an addressable and operable point of resource exchange which communicates Representations of a resource in compliance with the definitions of underlying Resource Interaction Interface. The Information Model does not constrain Data Providers in the way they configure the individual protocol bindings but it should provide a guidance and example instances demonstrating a recommended practice.
资源交互接口可以通过绑定到具体的通信协议来转换为可执行的服务。协议绑定提供了一种词汇表，将抽象操作签名映射到具体的结构（例如 HTTP 头或查询参数）、配置参数（例如 MQTT 代理）和交互模式（例如 WSDL[消息交换模式]）上。每个协议绑定的实例定义了一个资源端点，这是一个可寻址和可操作的资源交换点，它以符合底层资源交互接口定义的方式通信资源的表示。信息模型不限制数据提供者在配置单个协议绑定方面的方式，但它应提供指导和示例实例，以展示推荐的最佳实践。

 

Figure 3.26: Outline of the resource endpoint concept
图 3.26：资源端点概念概述

 

Commodization View  商品化视角

The  Commodization view focuses on the "commodity" aspects of a resource, amongst others its price, licensing model, and usage restrictions. It optionally lists the available Quality of Service options (per resource endpoint). Once published, the static dimensions of the Product concept are augmented by dynamic statistics and community feedback (rating, comments, etc.) represented by the Feedback concept. The Product information allows a potential Data Consumer to estimate the expenses and commercial exploitability of a resource.
商品化视角关注资源的“商品”属性，包括价格、许可模式和用途限制等。它还可以选择性地列出每个资源端点的可用服务质量选项。一旦发布，产品概念静态维度的静态维度将增加动态统计数据和社区反馈（评分、评论等），这些由反馈概念表示。产品信息允许潜在的数据消费者估计资源的费用和商业可利用性。

 

Figure 3.27: Outline of the Product concept
图 3.27：产品概念概述

 

Pricing  定价
The Pricing strategies of data marketplaces identified in [ERCIS15] apply likewise to IDS resources. The Free strategy does not charge the usage of resources. The Freemium strategy exposes a limited parts (or capabilities) of the resource at no cost, while additional parts are charged Pay-per-Use, or based on a Flat Rate. The Pay-per-Use strategy relies on a particular metrics (volume, access count, download) to define a charged instance of usage, while the Flat Rate strategy charges usage per quantitative slot (time, volume, credit), optionally associated with a tier¬ed cost model according to the configuration of the retrieved resource.
在[ERCIS15]中确定的数据市场定价策略同样适用于 IDS 资源。免费策略不收取资源使用费。免费增值策略免费提供资源的一部分（或功能），而额外部分则按使用付费，或按固定费率收费。按使用付费策略依赖于特定的指标（数量、访问次数、下载）来定义计费的使用实例，而固定费率策略则按定量槽（时间、数量、信用）计费，可根据检索资源的配置选择性地与分层成本模型相关联。

 

Regulations  规章

The regulatory aspects of the Commodization view are discussed in a separate section (see Section Facet 6:Regulations), because of their key role in implementing the data sovereignty of Data Owners and App Providers.
由于监管方面在商品化视图中的关键作用，其监管方面将在单独的章节中讨论（见第 6 个方面：规章制度），以实施数据所有者和应用提供商的数据主权。

 

Figure 3.28: Taxonomy of Product Pricing concepts
图 3.28：产品定价概念分类法

 

Summary  摘要

This section introduced the concept of an International Data Space resource, a generalization of the core asset concepts, the Data Asset and Data App. The resource is an identifiable, valuable, digital (non-physical) commodity traded and exchanged between participants by means of infrastructure components of the International Data Space. The specification of resource concept was given in terms of the Content, Communication, and Commodization views (3C-Principle). A refinement of the views by orthogonal layers lead to a complete description matrix as summarized in Figure 17.
本节介绍了国际数据空间资源的概念，这是对核心资产概念（数据资产和数据应用）的泛化。资源是一种可识别的、有价值的、数字的（非物理）商品，通过国际数据空间的基础设施组件在参与者之间进行交易和交换。资源概念的规定是以内容、通信和商品化视图（3C 原则）来表述的。通过正交层对视图的细化导致了一个完整的描述矩阵，如图 17 所示。

 

 

 

Facet 2: Data  面板 2：数据
Data is the central asset of the International Data Space. This section elaborates upon the concept of a Data Asset, an identifiable, non-physical entity that comprises data, or a service interface to data [NISTIR 7298]. The Data Asset concept is described only in the extent going beyond the description of the parent resource concept given above. Reference examples are presented to demonstrate the concept of a Data Asset. They demonstrate differences in the provision of static data versus dynamic data, different usage policies applied, different interaction patterns chosen, and different transfer protocols used.
数据是国际数据空间的核心资产。本节详细阐述了数据资产的概念，即一个可识别的非物理实体，包括数据或数据服务接口[NISTIR 7298]。数据资产的概念仅在本节中描述，超出了上述父资源概念的描述。通过参考示例来展示数据资产的概念。这些示例展示了静态数据与动态数据提供的差异、应用的不同使用策略、选择的不同交互模式和使用的不同传输协议。

 

Examples  示例
The reference data stems from a hypothetical scenario of measuring traffic conditions at defined locations of the highway E37 for purposes of traffic control, predictive road maintenance, toll fee optimization and so on.
参考数据源于一个假设场景，即测量高速公路 E37 在指定位置的交通状况，用于交通控制、预测性道路维护、通行费优化等目的。

Example DAT1: Off-line, free data download
示例 DAT1：离线，免费数据下载

The example DAT1 showcases an easy, non-interactive access to free, historical data. Monthly reports on traffic statistics collected during a year are provided for download at a fixed web address (.../trafficreport/). File names (e.g., E37_up_2018_01.csv.zip) consist of the (underscore separated) identifier of the highway (e.g., “E37”), the direction of travel (“up” or “down”, relative to highway mileage), year (e.g., “2018”) and month (e.g., “01”), and (optionally) the file (csv) and compression extension (zip). HTTP content negotiation or default settings may supplement missing values for file type (Accept-header) and compression (Accept-Encoding-header). The reports comprise tabular data with a fixed number of labeled columns. Each row corresponds to an individual value tuple collected in a certain sampling area within a certain sampling period. The sampling area is identified by a readable name (String), a distance marker (double, km), and the geo-location (according to a predefined geo-spatial reference system). The remaining columns contain the measurement details, i.e. the time stamp of the sampling period (ISO 8601 period format, YYYY-MM-DDThh:mmPnYnMnDTnHnM), the average velocity (double, km/h), and the number of vehicles passing (integer). The data may be used free of charge, but the policy requires a credits citation.
示例 DAT1 展示了轻松、非交互式访问免费历史数据的方法。提供了一年中收集的交通统计数据月度报告，可在固定的网络地址（.../trafficreport/）下载。文件名（例如，E37_up_2018_01.csv.zip）由高速公路（例如，“E37”）的标识符（用下划线分隔）、行驶方向（“up”或“down”，相对于高速公路里程）、年份（例如，“2018”）和月份（例如，“01”），以及（可选的）文件（csv）和压缩扩展名（zip）组成。HTTP 内容协商或默认设置可能补充文件类型（Accept-header）和压缩（Accept-Encoding-header）的缺失值。报告包含具有固定数量标签列的表格数据。每一行对应于在特定采样区域内特定采样期间收集的个别值元组。采样区域由一个可读的名称（字符串）、一个距离标记（双精度，公里）和地理定位（根据预定义的地理空间参考系统）标识。 剩余的列包含测量细节，即采样期间的时标（ISO 8601 期间格式，YYYY-MM-DDThh:mmPnYnMnDTnHnM），平均速度（双精度，千米/小时）以及通过的车辆数量（整数）。数据可免费使用，但政策要求引用信用。

Example DAT2: On-line, commercial data query
示例 DAT2：在线，商业数据查询

Example DAT2 introduces interactive features going beyond the retrieval of alternative representations of static content, allowing the Data Consumer to probe and accordingly operate services providing access to extended, growing datasets. In order to explore the dataset, the Data Consumer may request the value range of enumerable parameters (trafficreport/column/areaId), define valid filter conditions, and limit the report coverage to fit consumers' informational needs (trafficreport?filter=in(areaId,[id1,id2,id3]) in a fully automated manner. Elaborating upon the report structure of Example DAT1, the Data Consumer may learn about the available properties/columns (trafficreport/columns) and configure the report layout accordingly (trafficreport?column=areaId,timestamp,avgSpeed&orderBy=areaId,timestamp&order=asc). For some properties to be elicited, investments into dedicated sensory infrastructure may be required (e.g., weighbridge, vehicle type detection), making such values only commercially available (avgWeight, countVehicleTypeTruck). Pricing models may allow for discounts when combining payed properties. Depending on consumer’s request behavior, various payment models may be applied (pay-per-use, volume or time-based subscription, etc.). The usage policies of this sample prohibit resale of the commercial data parts.
示例 DAT2 引入了超越检索静态内容替代表示的交互式功能，允许数据消费者探测并相应地操作提供访问扩展、增长数据集的服务。为了探索数据集，数据消费者可以请求可枚举参数的值范围（trafficreport/column/areaId），定义有效的过滤条件，并以完全自动化的方式限制报告覆盖范围以适应消费者的信息需求（trafficreport?filter=in(areaId,[id1,id2,id3])）。在详细阐述示例 DAT1 的报告结构后，数据消费者可以了解可用的属性/列（trafficreport/columns）并相应地配置报告布局（trafficreport?column=areaId,timestamp,avgSpeed&orderBy=areaId,timestamp&order=asc）。对于某些属性的提取，可能需要投资于专用感知基础设施（例如，称重桥，车辆类型检测），使得这些值仅商业上可用（avgWeight，countVehicleTypeTruck）。定价模型可能允许在组合付费属性时提供折扣。 根据消费者的请求行为，可能应用各种支付模式（按使用付费、按量或时间订阅等）。本示例的使用政策禁止转售商业数据部分。

Example DAT3: Preprocessed, live data subscription
示例 DAT3：预处理，实时数据订阅
While data exchange in the two previous samples was driven by the Data Consumer (pull-pattern), Example DAT3 showcases a data-driven delivery, for which the Data Consumer is provided with content on the basis of a previously made subscription (push-pattern). In the context of the traffic monitoring scenario, a Data Consumer subscribes to traffic parameters, which values match a particular complex event pattern deployed on Data Provider premises as part of the subscription (see Facet #3: Applications section for details on examples of such rules).
在前两个示例中，数据交换是由数据消费者（拉模式）驱动的，而示例 DAT3 展示了数据驱动的交付，数据消费者根据之前做出的订阅获得内容（推模式）。在交通监控场景中，数据消费者订阅交通参数，其值与数据提供方场所部署的特定复杂事件模式相匹配，作为订阅的一部分（有关此类规则的示例，请参阅第 3 个方面：应用部分）。
The following sections summarize aspects that are considered specific to Data Assets.
以下各节总结了被认为与数据资产相关的内容。

 

 

Dynamicity  动态性
Data can differ significantly in terms of dynamicity (i.e., the way data expands and can be updated). As far as frequency is concerned, data may change spontaneously (i.e., on an irregular basis) or regularly (e.g., at a certain sampling rate). A change may represent an extension, i.e., an insertion in the middle of, or an addition at the head of, an ordered collection, a partial or complete update (replacement), or deletion of a collection item. (Continuously) extended, live collections (sensor measurements, log entries, message queues, etc.) differ from static collections. The time variance of data needs to be explicitly modeled and considered when selecting the appropriate interaction and communication protocol.
数据在动态性方面可能存在显著差异（即数据扩展和更新的方式）。就频率而言，数据可能自发地（即不规则地）或定期地（例如，以一定的采样率）发生变化。变化可能代表扩展，即在一个有序集合的中间插入，或在头部添加，或部分或完全更新（替换），或删除集合项。持续扩展的实时集合（如传感器测量、日志条目、消息队列等）与静态集合不同。数据的时间变化需要显式建模并在选择适当的交互和通信协议时予以考虑。

Context  上下文
The context is defined by the temporal, spatial, and socio-economical (or world) coverage of the data, i.e. the range of time, space, or real world entities referred to by the data. Accurate and meaningful context modeling gives answers to questions like “when”, “where”, and “what”, and is seen as a prerequisite for the assessment of data's relevance and business value with respect to the needs of Data Consumers. In the traffic scenario introduced above, the temporal context is the overall time period the data was collected in; its upper bound (end time) is undefined here because of the continuously extended live data). The spatial context of the examples may be defined by the geographical extent (union of bounding boxes) enclosing the sampling area. The world context may comprise the enumeration of the highways as a real-world objects of interest. An overly broad and excessive context description might impede the discoverability and value assessment of the Data Asset.
上下文由数据的时序、空间和社会经济（或世界）覆盖范围定义，即数据所涉及的时间范围、空间或现实世界实体的范围。准确且具有意义的上下文建模可以回答诸如“何时”、“何地”和“什么”等问题，并被视为评估数据与数据消费者需求相关的相关性和商业价值的前提。在上文所述的交通场景中，时序上下文是指数据收集的整体时间段；由于实时数据的持续扩展，其上限（结束时间）在此未定义。示例中的空间上下文可能由包围采样区域的地理范围（边界框的并集）定义。过于宽泛和过度的上下文描述可能会妨碍数据资产的发现性和价值评估。

 

Figure 3.30: Taxonomy of the Data Asset Context
图 3.30：数据资产上下文分类法

 

 

Topic  主题
The topic of a Data Assets emphasizes the essential statement of the data, its purpose, or interpretation. It might express the relation of data to the world context. Topics appropriate in a given traffic scenario are, for example "monitoring", "statistics", etc.
数据资产的主题强调数据的本质陈述、目的或解释。它可能表达数据与世界观的关系。在特定的交通场景中，适当的话题，例如“监控”、“统计”等。

 

Facet 3: Applications  方面 3：应用

The Application facet focuses on the description of reusable software and auxiliary artifacts delivering a data-specific functionality. Data Apps are self-contained and self-descriptive software packages (e.g. Linux Containers) extending the functionality of the generic Connector with custom capabilities. In addition, there are Data App Plug-ins and Data App Assets. A Data App Plug-in is an add-on of a Data App, adding new capabilities to it. The extension management process for selection, installation, and maintenance of such plugins has to be implemented by the respective Data App in accordance with the security policies of the Connector. A Data App Asset is a machine-interpretable Data Asset, such as a script file, algorithm, rule set, or another type of code, which execution relies on a particular runtime environment.
应用方面侧重于描述可重用软件和提供特定数据功能的辅助工件。数据应用是自包含且自描述的软件包（例如 Linux 容器），它通过自定义功能扩展了通用连接器的功能。此外，还有数据应用插件和数据资产。数据应用插件是数据应用的附加组件，为其添加新功能。此类插件的扩展管理过程，包括选择、安装和维护，必须由相应的数据应用根据连接器的安全策略实施。数据资产是机器可解释的数据资产，如脚本文件、算法、规则集或其他类型的代码，其执行依赖于特定的运行环境。

 

Examples  示例
The following reference examples demonstrate the provision, extension, and configuration of application logic in context of the traffic scenario.
以下参考示例展示了交通场景中应用程序逻辑的提供、扩展和配置。

Example DAP1: Data App for image anonymization
示例 DAP1：数据应用图像匿名化

The photographs taken by the surveillance camera have to be anonymized before being forwarded to a Data Consumer. This sample accepts images of standard traffic scenarios in various file formats (e.g. PNG, JPG) recorded in compliance with the international norm [EN 50132-7]. It is trained to locate particular personal information (e.g., the license plate of a car) and to apply image processing techniques to irreversibly obfuscate this information.
监控摄像头拍摄的图像在转发给数据消费者之前必须进行匿名化处理。本示例接受符合国际标准[EN 50132-7]的记录在各种文件格式（例如 PNG、JPG）中的标准交通场景图像。它被训练用于定位特定个人信息（例如，汽车的牌照）并应用图像处理技术来不可逆地模糊此信息。

Example DAP2: Data App Plugin for advanced image processing
示例 DAP2：高级图像处理数据应用插件

There may be scenarios that impose advanced privacy requirements and require a dedicated plug-in to augment the aforementioned sample with a capability of advanced image processing (e.g., face anonymization).
可能存在需要高级隐私要求并需要专用插件来增强上述示例以具备高级图像处理能力（例如人脸匿名化）的场景。

Example DAP3: Data App Asset as interpreted CEP rule (DAP3)
Example DAP3：数据应用资产作为解释型 CEP 规则（DAP3）的解读

The Data Consumer in the traffic scenario might define complex event processing (CEP) rules as part of a data subscription in order to shift the task of processing and monitoring live data at the edge of the network (edge computing). One such rule may request a notification sent every time the average speed in a critical area dropped below 10 km/h within the last 5 minutes (risk of congestion). Likewise, a notification is sent every time a truck weighing more than 20t heads towards a bridge that has only limited load carrying capacity (limited access). The content of the notification message, the communication protocol (MQTT), the quality of the service parameters (at-least-once delivery), and other details are defined by the rule as part of the subscription.
在交通场景中，数据消费者可能将复杂事件处理（CEP）规则定义为数据订阅的一部分，以便将处理和监控实时数据在网络的边缘（边缘计算）的任务转移。例如，可能有一条规则要求每当过去 5 分钟内关键区域的平均速度低于 10 公里/小时时（拥堵风险）就发送通知。同样，当一辆超过 20 吨的卡车驶向承载能力有限的桥梁时（有限通行），也会发送通知。通知消息的内容、通信协议（MQTT）、服务质量参数（至少一次投递）和其他细节都由规则作为订阅的一部分定义。

 

Dimensions  维度
In course of their life-cycle Data App may be considered according to various dimensions, as illustrated by Figure 19.
在其生命周期过程中，数据应用可以从多个维度进行考虑，如图 19 所示。

 

Figure 3.31: Dimensions of Data Apps
图 3.31：数据应用维度

 

The Resource dimension, shared by Data Assets and Data Apps, specifies their quality as a tradable digital commodity according to the 3C-Principle. The Functionality dimension expresses the functional potential, i.e. data handling capabilities, of a Data App published via the App Store component. The Deployment dimension deals with the runtime aspects of a concrete application deployment (security updates, quality of service and usage control enforcement etc.).
资源维度由数据资产和数据应用共享，根据 3C-原则指定其作为可交易数字商品的质量。功能维度表达了通过应用商店组件发布的数据应用的功能潜力，即数据处理能力。部署维度处理具体应用程序部署的运行时方面（安全更新、服务质量和使用控制执行等）。

 

Resource  资源
The following sections focus on the Resource dimension of the Data Apps. The views and layers of the 3C-Principle are instantiated according to characteristics of Data Apps.
以下章节重点介绍数据应用的资源维度。3C-原则的视图和层根据数据应用的特征进行实例化。

 

Content View  内容视图
The Content View considers the static, structural aspects of the Data App Resource. Its general Kind is expressed by a reference to a shared taxonomy of applications Categories, while a detailed modeling of the functionality is delegated to the Functionality dimension. The Representation Layer defines the distributions available as a combination of available software file formats and general properties of the target system (hardware architecture, operating system). Optionally, the Artifact Layer may elaborate about the structure, dependencies, configuration and requirements of a particular application build.
内容视图考虑数据应用资源的静态、结构方面。其一般类型通过引用共享的应用类别分类法来表示，而功能的具体建模则委托给功能维度。表示层定义了作为可用软件文件格式和目标系统（硬件架构、操作系统）的一般属性的组合可用的分布。可选地，工件层可以详细说明特定应用程序构建的结构、依赖关系、配置和需求。

 

Figure 3.32: Content view of the Data App resource
图 3.32：数据应用资源内容视图

 

The Structure concept discloses the internal software components the Data Apps uses or is based on. It allows to estimate their technical maturity, potential technical and security risks, e.g. once defects or security vulnerabilities of those components were reported. The Dependencies concept deals with the reliance on external software artifacts. The Environment concept encompasses the requirements on the execution context of the Data App, among others the runtime environment (J2EE, Linux-Container runtime), its configuration, and resources made available to the application (storage volume, network ports, memory, CPU). Finally, the Configuration concept describes the configuration options and default settings etc. The Signature concept covers the verifiable identity, integrity and formal IDS certification of the Artifact.
结构概念揭示了数据应用使用或基于的内部软件组件。它允许估计其技术成熟度、潜在的技术和安全风险，例如一旦报告了这些组件的缺陷或安全漏洞。依赖关系概念处理对外部软件工件的需求。环境概念包括对数据应用执行上下文的要求，例如运行时环境（J2EE、Linux-Container 运行时）、其配置以及提供给应用程序的资源（存储卷、网络端口、内存、CPU）。最后，配置概念描述了配置选项和默认设置等。签名概念涵盖了工件的可验证身份、完整性和正式的 IDS 认证。

 

Communication View  通信视图

The Communication view deals with the physical distribution of the Data App resource. Depending on the distribution strategy, a signed Data App might be provided in a decentralized manner by the Application Provider, similarly to a Data Asset, or retrieved from a central App Store repository. In the former case, the Application Provider has to define a resource Endpoint within a local Connector and publish it to the App Store Registry. Its resource Interaction Interface should enable the prospective Application user to select, customize and download an appropriate Data App resource. In the latter, default case, these tasks are handled by a generic resource Endpoint exposed by the App Store Repository.
通信视图处理数据应用资源的物理分布。根据分布策略，签名数据应用可能以去中心化的方式由应用提供者提供，类似于数据资产，或从中央应用商店仓库检索。在前一种情况下，应用提供者必须在本地连接器中定义一个资源端点并将其发布到应用商店注册表。其资源交互接口应允许潜在的应用用户选择、定制和下载适当的数据应用资源。在后一种，默认情况下，这些任务由应用商店仓库公开的通用资源端点处理。

Commodization View  商品化视角

In addition to the general considerations of the Resource Commodization View, specific aspects apply for Data Apps. An obvious example are the various deployment options, as listed in Table 7. Both on-premises deployment options impose additional agreements with regard to maintenance, upgrades, and usage policy enforcement.
除了资源商品化视图的一般性考虑之外，对于数据应用还有一些特定的方面需要考虑。一个明显的例子是各种部署选项，如表 7 所示。本地部署选项在维护、升级和执行使用政策方面都要求额外的协议。

 

Table 7 : Deployment options of Data Apps
表 7：数据应用部署选项

 

 

 

Functionality  功能
The Functionality dimension expresses the capabilities of a Data App to handle a type of data in a particular way. The Content view details out the Kind and syntactic Representation of the data in question. At the definition time there are no concrete data instances to be handled, therefore the Artifact layer of the Content view is omitted. Please refer to Section Content View for details. The Communication view defines a custom Data Interface in terms of Operations exposed by the Data App. Figure 21 summarizes the main aspects of the Functionality dimension.
功能维度表达了数据应用以特定方式处理某类数据的能力。内容视图详细说明了所涉及数据的类型和句法表示。在定义时没有具体的数据实例需要处理，因此内容视图的工件层被省略。请参阅内容视图部分以获取详细信息。通信视图定义了数据应用公开的操作的定制数据接口。图 21 总结了功能维度的主要方面。

 

Figure 3.33: Description matrix of the Data App Functionality dimension
图 3.33：数据应用功能维度描述矩阵

 

 

Communication View  通信视图
The Communication view considers in this context the abstract Data Interface (Interface Layer) of a Data App and its materialization as a Data Service (Service Layer).
在此上下文中，通信视图考虑了数据应用的数据接口（接口层）及其作为数据服务（服务层）的具体实现。

The Data Interface models the effective functionality of a Data App. It encapsulates a range of Operations upon data passed via the Parameters of the Operation. The semantic type of an Operation indicates the processing of and effect on input data in an interoperable way. The set of available Operation types includes the subset of Resource Interaction Interface Operation types and is deliberately not restricted. Data App Developers are free to specify custom Operation types in accordance to the Information Model governance rules. Depending on the data flow and interactions supported by the individual Operations, a Data App may act as a Data Providing App, Data Processing App or a Data Consuming App. These concepts are not disjoint, a single Data App may simultaneously implement any combination of these roles.
数据接口模拟了数据应用的有效功能。它封装了一系列通过操作参数传递的数据操作。操作的语义类型指示以互操作的方式处理和影响输入数据。可用的操作类型包括资源交互接口操作类型的子集，并且故意不加以限制。数据应用开发者可以根据信息模型治理规则自由指定自定义操作类型。根据个别操作支持的数据流和交互，数据应用可能充当数据提供应用、数据处理应用或数据消费应用。这些概念不是互斥的，单个数据应用可以同时实现这些角色的任何组合。

 

Figure 3.34: Data App taxonomy
图 3.34：数据应用分类

 

A Data Providing App exposes data by means of at least one Provide data Operation, as illustrated by Figure 23. Equally a Data Consuming App exposes at least one Consume data Operation in order to receive (and store) data. Please refer to Table 5 for a definition of those Operation types.
一个数据提供应用通过至少一个提供数据操作来公开数据，如图 23 所示。同样，一个数据消费应用至少公开一个消费数据操作以接收（并存储）数据。请参阅表 5 以了解这些操作类型的定义。

 

Figure 3.35: Outline of the Data Providing App concept
图 3.35：数据提供应用概念概述

 

Data Processing Apps expose custom functionality via at least one Process Data Operation. The range of such Operation types is rather infinite, the Table 8 provides some examples of possible subclasses.
数据处理应用通过至少一个处理数据操作来公开自定义功能。此类操作类型的范围相当无限，表 8 提供了可能的子类的一些示例。

Table 8 : Examples of Process data Operation types
表 8：处理数据操作类型的示例

 

 

At the Service layer Data Apps may require bindings to further, e.g. native protocols (IPC socket) in addition to "remote", web-based protocols involved in exchange of resources. The corresponding requirements and examples are being collected and will be included in the next document iteration. The Service description in context of the Functionality dimension is inevitably incomplete, the Data Service model remains a template with no references to a real Deployment.
在服务层，数据应用可能需要绑定到更进一步的，例如原生协议（IPC 套接字），以及涉及资源交换的“远程”、基于 Web 的协议。相应的需求和示例正在收集中，并将包含在下一份文档迭代中。在功能维度中的服务描述不可避免地是不完整的，数据服务模型仍然是一个没有参考实际部署的模板。

 

Deployment  部署

The Deployment dimension deals with concrete installations of Data Apps. A previously incomplete Data Service template becomes instantiated into a physically accessible Service model (endpoint) based on parameters of the host environment (IP address, port etc.). Data Providing and Data Consuming Apps may easily be turned into resource Endpoints by complementing their description in accordance with the 3C-Principle (e.g. by addition of the missing Product layer). The tasks to be supported by an Information Model of a Data App Deployment are, among others, the tracking of administration provenance (modifications applied to the application), logging of execution parameters (downtimes, usage of computational resources, service availability etc.) and the support of maintenance life-cycle (security updates etc.).
部署维度涉及数据应用的实体安装。一个之前不完整的数据服务模板根据主机环境的参数（IP 地址、端口等）实例化为一个物理可访问的服务模型（端点）。数据提供和消费应用可以通过补充其描述（例如，通过添加缺失的产品层）轻松地转变为资源端点。数据应用部署的信息模型需要支持的任务包括，但不限于，跟踪管理溯源（对应用程序应用的修改）、记录执行参数（停机时间、计算资源的使用、服务可用性等）以及支持维护生命周期（安全更新等）。

Summary  摘要
This section elaborated upon the concept of a Data App, a re-usable software and auxiliary artifacts delivering a data-centric functionality. Data Apps were analysed along three dimensions. The resource dimension considers Data Apps as a tradable digital commodity according to the 3C-Principle. The Functionality dimension expresses its data handling capabilities, whereas the Deployment dimension deals with the runtime aspects of a concrete application deployment. Depending on the data flow and interactions supported Data App were categorized as a Data Providing App, Data Processing App, and Data Consuming App.
本节详细阐述了数据应用的概念，数据应用是一种可重用的软件及其辅助工件，提供以数据为中心的功能。数据应用从三个维度进行了分析。资源维度将数据应用视为根据 3C 原则的可交易数字商品。功能维度表达了其数据处理能力，而部署维度则处理具体应用程序部署的运行时方面。根据支持的数据流和交互，数据应用被分为数据提供应用、数据处理应用和数据消费应用。

 

Facet 4: Infrastructure  4. 基础设施

 

Figure 3.36: Taxonomy of infrastructure components
图 3.36：基础设施组件分类

 

Figure 24 outlines a taxonomy of the main Infrastructure components of the International Data Space. The Connector is its core building block, a communication server providing and consuming data by means of Data Apps via a number of resource endpoints. The Broker component is a meta-data registry of Data Asset offerings, whereas the App Store is a registry of Data App offerings and a secure registry for their distribution. The Vocabulary Hub serves the maintenance of shared vocabularies and related (schema) documents. The Identity Provider manages and validates the digital identity of International Data Space Participants. The Clearing House provides clearing and settlement services B2B interactions within the International Data Space.
图 24 概述了国际数据空间主要基础设施组件的分类。连接器是其核心构建块，通过数据应用和多个资源端点提供和消耗数据。经纪人组件是数据资产提供的元数据注册库，而应用商店是数据应用提供的注册库，也是其分发的安全注册库。词汇中心负责维护共享词汇和相关（模式）文档。身份提供者管理和验证国际数据空间参与者的数字身份。清算所提供国际数据空间内 B2B 交互的清算和结算服务。

 

Connector  连接器

Being the dedicated point of data exchange and usage policy enforcement, the Connector is the central component of the infrastructure. It constitutes the basis for the implementation of other, more specialized components, such as the Broker. Each Connector may expose an arbitrary number of resource endpoints, offerings of digital commodities that are optionally advertised by publication at the meta-data registries, the Broker, or App Store respectively. The Deployment Context of a Connector comprises the geo-location information (e.g., country of deployment or applicability of national law), deployment type (on-premises vs. cloud). Furthermore, the responsible Participant operating the Connector (Service Provider) is referenced.
作为数据交换和用法政策执行的专用点，连接器是基础设施的核心组件。它是实现其他更专业组件（如代理）的基础。每个连接器可以公开任意数量的资源端点，即数字商品的提供，这些商品可以选择性地通过在元数据注册表、代理或应用商店发布来宣传。连接器的部署上下文包括地理位置信息（例如，部署国家或适用国家法律）、部署类型（本地化部署与云部署）。此外，还引用了负责运营连接器的参与者（服务提供商）。

 

Figure 3.37: Outline of the Connector concept
图 3.37：连接器概念概述

 

A Connector may specify the supported Security Profile in order to indicate a level of technical trustworthiness. The Security Profile is composed of several security options, which are outlined in Figure 26, among others the capability of a remote integrity verification, applications isolation level etc.  Predefined configurations of Security Profiles should be supplied in order to identify common security levels of Connectors (e.g. Base Connector, Trusted Connector etc.).
连接器可以指定支持的 安全配置文件，以表明技术可靠性水平。安全配置文件由多个安全选项组成，如图 26 所示，其中包括远程完整性验证能力、应用程序隔离级别等。应提供预定义的安全配置文件配置，以识别连接器的常见安全级别（例如，基本连接器、可信连接器等）。

 

Figure 3.38: Outline of the Security Profile concept
图 3.38：安全配置文件概念概述

 

The capabilities of enforcing data usage control by the Connector are modeled as part of the Security profile. These cover information whether and how certain usage control policies (e.g., mandatory deletion of data after a certain period of time) are automatically enforced by the Connector (i.e., on the technical level) or supported by governance processes during the data consumption process (i.e., on the organizational level).
连接器强制执行数据使用控制的能力作为安全配置文件的一部分进行建模。这包括有关某些使用控制策略（例如，在一段时间后强制删除数据）是否以及如何由连接器自动执行（即在技术层面上）或由治理流程在数据消费过程中支持（即在组织层面上）的信息。

 

Facet 5: Participants  面板 5：参与者
A participant is a legal or natural person assuming a role (or more than one role) in the International Data Space. For certain, critical roles to assume, participants must undergo a certification. Certification of participants is considered a measure to establish trust across the International Data Space.
参与者是在国际数据空间中承担（或承担多个）角色的法人或自然人。对于某些必须承担的关键角色，参与者必须接受认证。参与者的认证被视为在国际数据空间内建立信任的措施。

 

Examples  示例
Instances of participants involved in the traffic scenario are outlined below.
以下概述了参与交通场景的参与者实例。

Example PAT1: Multi-national logistics company
示例 PAT1：跨国物流公司
MAIER Logistics is a multinational logistics company with hundreds of trucks driving throughout Europe. The company is interested in live traffic monitoring data, as it wants to provide its drivers with up-to-the-minute traffic information to allow for efficient routing and timely issuing of hazard warnings. In this scenario, MAIER Logistics is an organization that runs several sites, such as MAIER Deutschland, Musterstraße 5, Köln, Deutschland, or MAIER UK, Example Road 5, Liverpool, United Kingdom. The organization complies with the ISIC classification rev. 4 and has ISIC code 4923 (freight transport via road). For this scenario, the company’s distribution departments are relevant, being the organizations which control and monitor outbound distribution via trucks. The distribution departments are part of the MAIER Logistics Organization. Each distribution department has a specific site. The German Distribution department is located at MAIER Logistics Distribution Cologne, Musterallee 323, Köln, Deutschland. MAIER Logistics Distribution Cologne assumes the role of a Data Consumer in data Example DAT3. It has a valid certificate and a unique identity. As a Data Consumer, it receives notifications with hazard warnings and congestion information. The information received is processed by a custom software of the department, which sends the information to the trucks using geo-location information.
迈尔物流是一家跨国物流公司，拥有数百辆卡车在欧洲各地行驶。该公司对实时交通监控数据感兴趣，因为它希望为驾驶员提供最新的交通信息，以便进行高效路线规划和及时发布危险警告。在这种情况下，迈尔物流是一家运营多个地点的组织，例如迈尔德国，Musterstraße 5，科隆，德国，或迈尔英国，Example Road 5，利物浦，英国。该组织符合 ISIC 分类修订版 4，拥有 ISIC 代码 4923（公路货运）。对于此场景，公司的分销部门是相关的，因为它们是控制和监控通过卡车进行出口分销的组织。分销部门是迈尔物流组织的一部分。每个分销部门都有一个特定的地点。德国分销部门位于迈尔物流分销科隆，Musterallee 323，科隆，德国。迈尔物流分销科隆在数据示例 DAT3 中扮演数据消费者角色。它拥有有效的证书和唯一的身份。 作为数据消费者，它接收危害警告和拥堵信息的通知。接收到的信息由部门定制的软件进行处理，然后利用地理定位信息将信息发送到卡车。

 

Figure 3.39: Outline of the Participant concept
图 3.39：参与者概念概述

 

Organization and Person  组织和个人
A Participant can be an organization (or organizational unit) or an individual. If the participant is an organization, it may consist of sub-organizations, departments, or other organizational structures. Corporations may indicate an organizational structure by linking to subsidiary companies or organizational units acting as related, but more or less independent participants. This approach allows sharing authorization certificates along a trust chain and enforcing company-wide policies. If the participant is an individual, he or she may assume a specific role in the corresponding organization.
参与者可以是组织（或组织单位）或个人。如果参与者是组织，它可能包括子组织、部门或其他组织结构。公司可以通过链接到子公司或作为相关但相对独立参与者的组织单位来表示组织结构。这种方法允许在信任链中共享授权证书并执行公司范围内的政策。如果参与者是个人，他或她可能在相应的组织中担任特定角色。

Business Classification  商业分类
Participants may indicate the type of business and the domain in which they operate by making references to established business classifications, i.e., business catalogs or registries. The classification can be used, for example, to search for data assets according to business category. For formal representation of business classifications, e.g. NAICS identifiers can be used. These are part of the extended core of the International Data Space Information Model. It will therefore be possible to support additional classification schemes (such as D&B D-U-N-S® Number, ISIC, or UNSPSC) in future revisions of the extended core model.
参与者可以通过引用已建立的商业分类，例如商业目录或注册，来表明其业务类型和运营领域。例如，可以使用分类来根据业务类别搜索数据资产。为了正式表示商业分类，例如可以使用 NAICS 标识符。这些是国际数据空间信息模型的扩展核心的一部分。因此，在扩展核心模型的未来修订中，将能够支持额外的分类方案（如 D&B D-U-N-S®编号、ISIC 或 UNSPSC）。

Site  场地
Each Participant can be assigned to one or more unambiguously defined Sites. Site information comprises the name and address of the site as well as geo-location information. It is particularly important in cases in which specific rules (e.g., national law) apply, affecting, for example, the data usage control policy.
每个参与者可以分配到一个或多个明确定义的站点。站点信息包括站点的名称和地址以及地理位置信息。在特定规则（例如，国家法律）适用的情况下，这些规则会影响数据使用控制政策，此时尤其重要。

Identity  身份
By default, and in accordance with linked-data principles, a participant can unambiguously be identified by a dereferencable HTTPS URL, which references to a live meta-data document describing the participant. This identity is confirmed by a (X509) certificate.
默认情况下，并符合链接数据原则，参与者可以通过一个可解析的 HTTPS URL 被明确识别，该 URL 引用一个描述参与者的实时元数据文档。此身份由（X509）证书确认。

 

 

Facet 6: Regulations  面板 6：法规
This section refers to contracts and policies governing the interactions of participants and how they use data assets.
本节涉及规范和协议，这些规范和协议规定了参与者之间的互动以及他们如何使用数据资产。

 

Usage Contract  使用合同
A pivotal part of the Product concept introduced by the Commodization view of resources in Section Commodization View is the formal expression of Usage Contracts pertaining to the Product. The Usage Contract defines a validity Period and formal Rules agreed upon by Participants involved in the provision, or subsequent usage of the Product.
资源商品化视角中，在“商品化视角”章节引入的产品概念中，一个关键部分是对产品使用合同的正式表达。使用合同定义了有效期限和参与者之间就产品提供或后续使用所达成的一致正式规则。

 

Figure 3.40: Outline of the Usage Contract concept
图 3.40：使用合同概念概述

 

The Rules specify Actions that an involved Party (Participant) is obliged, permitted or prohibited to perform with respect to an Asset (resource or a collection of resources). Formal Constraints state the applicability of Rules and refine the interpretation of Actions. Given the reference data example DAT1, a Permission allowing for an unrestricted usage of the data holds when the Data Consumer met her Obligation to cite the data source. The Reference data example DAT2 prohibits the resale of commercial data segments via a Prohibition on Data Consumer. With respect do data example DAT3 a Duty may express the Obligation on Data Provider to maintain a particular Quality of Service (QoS) level, i.e. publish the live sensor data at a particular rate and warrant a reliable delivery (QoS level "at least once").
规则规定了参与方（参与者）在资产（资源或资源集合）方面的义务、允许或禁止执行的行为。正式约束说明了规则的可适用性并细化了行为的解释。以参考数据示例 DAT1 为例，当数据消费者履行了引用数据来源的义务时，允许无限制使用数据的权限成立。参考数据示例 DAT2 禁止通过禁止数据消费者来转售商业数据段。对于数据示例 DAT3，义务可能表达数据提供者维持特定服务质量（QoS）水平的义务，即以特定速率发布实时传感器数据并保证可靠交付（QoS 水平“至少一次”）。

 

Figure 3.41: Outline of the Rule concept
图 3.41：规则概念概述

 

Usage Contracts formalize the expectations on behavior of involved Participants in a declarative, technology-agnostic way. The perpetual control and enforcement of such specification level policies may involve the inception of governance processes or, when appropriate the deployment of a technological solution. Data Usage Control Frameworks like [IND²UCE] define implementation-level policy languages in terms of technology-dependent events and actions, i.e. access to or modification of single files. Appropriate Policy Mappings should be specified to cope with the obvious conceptual gap between both policy levels and to enable a reliable and affordable technological enforcement of (parts of) Usage Contracts. Usage Contracts therefore should indicate an enforcement strategy and, in case of a technological enforcement, the Policy Mappings to be supported by the target Connector. As mentioned in Section Connector, a Connector should disclose its Usage Control capabilities as part of its Security Profile.
使用合同以声明性、技术无关的方式明确涉及参与者的行为期望。此类规范级别政策的持续控制和执行可能涉及治理流程的启动，或者在适当的情况下部署技术解决方案。像[IND²UCE]这样的数据使用控制框架定义了基于技术相关事件和行为的实施级别策略语言，即对单个文件的访问或修改。应指定适当的策略映射，以应对两者政策级别之间明显的概念差距，并确保（部分）使用合同的可靠和经济的技术执行。因此，使用合同应指明执行策略，在技术执行的情况下，还应指明目标连接器应支持的策略映射。如第连接器节所述，连接器应将其使用控制能力作为其安全配置文件的一部分披露。

 

Subscription  订阅
The Subscription concept expresses an Obligation to deliver data at a particular Quality of Service mandated by the Usage Contract from an active Data Source to a number of subscribed Data Sink targets within the given Period.
订阅概念表示在特定服务质量的义务，即在给定的期限内，从活跃的数据源向多个订阅的数据汇目标交付数据。这一义务由使用合同规定。

 

Figure 3.42: Outline of the Subscription concept
图 3.42：订阅概念概述

 

Facet 7: Interactions  面板 7：交互

The Interactions facet deals with concepts underlying business interactions among the IDS Participant, i.e. the interchange and consumption of Resources according to defined Regulations. The internal maintenance and operation processes of the IDS Infrastructure are considered afterwards. Both facet are subject to an ongoing change and are presented in a limited extent.
交互纵向处理 IDS 参与者（即参与者）之间的业务交互背后的概念，即根据定义的规则进行资源交换和消费。随后考虑 IDS 基础设施的内部维护和运营流程。这两个纵向都处于持续变化中，并且仅以有限的方式呈现。

Data Transfer  数据传输
Each Resource interchange in the International Data Space is modeled as an instance of the Data Transfer concept. It specifies a minimalistic meta-data model supporting security, traceability and usage control purposes. The Data Transfer refers to the originating and target Resource Endpoints, the time-stamp and the Payload (Resource) being distributed. The message is optionally signed and contains an authentication token (Trusted Connector). The Data Transfer carries a reference to the underlying Usage Contract, a source of formerly aggreed usage policies, optionally augmented by a dynamic instance of a Usage Policy.
国际数据空间中，每个资源的交互都建模为数据传输概念的实例。它指定了一个支持安全、可追溯性和使用控制的简约元数据模型。数据传输指的是源和目标资源端点、时间戳以及被分发的有效载荷（资源）。消息可选签名并包含一个认证令牌（可信连接器）。数据传输携带对底层使用合同的引用，该合同是以前同意的使用策略的来源，可选地由使用策略的动态实例进行补充。

 

Figure 3.43: Outline of the Data Transfer concept
图 3.43：数据传输概念概述

 

Facet 8: Maintenance  面板 8：维护

The Maintenance facet deals with the concepts describing the internal processes of maintenance and operation of the IDS Infrastructure, including the maintenance and dissemination of shared informational Resources, e.g. Ontologies.
维护方面涉及描述 IDS 基础设施维护和操作内部过程的概要，包括共享信息资源（例如本体）的维护和传播。

Life-cycle tracking  生命周期跟踪
Infrastructure components of the International Data Space are subjects to administrative operations, i.e. a life-cycle management defined by a set of States. The transition among these states are triggered by standardized Activities performed by administrative Agents. A record of life-cycle events should be maintained, e.g. to analyze and prevent failure conditions. Likewise the meta-data descriptions of Resources and Participants evolve over the time demanding for a life-cycle management and versioning. Such, e.g. historical versions of contracts have to be maintained alongside with recent revision or the representation of a Participant, created at some point may become temporarily suspended or permanently blocked. The concept of an Entity with Lifecycle was introduced to represent entities that are subject to evolution which needs to be tracked.
国际数据空间的基础设施组件受行政操作管理，即由一组国家定义的生命周期管理。这些状态之间的转换由行政代理执行的标准化活动触发。应维护生命周期事件的记录，例如，用于分析和预防故障条件。同样，资源和参与者的元数据描述随着时间的推移而演变，需要生命周期管理和版本控制。例如，必须维护合同的历次历史版本，以及可能在某个时间点创建的参与者的表示，该表示可能暂时暂停或永久阻止。引入了具有生命周期的实体概念，以表示需要跟踪进化的实体。

 

Figure 3.40: Outline of the Entity with Lifecycle
图 3.40：实体的生命周期概述

3.3. Vocabularies  3.3. 词汇表

Combining data from various sources in different formats and modeling views requires both syntactic and semantic integration efforts. Whereas a syntactic integration can be established by relying on common data formats, like XML or JSON, the semantic variety also needs a shared and formalized understanding on the meaning of the used terminology. In particular, searching and selecting data sources, exchanging datasets and invoking and accessing software services requires explicit information on the meaning of concepts.
将来自不同格式和视图的数据源的数据结合起来，需要语法和语义的集成努力。虽然可以通过依赖常见的数据格式（如 XML 或 JSON）来建立语法集成，但语义多样性也需要对使用术语的含义有一个共享和正式的理解。特别是，搜索和选择数据源、交换数据集以及调用和访问软件服务都需要对概念含义的明确信息。

Controlled vocabularies are the most basic form of shared concepts. While the meaning and spelling of terms is determined, no further information on the inherent structure is modeled. As such, controlled vocabularies form a light-weight approach with low entry barriers for data integration among partners and systems where a basic data exchange with restricted background information is sufficient.
控制词汇表是共享概念的最基本形式。虽然术语的意义和拼写已确定，但对其内在结构的进一步信息并未建模。因此，控制词汇表是一种轻量级方法，具有低门槛，适用于合作伙伴和系统之间的数据集成，在这些集成中，基本的数据交换与有限背景信息就足够了。

Taxonomies extend the controlled vocabularies by adding hierarchichal relations to the concepts and allow the modeling of catgorise and classifications. In order to express even further statements regarding relations and dependencies but also to allow automatic infering of new data and knowledge, o ntologies provide a formal and machine-understandable form of information modeling. In recent years, RDF has become the de facto standard for expressing ontolgies by strictly relying on URIs as identificators of concepts. In that sense, the referent of a concept is not its natural language representation, as in general applied for controlled vocabularies, but a URI modeled as nodes in a so called knowledge graph.
分类法通过向概念添加层次关系扩展了受控词汇表，并允许对范畴和分类进行建模。为了进一步表达关于关系和依赖的陈述，并允许自动推断新的数据和知识，本体提供了正式且机器可理解的建模形式。近年来，RDF 已成为严格依赖 URI 作为概念标识符的事实标准，用于表达本体。在这种情况下，一个概念的含义不是其自然语言表示，如通常在受控词汇表中应用的那样，而是一个作为所谓知识图中的节点建模的 URI。

The IDS expresses its Information Model as an RDF ontology in order to achieve unambigous identifiers and formalized definitions of its concepts and relations. In order to simplify the integration of the IDS ontology, descriptions directly conencted to the respective concepts and links to widely-known concepts of so called upper-level ontologies provide further explanations. As data exchange between different parties is a the core of the IDS, only a fundamental core vocabulary for data descriptions and exchange invokations is requried for all IDS participants. Domain-specific vocabularies may be used wherever necessary to extend the core concepts and to supply more information on provided or requested data.
国际数据空间将其信息模型表达为 RDF 本体，以实现其概念和关系的明确标识和形式化定义。为了简化国际数据空间本体的集成，提供与相应概念直接相连的描述以及链接到所谓上层本体中广泛知名概念的说明。由于数据交换是国际数据空间的核心，因此所有国际数据空间参与者只需要一个基本核心词汇表来描述数据和交换调用。在必要时，可以使用特定领域的词汇表来扩展核心概念，并就提供或请求的数据提供更多信息。

The Industrial Ontology Foundary (IOF) provides a common reference framework for manufacturing-related vocabularies. The thereby de fined terms provide a higher usability in comparision to other vocabulary providers as the IOF vocabulary represents the condensed view of a broad ratio of the manufactoring industry. Additional domain specific vocabularies describe certain industry needs or requirements. Commonly known examples are the Semantic Sensor Network (SSN) or the Sensor, Observation, Sample, and Actuator (SOSA) ontology. Widely used tools for creating and maintaining ontologies are the OWL IDE Protégé, the web-based WebVOWL and VoCol, a reference implementation of the IDS Vocabulary Provider. In addition, other common vocabularies are standardized eCl@ss for product and service related concepts and dictionaries published by RosettaNet.
工业本体基金会（IOF）为制造相关词汇提供了一个共同的参考框架。因此定义的术语与其他词汇提供者相比具有更高的可用性，因为 IOF 词汇代表了制造行业的浓缩视图。此外，一些特定领域的词汇描述了某些行业需求或要求。常见的例子包括语义传感器网络（SSN）或传感器、观测、样本和执行器（SOSA）本体。广泛使用的创建和维护本体工具有 OWL IDE Protégé、基于 Web 的 WebVOWL 和 VoCol，这是 IDS 词汇提供者的参考实现。此外，其他常见的词汇已标准化，如用于产品和服务相关概念的 eCl@ss 以及 RosettaNet 发布的词典。

3.4. App Interfaces  3.4. 应用接口

In the same ways IDS connectors need to supply information on their identity, functionality, and interaction capabilities, IDS Data Apps are equipped with meta information according to the IDS Information Model. These description files provide, among others, details on their intended usage and purpose, their security level but also the applied licensing model. In addition, provider may further describe the Data Apps with vocabularies outside of the IDS core ontology. For instance, domain specific explanations may require further terms and concepts.
在相同的方式下，IDS 连接器需要提供有关其身份、功能以及交互能力的信息，IDS 数据应用根据 IDS 信息模型配备了元信息。这些描述文件提供了其他信息，例如它们的使用目的和用途、安全级别，以及所应用的许可模式。此外，提供商还可以使用 IDS 内核本体之外的词汇表进一步描述数据应用。例如，特定领域的解释可能需要更多的术语和概念。

The description of Data Apps eases the discovery and selection at an IDS App Store. Consequently, the metadata must contain all necessary information to determine the offered value and applicability of the respective apps. Furthermore, the metadata is a fundamental building block for the deployment and composition of several Data Apps at a local IDS Connector. Therefore, all operations have to be defined in terms of input and output parameters, bound protocols and endpoints. Preconditions and postconditions need to be made explicit and effects on the environement must be outlined.
数据应用的描述简化了在 IDS 应用商店中的发现和选择。因此，元数据必须包含所有必要信息，以确定各自应用提供的价值和适用性。此外，元数据是本地 IDS 连接器部署和组合多个数据应用的基本构建块。因此，所有操作都必须以输入和输出参数、绑定协议和端点来定义。需要明确前条件和后条件，并概述对环境的影响。