元数据是关于数据的数据。
Metadata literally means data about data.
元数据即关于数据的数据。
Metadata, simply put, is data about data.
简单地说，元数据就是关于数据的数据。
Metadata literally means "data about data" and that's exactly what it is.
metadata照字面上地意谓“关于数据的数据”，而且那完全地是它是什么。
The most common definition of metadata is data about data -- which doesn't really say much.
最常见的元数据定义是关于数据的数据——其实并不然。
Metadata, often referred to as data about data, is information about another piece of information.
元数据通常又被称为有关数据的数据，它指的是有关另外一条信息的信息。
Metadata strategy identifies the type and structure of metadata, also known as "data about data" (or content).
元数据策略，定义元数据的结构，也称作“关于数据的数据”(或是内容)。
Absrtact: Metadata is "the data about data", it's the information that is used to describe resources' properties.
摘要：元数据是“关于数据的数据”，是用来描述资源属性的信息。
Use Import Export Manager to bring metadata about data files, data tables, business terms, reports, and models into Workbench.
使用ImportExportManager把关于数据文件、数据表、业务术语、报告和模型的元数据导入到Workbench中。
Metadata can be thought of as "data about data". Any aspect of the file content holding users 'interests can be used as metadata.
元数据是对数据的再描述，使用户感兴趣的有关文件内容的任何方面都可以作为文件的元数据。
Metadata, the data about data, which describe every document in Digital Library, is a important tool to manage, retrieve data and to interoperate among Digital Libraries.
元数据是关于数据的数据，数字图书馆中，每个数据文档由其元数据描述，元数据是数字图书馆管理、检索数据以及在各个层面上实现互操作的重要手段。
Meta data Management is the process for managing information needed to promote data legibility, use and administration. Contents are described in terms of data about data, activity and knowledge.
元数据管理是提供数据可理解、使用和管理的管理信息的过程。主要用来记录数据、行为和知识。
Some developers insist that attribute information should be metadata, namely information about the data, and not the data itself.
一些开发者坚持认为属性信息应该是元数据，即关于数据的信息，而不是数据本身。
These commands run algorithms on the data or query for information about the data.
这些命令对数据运行算法，或查询有关该数据的信息。
是一个关于你的数据的数据集。
Data — Often, message data, information about application flow, and test data might also be placed in the application context.
数据——通常，消息数据、关于应用程序流的信息和测试数据也可能放置在应用程序上下文中。
Instead, data binding is simply about — well — data.
相反，数据绑定仅仅和“数据”有关。
The content of a data page is both the data and information about the data on the page (sometimes called metadata).
数据页面的内容包括页面上的数据和有关页面上数据的信息(有时称为元数据)。
The data object also holds references to metadata that provides information about the data included in the data object.
数据对象还存放对元数据的引用，元数据提供有关包含在数据对象中的数据的信息。
Although the chapter title says it's about data crunching, we store our masses of data in relational databases.
尽管此章节的标题是关于数据咀嚼，但是我们将大量数据存储在关系数据库中。
Although data protection provides the ability to regenerate data on a failure, it says nothing about the validity of the data in the first place.
虽然数据保护提供了在故障时重新生成数据的能力，但是这并不涉及处于第一位的数据的有效性。
You'll learn more about the operational data and the data warehouse design shortly.
稍后您将了解更多关于操作型数据和数据仓库设计的信息。
Once the RSS data has been stored, I then add data about the context URI into the store.
一旦存储了RSS数据，我随后就将有关上下文uri的数据添加到存储中。
Then, at runtime, you work more with the data as business data, and can forget about the XML.
然后，在运行时，将数据更多地作为业务数据来使用，可以不用考虑X ML了。
Otherwise they're not: data is data, services are about behavior atop line of business data.
否则，它们就不是——数据就是数据，而服务是业务数据之上的行为。
XMI allows data about the structure of other data to be passed.
XMI允许传递与其它数据结构有关的数据。
Each document also contains metadata (data about the data), such as a unique document ID and revision Numbers.
每个文档还可以包含元数据(关于数据的数据)，比如惟一的文档id和修改号。
Throughout the series, you discover how to manage and organize data and content, learn about distributed data mining, and find tips for analyzing and presenting information to users.
在本系列中，您将了解如何管理和组织数据与内容，了解分布式数据挖掘并学习分析信息并向用户呈现的一些技巧。
Every place will tell a story it could not before, without a nose to find the data about it and a data base to store it and a mind to process it.
每一处地方都会讲述自身的故事，而在之前是无法办到的，因为之前没有搜寻数据的鼻子和存储这些数据的数据库以及对其进行处理的大脑。
The technique of data normalization is about correct ways of partitioning the data among tables to minimize data redundancy and maximize the speed of retrieval.
数据正规化技术是为将数据正确地保存再各个标准，从而使数据冗余达到最小，存取速度达到最高。
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