帮助:介绍SMW

Semantic MediaWiki (SMW) is an extension of MediaWiki – the wiki application best known for powering Wikipedia – that helps to search, organise, tag, browse, evaluate, and share the wiki's content. While traditional wikis contain only text which computers can neither understand nor evaluate, SMW adds semantic annotations that allow a wiki to function as a collaborative database. Semantic MediaWiki was first released in 2005, and currently has over ten developers, and is in use on hundreds of sites. In addition, a large number of related extensions have been created that extend the ability to edit, display and browse through the data stored by SMW: the term "Semantic MediaWiki" is sometimes used to refer to this entire family of extensions.

语义维基是MediaWiki的一款扩展。维基百科就是MediaWiki所驱动，SMW可以帮助用于搜索、组织、标记、浏览、评估 和 分析维基内容。然而传统的维基包含的文本，计算机无法评估和理解它。SMW添加了语义注释允许将一个维基起到协作数据库的作用。SMW最初发布与2005年，且现在有超过十名开发人员，并有上百个网站使用它。此外还有众多关联的扩展被创建用于扩充编辑、显示 和 浏览 被SMW存储的数据。SMW有时是也被用于指代SMW扩展家族。

Why Semantic MediaWiki? 为什么用SMW

Wikis are a great tool for collecting and sharing knowledge in communities and organizations. This knowledge is mostly contained within texts and multimedia files, and is thus easily accessible for human readers. But though wikis are very good for storing and retrieving individual facts, they are less useful for getting queried or aggregated information. As a simple example, let's say you use a wiki that stores information about projects related to your organization. You have the following simple question: 维基是一个在组织和社群中收集分享知识的好工具。这些知识通常包含在文字和多媒体文件中，而因此容易被人类读者浏览。但尽管维基可以很好的存储 和 检索单个事实，但他们信息查询 和 整合方面 并不好用。举个例子：假如你在使用一个存储着与你组织相关计划的维基，你想查询下面这个简单的问题：

"What are the active projects that were started in 2012?" “哪一个活跃的计划是在2012年开始的？”

This should be an easy question to answer, but in fact it's not - you would have to read through all of the pages about projects every time you wanted to answer the question. Text searches won't necessarily help. Categories could help to some extent, although they're not an ideal tool and maintaining them can become complex (see below). And there doesn't exist an artificial intelligence tool that could help with this task either.

这个问题的答案应该很好回答。但事实上不是。你想回答这个问题得每一次都都阅读一边所有的计划页面。文本搜索没有起到重要的作用。分类可以在某些程度上起作用，但是这不是一个理想的工具，而且维护起来会非常复杂（见下）。还有的是不存在人工智能来帮助你。

Semantic MediaWiki enables wikis to make their knowledge computer-processable, so that you can find and display the answer to this question - and to many more.

SMW能让维基知识库可以被计算机处理，所以你可以找到这个问题的答案，还可以做得更多。

Where SMW can help SMW可以帮到什么

Semantic MediaWiki introduces some additional markup into the wiki-text which allows users to add "semantic annotations" to the wiki. While this at first appears to make things more complex, it can also greatly simplify the structure of the wiki, help users to find more information in less time, and improve the overall quality and consistency of the wiki. Here are some of the benefits of using SMW:

SMW在维基文本之中额外引入了某些标记，从而让用户能够为维基添加"语义标注"。一开始，这似乎让事情更加复杂了，但其却大大简化了维基的结构，有助于用户更快地找到更多的信息，并且改善了维基的总体质量和一致性。以下是使用SMW的一些好处：

• Automatically-generated lists. 自动生成列表

Lists and tables are a natural way to view information at a glance. In some cases, non-semantic wikis contain human-generated lists; Wikipedia itself has thousands, like "List of metropolitan areas in Spain". These lists are prone to errors, since they have to be updated manually. Furthermore, the number of potentially interesting lists is huge, and it is impossible to provide all of them in acceptable quality. In SMW, lists are generated automatically. They are always up-to-date and can easily be customised to obtain further information.

• Visual display of information. 显示可视化信息

The various display formats defined by additional extensions, such as Extension "Semantic Result Formats" and Maps (formerly Semantic Maps), allow for displaying of information in calendars, timelines, graphs and maps, among others, providing a much richer view of the data than simple lists and tables would.

• Improved data structure. 改善数据架构

MediaWiki wikis tend to make heavy use of categories for structuring data. While these are generally helpful, consider the category on Wikipedia called "1620s births"; if the information in these pages were stored using SMW, these categories could be replaced by simple semantic values, reducing the need for a complex classification system. In addition, if semantic markup within the wiki is stored within templates, otherwise known as semantic templates, a wiki can easily gain a solid data structure. And the Page Forms (formerly Semantic Forms) extension lets administrators create forms for adding and editing the data within semantic templates, thus making the addition of semantic information even easier and more straightforward than using regular wiki text.

• Searching information. 信息搜寻

Individual users can search for specific information by creating their own queries, supported via extensions like Extension "Semantic Drilldown" and Page Forms (formerly Semantic Forms).

• External reuse. 外部使用

Data, once it is created in an SMW wiki, does not have to remain within the wiki; it can easily be exported via formats like CSV and JSON. This enables an SMW wiki to serve as a data source for other applications, or, in the case of enterprise usages, to take over the role that a relational database would normally play. Through the use of the Extension "External Data" extension, SPARQL, and other tools, one SMW-based wiki can even use the data from another, eliminating the need for redundancy between wikis. You can also query SMW's data from outside the wiki, via the API or an RDF triplestore.

• Integrate and mash-up data. 整合混搭数据

Data contained in an SMW installation does not have to be an isolated store of information. Extensions such as Extension "Data Transfer" and Extension "External Data" empower you to integrate external data (coming e.g. from legacy systems, web services or linked data sources) and interrelate it with existing semantic data in the wiki. Thus, an SMW-powered wiki can serve as a central information hub in an IT landscape.