What is semantic markup, and why would I want to u

问题:

Like it says.

回答1:

Using semantic markup means that the (X)HTML code you use in a page contains metadata describing its purpose -- for example, an <h2> that contains an employee's name might be marked class="employee-name". Originally there were some people that hoped search engines would use this information, but as the web has evolved semantic markup has been mostly used for providing hooks for CSS.

With CSS and semantic markup, you can keep the visual design of the page separate from the markup. This results in bandwidth savings, because the design only has to be downloaded once, and easier modification of the design because it's not mixed in to the markup.

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Another point is that the elements used should have a logical relationship to the data contained within them. For example, tables should be used for tabular data, <p> should be used for textual paragraphs, <ul> should be used for unordered lists, etc. This is in contrast to early web designs, which often used tables for everything.

回答2:

Semantics literally means using "meaningful" language; in Web Development, this basically means using tags and identifiers which describe the content.

For example, applying IDs such as #Navigation, #Header and #Content to your <div> tags, rather than #Left, and #Main, or using unordered lists for a list of navigational links, rather than a table.

The main benefits are in future maintenance; you can easily change the layout or the presentation without losing the meaning of your content. You navigation bar can move from the left to the right, or your links displayed horizontally rather than vertically, without losing the meaning.

回答3:

From http://www.digital-web.com/articles/writing_semantic_markup/ :

semantic markup is markup that is descriptive enough to allow us and the machines we program to recognize it and make decisions about it. In other words, markup means something when we can identify it and do useful things with it. In this way, semantic markup becomes more than merely descriptive. It becomes a brilliant mechanism that allows both humans and machines to “understand” the same information.

回答4:

Besides the already mentioned goal of allowing software to 'understand' the data, there are more practical applications in using it to translate between ontologies, or for mapping between dis-similar representations of data - without having to translate or standardize the data (which can result in a loss of information, and typically prevents you from improving your understanding in the future).

There were at least 2 sessions at OSCon this year related to the use of semantic technologies. One was on BigData (slides are available here: http://en.oreilly.com/oscon2008/public/schedule/proceedings, the other was the guys from FreeBase.

BigData was using it to map between two dis-similar data models (including the use of query languages which were specifically created for working with semantic data sets). FreeBase is mapping between different data sets and then performing further analysis to derive meaning across those data sets.

Related topics to look into: OWL, OQL, SPARQL, Franz (AllegroGraph, RacerPRO and TopBraid).

回答5:

Here is an example of a HTML5, semantically tagged website that I've been working on that uses the recently accepted Micro-formats as specified at http://schema.org along with the new more semantic tagging elements of HTML5.

http://blog-to-book.com/view/stuff/about/semantic%20web

Googles has a handy Semantic tagging test tool that will show you how adding semantic tags to content enables search engines to 'understand' far more about your web pages.

Here is the test tool: http://www.google.com/webmasters/tools/richsnippets?url=http%3A%2F%2Fblog-to-book.com%2Fview%2Fstuff%2Fabout%2Fsemantic+web&view=

Notice how google now knows that the 'things' on the page are books, and they have an isbn13 identifier. Adding additional metadata, such as price and author enables further inferences to be made.

Hope this points you in some interesting directions. More detailed semantic tagging can be achieved using the Good Relations Ontology which is pretty much the most comprehensive I can think of right now.