Wednesday, December 16, 2009

RDFa on topquadrant.com

RDFa is the W3C standard for embedding RDF triples in arbitrary XML using attributes. Its most popular use is in HTML, because it makes it easy to add machine-readable versions of a web page's information with minimal new markup.

You could add this markup to just about any web page, but it's especially useful on pages with information that is good for redistribution and can be described with popular vocabularies. We've just added RDFa to our products, management, and contact pages using the FOAF, Dublin Core, vcard, and GoodRelations vocabularies.

GoodRelations is the newest of these vocabularies, and it's getting popular quickly. A recent Semantic Technology Blog posting described a talk at the 2009 Search Engine Strategies conference in which BestBuy's Lead Web Development Engineer described how "GoodRelations + RDFa improved the rank of the respective pages in Google tremendously." In addition to improving page rank when selling products, RDFa makes it easier to share other kinds of information for use by applications on web pages where the data is already present for human consumption, whether it's research data, government data, or airline flight schedules.

An increasing number of tools are available for extracting triples from web pages with embedded RDFa, and the TopBraid Suite has supported this for a while. A TopBraid application can define a particular internet or intranet web page as an RDFa data source so that each time you run the application it will check for the latest set of triples in that page and then incorporate that data with the other data and logic used for that application.

And now, applications like this can pull data about TopQuadrant's products, people, and places from our HTML web pages!

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This is a blog by TopQuadrant, developers of the TopBraid Suite, created to support the pursuit of our ongoing mission - to explode strange semantic myths, to seek out new models that support a new generation of dynamic business applications, to boldly integrate data that no one has integrated before.