information architecture
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Microformats
The microformats.org community recently celebrated its 5th birthday – five plus years of openly researching, creating, and iterating on web standards to express common semantics designed for humans first, machines second. Originally brainstormed in September 2004 , and rapidly adopted by numerous tools, sites, large and small, the number of pages published with one or more hCards recently crossed the 2 billion mark a few days ago according to Yahoo Search Monkey, making it the most popular format for people or organizations on the web: Search Monkey’s results do tend to fluctuate a few percentage points, even hour by hour, so you may see different numbers, both lower, and over time, higher and higher.
This user interface, and the code behind it, is provided as an example for the benefit of microformat open standards developers, and to demonstrate the clear one to one correspondence between microformat fields and microformat code. The code generated by this interface may be used for semantic web pages, structured blogging, or any other application that requires markup that is simultaneously human presentable and machine readable.
hCard Creator
Nun geht es wieder los mit dem Open Web Podcast: Neues Logo, ein bisschen neue Technik, neuer Livestream und nicht mehr so technisch! Los geht’s!
Der deutsche OpenWeb-Podcast | Der Podcast über offene Standards im Internet
Das Resource Description Framework ( RDF , engl. (sinngemäß) „System zur Beschreibung von Ressourcen“) bezeichnet eine Familie von Standards des World Wide Web Consortiums (W3C) zur formalen Beschreibung von Informationen über Objekte, sogenannte Ressourcen , die durch eindeutige Bezeichner ( URIs ) identifiziert werden. [1] Es ist ursprünglich als Datenmodell zur Beschreibung von Metadaten im World Wide Web (WWW, Web), wie z. B.
Resource Description Framework – Wikipedia
Social media sharing web sites like Flickr allow users to annotate images with free tags, which significantly facilitate Web image search and organization. However, the tags associated with an image generally are in a random order without any importance or relevance information, which limits the effectiveness of these tags in search and other applications. In this paper, we propose a tag ranking scheme, aiming to automatically rank the tags associated with a given image according to their relevance to the image content.