Generator

aTags ("associative tags") are snippets of HTML that capture the information that is most important to you in a machine-readable, interlinked format, making it easier for you and others to see the big picture.

Get the Paper: “Simple, ontology-based representation of biomedical statements through fine-granular entity tagging and new web standards” Matthias Samwald and Holger Stenzhorn. Bio-Ontologies 2009.
Article PDF, Presentation PDF.

aTag Generator Bookmarklet

With this bookmarklet you can create aTags for any kind of content on the web. To use it:

Drag the aTag this bookmarklet to your bookmarks bar. (You might need to enable the bookmarks bar in your browser first.) Clicking this bookmarklet executes the standard aTag generator, including an auto-completion feature based on DBpedia.
There are also alternative, experimental versions of the generator, based on NCBO BioPortal services:
The aTag this (NIFSTD) bookmarklet makes use of the Neuroinformatics Framework ontology.
The aTag this (NCI Thesaurus) bookmarklet makes use of the National Cancer Institute Thesaurus.
When you are at a webpage that contains a snippet of text that you want to capture with an aTag, select the snippet of text, then click on the aTag bookmarklet in your bookmarks bar.
A pop-up window will appear, containing the snippet of text you selected. Add tags to this snippet of text by typing in the box below it. Matching terms will be suggested as you type. Tag recommendation is currently based on DBpedia. If no suitable term already exists, you can choose to create a new term.
When you are finished, click on 'Generate aTag'.
You can copy and paste the generated aTag into your HTML-based application (such as a Wordpress blog, content management system, e-mail). The aTags on the web will be found by RDF-enabled search engines.
If you are an RDF/OWL enthusiast, you can also visualize the RDF in the aTag you created with the RDFa highlight bookmarklet you can find here.

Technical Background

aTags are based on Semantic Web standards and Linked Data practices. Specifically, they make use of RDFa, the SIOC vocabulary and various domain ontologies and taxonomies that are available in RDF/OWL format. The autocomplete functionality is based on Apache Solr.