ImageSnippets is an image based, data-centric platform that links machine-readable descriptions to images, using cutting-edge Semantic Web and Linked Data technology and standards.

Once created, these descriptions have many uses: apps can do more meaningful searching for images in an image corpus; your described images can be found on the Web in powerful new ways, and seamlessly incorporated into other linked data tools; and your image and copyright information can be held secure on protected servers, safe from metadata stripping in social media. But first you have to create it, which has been a problem. ImageSnippets makes this easy.

ImageSnippets(tm) is a new kind of digital asset management system built on principles from the semantic web. We are a group of designers, cognitive scientists, programmers, and image makers interested in taking image management to a whole new level.

The lightweight image ontology (LIO) used by Imagenippets was designed by Patrick Hayes and Margaret Warren and is open and freely usable and more can be found about it at: http://lov.okfn.org/dataset/lov/vocabs/lio

The ImageSnippets dataset/triple-store of image data can found here: /dataset/ and can also be found by searching for ImageSnippets in the Google Dataset search: https://toolbox.google.com/datasetsearch

How does ImageSnippets work?

 Semantic technology links data using RDF :

• A subject, a property, and an object

• The subject of the image can either be the image or a region in the image.

• The property describes how the keyword relates to the image, such as: “depicts” or “looks like”.

• The object is like a normal keyword phrase or tag, such as: “Windows”, “Silhouette”, “New Orleans”, etc.

• You can add as much or as little metadata as you want to an image.

We are currently working on image galleries based on metadata added through ImageSnippets using our newly developed Word Press plug-in. Example galleries coming soon! Stay tuned!