Friend Of A Friend - FOAF
FOAF (an acronym of Friend A Friend) is a machine-readable ontology describing persons, their activities and their relations to other people and objects.
A generic ontology with a focus on online people.
FOAF describes the world using simple ideas inspired by the Web. In FOAF descriptions, there are only various kinds of things and links, which we call properties. The types of the things we talk about in FOAF are called classes. FOAF is therefore defined as a dictionary of terms, each of which is either a class or a property. Other projects alongside FOAF provide other sets of classes and properties, many of which are linked with those defined in FOAF.
Description: this ontology is used to describe people and social relationship on the Web. It is mostly focused on people's existence in the virtual world, with many properties related to online activity or identity: , , , , etc. Nothing about family relations, physical address... It provides similar information on organisations or groups with a similar focus on their existence on the Web ( webpage, etc). It is particularly well suited for describing people on Web-based Social platforms (, twitter, , ...).
Which datasets use it: FOAF is used on many different websites. The list would be too long for this page. Notable examples are: Live Journal, etc. Many computer scientists in the Semantic Web field all over the world are publishing their personal FOAF file.
Tools supporting it: FOAF-a-Matic is a Web-based app which allows the user to create a FOAF file quickly by entering natural language text information in a Web form. The Wiki of the FOAF project has a webpage listing many FOAF-related tools.
Technicalities: FOAF is a rather small ontology (19 classes, 44 object properties, 27 datatype properties). It is not an OWL 2 DL ontology because it relies on inverse functional datatype properties. However, apart from this small issue and minor syntactical issues, the ontology is essentially compatible with OWL 2 RL, which means it is particularly suitable for materialising implicit knowledge about FOAF data in a triple store.