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FOAF (an acronym of friend of a friend) is a machine-readable ontology describing persons, their activities and their relations to other people and objects. Anyone can use FOAF to describe themselves. FOAF allows groups of people to describe social networks without the need for a centralised database.
The analysis highlights Deployment, Overview and Example as prominent areas in the source structure around FOAF.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around FOAF shows recurring relationship patterns in the source. For example, FOAF → Although, DeadJournal, Firefox, For, FriendFeed, Identi, Live Journal, MediaWiki, My Opera, Prominent, RSS, Safari, Semantic MediaWiki, Semantic Radar, TypePad, WordPress, Yandex Another extracted example is FOAF → Angela Beesley, He, His, James Wales, Person, RDF, The, Turtle, Wikimedia. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
web rdf people semantic profile relationships ontology friend social owl example support resource profiles name use describe networks vocabulary defining
TTTA extracted 46 structured relationships around FOAF. Examples in this analysis include FOAF → Abbreviation → FOAF and FOAF → Authors → Dan Brickley, Libby Miller. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| FOAF | Abbreviation | FOAF | 1.00 | infobox |
| FOAF | Authors | Dan Brickley, Libby Miller | 1.00 | infobox |
| FOAF | Base standards | RDF, OWL | 1.00 | infobox |
| FOAF | Domain | Semantic Web | 1.00 | infobox |
| FOAF | First published | June 3, 2005; 21 years ago (2005-06-03) | 1.00 | infobox |
| FOAF | Latest version | 0.99 January 14, 2014; 12 years ago (2014-01-14) | 1.00 | infobox |
| FOAF | License | CC BY 1.0 | 1.00 | infobox |
| FOAF | Series | Namespace Document | 1.00 | infobox |
| FOAF | Status | Published | 1.00 | infobox |
| FOAF | Website | xmlns.com/foaf/spec/ | 1.00 | infobox |
| FOAF | Year started | 2000; 26 years ago (2000) | 1.00 | infobox |
| FOAF | is a | descriptive vocabulary expressed using the Resource Description Framework | 0.90 | text |
The concept neighborhoods around FOAF bring nearby vocabulary together. In this analysis, examples include Support, Semantic and Web. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For FOAF, one of the stronger structural bridges in this analysis connects FOAF with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around FOAF to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Deployment, Overview & Example, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — FOAF · EN edition · Analysis: TopicsToTalkAbout