A wealth of information has recently become available as browsable RDF data on the Web, but the selection of client applications to interact with this Linked Data remains limited. We show how to browse Linked Data with Fenfire, a Free and Open Source Software RDF browser and editor that employs a graph view and focuses on an engaging and interactive browsing experience. This sets Fenfire apart from previous table- and outline-based Linked Data browsers.
One generic Linked Data browser is Tabulator [
The Fenfire application is a generic RDF browser and editor
with features useful for Linked Data browsing. The user
interface employs the conventional graph representation of
the RDF data model. To make the visualisations scalable
in the number of nodes in the graph and to focus on one
thing at a time, only one central node and its surroundings
are displayed concurrently. It is possible to switch between
two views implemented based on the concept: a simple list
view of objects associated with the focused subject (say, a
container), and the generic graph view from Fentwine [
For the surroundings, the generic graph view shows to the left of the focus all triples that have the focus as an object, and to the right all triples that have the focus as a subject. Each triple is shown as a predicate connecting the subject to the object. This view is applied recursively to each displayed node until, with distance, the graph fades away to the background. If the node has an rdfs:label, it is displayed instead of the URI.
Graph navigation can be done entirely via keyboard by rotating the surrounding nodes around the centre and moving focus to the node immediately to the left or right of the centre. While there is limited space for the surrounding nodes, all nodes can be navigated to via the rotation.
To enable browsing of Linked Data, Fenfire dereferences the URI of the focused node and retrieves any rdfs:seeAlso related to this node whenever instructed to do so. For example, in Figure 1 a user has loaded the FOAF profile of one person, followed a foaf:knows link to another person and retrieved the FOAF profile of this person.
As an important alleviation of incompletely linked data, Fenfire adds triples asserting that the graph retrieved contains information about all of its disconnected components.
We target two audiences primarily: • Semantic Web researchers, application developers and data producers need to explore available data on the level of individual triples. Fenfire provides a convenient alternative to manually downloading graph documents, reading the serialisation formats, and trying to match URIs to discover the links in the data. • People who want to learn about or demonstrate the Semantic Web and what data is available benefit from a visual presentation that truthfully shows the networked nature of the data. Here it is highly advantageous that Linked Data documents that follow the guidelines include an rdfs:label for each node.
Fenfire has its origins in ZigZag [
Fenfire is implemented in the Haskell programming language to achieve high programmer productivity while meeting performance requirements for real-time animation and for browsing large graphs. It uses the Raptor library of the Redland project for RDF parsing, the GTK library for the standard graphical user interface elements and the Cairo library for the animated, vector-graphics based visualisations. A major part of the architecture is the key-frame and identitybased visualisation and animation system that provides the user continuous feedback on how the navigation and the switching between alternative views change what is visible.
We applied Fenfire to the task of browsing Linked Data with a graph view and highlighted the use cases of exploring, learning about and demonstrating Semantic Web data. Some Linked Data browsers can edit the data as well. Fenfire can edit RDF graphs, but we need to implement remote publishing interfaces in addition to the current feature of saving to local files.
Information display and navigation can be enhanced if there is knowledge about the user interaction requirements for a specific domain. Thus, Fenfire should have some automatic ontology-awareness and more should be configurable with settings and plug-ins.
The implementation of Fenfire in Haskell was initially developed by Benja Fallenstein and Tuukka Hastrup.