RDF Visualizer is a generic browsing mechanism that gives the user a flexible, highly configurable, detailed overview of a dataset/database encoded in RDF. It is designed and developed to overcome the drawbacks of the existing RDF data visualization methods/tools with an innovative point of view. It allows users with neither previous knowledge of the data structure nor SPARQL skills to navigate and explore the data starting from an element of interest and incrementally explore further the source. The tool is currently used in several national and EU funded research projects such as HELLAS-CH and PARTHENOS and has been tested with large datasets from the British Museum and the American Art Collaborative project.
The tool has been designed and implemented to represent RDF data as an indented list, to handle the density and depth of information starting from a specified RDF resource (URI) and generating a dynamically expandable tree structure. In order to achieve this, all incoming and outgoing links are transformed and presented as nodes of every class/instance in a schema agnostic way. Users are able to configure the display of schema-dependent information according to their preferences by editing a configuration file. They are also able to define priority-based rule chains that are used to define schema-dependent style and order of properties that are inherited to subclasses and sub properties by editing an xml file. For anything not covered by a rule, default options are applied based on experience and best practices. User interface of the tool has been designed in cooperation with potential users, focusing on usability and readability. Moreover, rich functions are provided to control the display of data items, such as, identifying same instances, expanding collapsing big texts or big sets of results, displaying images and image galleries, removing or replacing prefixes, selecting non displayed URIs and displaying the subject’s URI on label hover. With right click user can focus on a specific URI, open it as root in new tab, copy it on clipboard or retrieve the path of its sub-graph.
The innovative features that led us to develop this tool are the following: • Display data of any schema • Display all nodes of any class / instance • Apply configuration rules to known classes and properties to improve layout and readability • Display information of high density in one screen • Transforms an RDF graph into an indented list by inverting incoming links
The architecture of tool is presented in figure below. The arrows depict the data flow between the two basic system components. The first is the core API that consists of micro services that are divided in three levels. The tool is able to parse RDF data either from triple stores–graph databases (e.g. virtuoso, blazegraph) using Triple Store Manager or from raw .ttl files using RDF File Manager. The tool considers user’s choices to prioritize subject’s properties from an xml file with X3MLProperty Reader. It constructs SPARQL queries using SPARQL Query Builder and executes them with Query Executor. The output of these functions is fed as input to Prioritizer and Sorter producing a Map <Triple, List<Triple>> considering user’s choices from two configuration files (properites.xml and config.properties).
The second component is the Web Application that transform this Map into JSON format and projects data in a readable and interactive tree structure on a web browser. Each node is represented by its label and type. Initially, the tool creates a tree that has as subject (root) the given URI and as leaves its direct properties and objects. If an object is by its own a subject (having properties and objects), there is an expand icon on the right. On click, the above same process runs recursively transforming the object into subject creating dynamically its own sub tree of properties and objects. So with this incremental exploration the tool is remarkably lightweight and lets users guide their exploration.
RDF Visualiser has been integrated in the 3M interface of the X3ML suite of tools for data mapping and transformation. It enhances 3M with an important validation tool for transformed data. Domain experts can easily check and correct their mapping and transformations on the fly resulting, enabling an iterative and collaborative evaluation of the resultant RDF.
A fully working demo representing a well formed example is running here. A step-by-step explanation can be found in this document.
A richer use case showing different datasets from diverse sources to demonstrate the ability of the tool to visualize heterogeneous data in a generic way can be found here. In this demo are available four different datasets from:
giving examples of Culture Heritage field and biology data focusing on DNA sequences.
For more information contact Maria Theodoridou
