Visualising and easing the interpretation of semantic web data is now one of the largest challenges facing the Semantic Web community. The growth of the Web of Linked Data has shifted research from being primarily focused on producing semantic web data to consuming it, not only are we beginning to eat our own dog food, we are starting to offer it to others outside of the community to taste and adapt to their needs. Mainstream adoption is, however, still limited by a lack of understanding of the Semantic Web Technology stack. Questions like ‘What makes the Semantic Web different from the World Wide Web?’, ‘What is an ontology?’ and ‘What is semantic metadata?’ are commonplace when presenting non-semantic web savvy users with semantic data. Work is required that allows lay-users to consume and interact with semantic web data without a deep knowledge of the intricacies of the Semantic Web stack. In providing such approaches reuse and consumption of semantic web data will be achieved in areas such as education, social awareness and governmental transparency, all areas where data is currently available and encoded as Linked Data and/or using other semantic representations.
We invite submissions that illustrate interactive visualisation of semantic web data, to support activities such as exploratory knowledge discovery and browsing of linked data, in order to aid understanding of the very large amounts of highly interlinked, high-dimensional data, and therefore demonstrate the power and utility of the semantic web.
The volume of semantic web data now available and the rate at which it is being produced also provide challenges to data consumers and semantic web developers. Without performing a depth-first exploration of a given dataset it is hard to know what the dataset may contain, its size, its attributes or whether it is useful for what a given consumer needs. Analytics, supported by interactive visualisation, plays a vital role in this situation by generating overviews and improving the interpretation of statistical analysis that describes dataset properties. Such an approach provides consumers with abstract or high-level descriptions of what is available and helps to point to what could be useful to carrying out their tasks successfully.
We solicit work that illustrates the application of visual analytics to semantic web data,. Examples include graph summarisation, network-based analytics and plot layouts that provide density and connectivity assessments, used in co-ordination with other visual analytics techniques that highlight specific attributes, such as time and location.
Ontologies form a vital component of the Semantic Web, allowing community-specific terms and colloquial use of language to be expressed using commonly agreed formal terms or concepts. Ontologies further ease the definition of the (often multiple) relationships between concepts. Despite such formal constructs, presenting ontological concepts and their relations in a coherent and legible form still remains a challenge. While support for formal knowledge representation is available for technical audiences it is unclear if we are close to an agreed community-standard or practice for such presentation to other end users? How should the presentation be adapted given the audience (technical or lay) in order to convey the value of its information content to them?
We invite submissions that provide novel and innovative ways to visualise ontologies, concept hierarchies and the dependencies between distributed ontologies, and contrast existing ontology visualisation approaches.
Submissions should be suitable for a highly ranked archival journal (IJSWIS is among the top journals in WWW).
We invite submissions covering the following topics: