User Interaction with the Semantic Web, Challenges and Opportunities

It can be argued that although the semantic web has been devised for automated environments (machine based), eventually humans are its final intended consumers, at least from one possible viewpoint.

A critical aspect of Semantic Web user interfaces is that they are capable of making all the richness of the underlying data model available at the interaction level. An important aspect of those tools should be that constraints at the interaction level should be minimized as much as possible.

Therefore, the interfaces built to drive user interaction should be flexible enough to offer to users as many as possible ways to interact with the data they can conceive. This flexibility should not be at the expense of users’ cognitive load.

The adoption of Semantic Web technologies implies new challenges for user interaction beyond those already posed by Web technologies and interactive systems in general. It's important that those new challenges be identified and considered. A preliminary distinctive list of challenges to Semantic Web Interfaces is identified below:

• SW technologies provide a new set of innovative functionalities, which require equally innovative interfaces to be enjoyed

• Interfaces are required for datasets of which the schemas are not yet fully known at design time

• Interfaces are required for datasets that are under (quality) control of organisations other than that of the user of the SI

• Interfaces are required for evolving heterogenous datasets, often with many conflicting versions of datasets of same provenance.

• Interfaces for applications with purposes and goals diverging from those of the original datasets.

• UIs for datasets where there is as much information in the links between the resources as in the resources themselves.

• Interfaces need to be able to deal with different levels of granularity of data and information.

• UIs for information that is automatically derived from potentially incomplete and imperfect data.

• Control over data/information delivery, due to size and complexity of data sources.