Towards a pattern science for the Semantic Web

With the the web of data, the semantic web can be an empirical science. Two problems have to be dealt with. The knowledge soup problem is about semantic heterogeneity, and can be considered a difficult technical issue, which needs appropriate transformation and inferential pipelines that can help making sense of the different knowledge contexts. The knowledge boundary problem is at the core of empirical investigation over the semantic web: what are the meaningful units that constitute the research objects for the semantic web? This question touches many aspects of semantic web studies: data, schemata, representation and reasoning, interaction, linguistic grounding, etc.