Supporting citizen science and biodiversity informatics on the semantic web

A question faced by semantic web developers is how much and what form of explicit semantics to encode in domain ontologies. A typical answer to this question is that it depends on the use case. This suggests the question Can we create ontologies that support multiple use cases, in situations where those use cases have conflicting ontology-design requirements? We present an approach to building ontologies by layer, and results that suggest that, at least in the domains of citizen science and biodiversity informatics, the answer to that question is yes. The layers that we develop correspond to patterns in the RDF graph. This contrasts with typical approaches to modular ontology development, where the layers are domain based. The three primary motivations for this approach are i) preserving computational tractability; ii) enabling easy coupling and decoupling with foundational ontologies and iii) maintaining cognitive tractability. This third motivation is still under-studied in semantic web development; we consider it in relation to reducing the ease with which ontology users can publish data that accidentally implies things that they do not mean. This is important always, but becomes especially so in citizen science, where users will naturally bring intuitive semantics to the terms that they encounter. We describe case studies that involved deploying our approach in the context of citizen science events, and which provided opportunities to assess its capabilities and limitations. We also describe subsequent work aimed at addressing these limitations, and, by applying newly defined layers over the underlying data, show that we are able to improve the competency of our knowledge base. More generally, we show that appropriately combining triple-pattern-based layers allows us to support a wide variety of use cases with varied (and occasionally conflicting) requirements. In addition to our approach to semantic layering, contributions include a better understanding of how to fuse social and semantic computing to support citizen science, and, specifically, a collection of semantic layers for representing biodiversity information in RDF, demonstrated to support a variety of citizen science use cases, with a focus on those that involve invasive species. Unlike other proposed "semanticizations" of the Darwin Core standard for representing biodiversity occurrence data, these layers involve minimal modification to the current Darwin Core vocabulary, and make maximal use of the Darwin Core namespace. Therefore, they significantly simplify the transitioning of current practices onto the semantic web.