Purpose: – Marine species data are scattered across a series of heterogeneous repositories and information systems. There is no repository that can claim to have all marine species data. Moreover, information on marine species are made available through different formats and protocols. The purpose of this paper is to provide models and methods that allow integrating such information either for publishing it, browsing it or querying it. Aiming at providing a valid and reliable knowledge ground for enabling semantic interoperability of marine species data, in this paper the authors motivate a top level ontology, called MarineTLO and discuss its use for creating MarineTLO-based warehouses. Design/methodology/approach: – In this paper the authors introduce a set of motivating scenarios that highlight the need of having a top level ontology. Afterwards the authors describe the main data sources (Fisheries Linked Open Data, ECOSCOPE, WoRMS, FishBase and DBpedia) that will be used as a basis for constructing the MarineTLO. Findings: – The paper discusses about the exploitation of MarineTLO for the construction of a warehouse. Furthermore a series of uses of the MarineTLO-based warehouse is being reported. Originality/value: – In this paper the authors described the design of a top level ontology for the marine domain able to satisfy the need for maintaining integrated sets of facts about marine species and thus assisting ongoing research on biodiversity. Apart from the ontology the authors also elaborated with the mappings that are required for building integrated warehouses.

The ability to compute the differences that exist between two RDF/S Knowledge Bases (KB) is an important step to cope with the evolving nature of the Semantic Web (SW). In particular, RDF/S deltas can be employed to reduce the amount of data that need to be exchanged and managed over the network in order to build SW synchronization and versioning services. By considering deltas as sets of change operations, in this article we introduce various RDF/S differential functions which take into account inferred knowledge from an RDF/S knowledge base. We first study their correctness in transforming a source to a target RDF/S knowledge base in conjunction with the semantics of the employed change operations (i.e., with or without side-effects on inferred knowledge). Then we formally analyze desired properties of RDF/S deltas such as size minimality, semantic identity, redundancy elimination, reversibility, and composability, as well as identify those RDF/S differential functions that satisfy them. Subsequently, we experimentally evaluate the computing time and size of the produced deltas over real and synthetic RDF/S knowledge bases.