We present our work in the LifeWatchGreece infrastructure (ESFRI) on providing a conceptual interpretation of biodiversity datasets, with focus on a detailed, comprehensive modelling of the biological observation processes itself and its products. In the complex and heterogeneous biodiversity domain the data providers usually use their own schemata to describe their data which are mainly based on vocabularies of terms (e.g., Darwin Core) that describe the domain of interest through a column-based structure. One of the disadvantages of such a flat structure is that they leave implicit information/associations that characterize the domain entities to the user intuition, hampering the access and retrieval of, not only data, but also knowledge. To face such an issue, we adopted an ontological approach based on the CRM family of semantic models such as CRM-sci and MarineTLO. The first results, through a strong empirical verification via real data, show that these semantic models that offer high-level abstractions through classes and properties: i) capture and enhance the formal representation of Darwin Core records, providing an unambiguous representation of facts that characterize the underlying domain, ii) elicit tacit knowledge and add expressivity and semantic structure to the domain entities, increasing the expressive power and automated access to relevant data of the research process and iii) enable for mechanical integration of factual knowledge of information from other sources (WoRMS, FishBase and SeaLifeBase were considered) successfully, empowering the building of a global knowledge network for the biodiversity domain, for the purpose of supporting the integration of data and models.