Understanding the major societal challenges in the field of environment requires multidisciplinary approaches, which in the case of the biosphere requires the integration of information and knowledge of the various components, including the atmospheric, marine and terrestrial environment. Examples of these challenges include biodiversity loss, climate change and its effects on biodiversity, invasive species, land-use change and habitat fragmentation.
Scientific research in this field needs to be supported by a research infrastructure with sufficient analytical capacity, persistence and scalable structure, capable of encompassing the different thematic (e.g. taxonomic, functional and phylogenetic), spatial and temporal scales of the hypotheses tested.
Species occurrence and abundance data, an essential component of this analytical capacity, are derived from observations and sampling of biodiversity made in the wild. Data, often resident in natural history collections or databases of scientific projects, environmental impact studies or biodiversity monitoring, document where, when, under which ecological or habitat conditions biological species have been observed or collected. They also indicate who observed or collected them, and who identified these species. In this way, the provenance of the data, which ensures the rigorous scientific use of the information, is exhaustively recorded.
PORBIOTA promotes access and scientific use of primary biodiversity data through cataloguing and digitization from analogue supports. It also facilitates standardization and publication from institutional databases, scientific projects or citizen science initiatives. Data is published and accessed through the Global Biodiversity Information Facility (GBIF), the largest global biodiversity data network, adopting best practices, tools, protocols and quality control mechanisms.
The Portuguese Node of GBIF platform integrates with Global Biodiversity Information Facility (GBIF), adopting best practices, tools, protocols, and quality control mechanisms, which combining information from natural history collections, observations (including citizen science) and sampling programs.