The service model of the Global Biodiversity Information Facility (GBIF) is being implemented in an increasing number of national biodiversity (BD) data services. While GBIF already shares >109 data points, national initiatives are an essential component: increase in GBIF-mediated data relies on national data mobilisation and GBIF is not optimised to support local use. The Finnish Biodiversity Information Facility (FinBIF), initiated in 2012 and operational since late 2016, is one of the more recent examples of national BD research infrastructures (RIs) – and arguably among the most comprehensive. Here, we describe FinBIF's development and service integration, and provide a model approach for the construction of all-inclusive national BD RIs. FinBIF integrates a wide array of BD RI approaches under the same umbrella. These include large-scale and multi-technology digitisation of natural history collections; building a national DNA barcode reference library and linking it to species occurrence data; citizen science platforms enabling recording, managing and sharing of observation data; management and sharing of restricted data among authorities; community-driven species identification support; an e-learning environment for species identification; and IUCN Red Listing (Fig. 1). FinBIF's aims are to accelerate digitisation, mobilisation, and distribution of biodiversity data and to boost their use in research and education, environmental administration, and the private sector. The core functionalities of FinBIF were built in a 3.5-year project (01/2015–06/2018) by a consortium of four university-based natural history collection facilities led by the Finnish Museum of Natural History Luomus. Close to 30% of the total funding was granted through the Finnish Research Infrastructures programme (FIRI) governed by the national research council and based on scientific excellence. Government funds for productivity enhancement in state administration covered c.40 % of the development and the rest was self-financed by the ...
The service model of the Global Biodiversity Information Facility (GBIF) is being implemented in an increasing number of national biodiversity (BD) data services. While GBIF already shares >109 data points, national initiatives are an essential component: increase in GBIF-mediated data relies on national data mobilisation and GBIF is not optimised to support local use. The Finnish Biodiversity Information Facility (FinBIF), initiated in 2012 and operational since late 2016, is one of the more recent examples of national BD research infrastructures (RIs) – and arguably among the most comprehensive. Here, we describe FinBIF's development and service integration, and provide a model approach for the construction of all-inclusive national BD RIs. FinBIF integrates a wide array of BD RI approaches under the same umbrella. These include large-scale and multi-technology digitisation of natural history collections; building a national DNA barcode reference library and linking it to species occurrence data; citizen science platforms enabling recording, managing and sharing of observation data; management and sharing of restricted data among authorities; community-driven species identification support; an e-learning environment for species identification; and IUCN Red Listing (Fig. 1). FinBIF's aims are to accelerate digitisation, mobilisation, and distribution of biodiversity data and to boost their use in research and education, environmental administration, and the private sector. The core functionalities of FinBIF were built in a 3.5-year project (01/2015–06/2018) by a consortium of four university-based natural history collection facilities led by the Finnish Museum of Natural History Luomus. Close to 30% of the total funding was granted through the Finnish Research Infrastructures programme (FIRI) governed by the national research council and based on scientific excellence. Government funds for productivity enhancement in state administration covered c.40 % of the development and the rest was self-financed by the implementing consortium of organisations that have both a research and an education mission. The cross-sectoral scope of FinBIF has led to rapid uptake and a broad user base of its functionalities and services. Not only researchers but also administrative authorities, various enterprises and a large number of private citizens show a significant interest in the RI (Table 1). FinBIF is now in its second construction cycle (2019–2022), funded through the FIRI programme and, thus, focused on researcher services. The work programme includes integration of tools for data management in ecological restoration and e-Lab tools for spatial analyses, morphometric analysis of 3D images, species identification from sound recordings, and metagenomics analyses.
The Finnish Biodiversity Information Facility FinBIF receives, stores and manages biodiversity data mobilised in Finland, and shares the data through its own portal (species.fi) and through Global Biodiversity Information Facility GBIF. FinBIF's data policy (data policy) embraces the European FAIR data principles (FAIR - Findable, Accessible, Interoperable, Reusable; Wilkinson (2016)) but also incorporates specific restrictions stemming from national legislation, researchers' needs, and data owners' requirements. Here, we describe how the necessary, due to various reasons from sensitivity of the data to research embargo, restrictions to openness have been defined and implemented on the policy level and in technical data infrastructure solutions. We hope to contribute to an improvement of data management in the international biodiversity data infrastructures. In Finland, the law prohibits public authorities from distributing occurrence data if this causes increased threat to endangered species. However, neither the definition of 'endangered species' nor guidelines for the evaluation of potential risk by openness of data are formulated. To enable mobilisation of datasets containing information on endangered species, FinBIF convened a task force commissioned to set rules on data distribution, which respect the spirit of the law. The task force consisted of representatives of relevant data holding authorities and it consulted a wide group of taxon experts and the species information community. First, a list of species, judged to be among those targeted by the spirit of the law, was created (sensitive species data). Then the rules of restriction were decided on for each of the species. Measures of restriction ranged from complete non-disclosure of data to temporal and spatial restrictions. The identified safeguards concerning the sensitive data management in all use cases led us to create a series of innovative solutions Researchers often wish to restrict the openness of data they have gathered for research purposes ...
The Finnish Biodiversity Information Facility FinBIF receives, stores and manages biodiversity data mobilised in Finland, and shares the data through its own portal (species.fi) and through Global Biodiversity Information Facility GBIF. FinBIF's data policy (data policy) embraces the European FAIR data principles (FAIR - Findable, Accessible, Interoperable, Reusable; Wilkinson (2016)) but also incorporates specific restrictions stemming from national legislation, researchers' needs, and data owners' requirements. Here, we describe how the necessary, due to various reasons from sensitivity of the data to research embargo, restrictions to openness have been defined and implemented on the policy level and in technical data infrastructure solutions. We hope to contribute to an improvement of data management in the international biodiversity data infrastructures. In Finland, the law prohibits public authorities from distributing occurrence data if this causes increased threat to endangered species. However, neither the definition of 'endangered species' nor guidelines for the evaluation of potential risk by openness of data are formulated. To enable mobilisation of datasets containing information on endangered species, FinBIF convened a task force commissioned to set rules on data distribution, which respect the spirit of the law. The task force consisted of representatives of relevant data holding authorities and it consulted a wide group of taxon experts and the species information community. First, a list of species, judged to be among those targeted by the spirit of the law, was created (sensitive species data). Then the rules of restriction were decided on for each of the species. Measures of restriction ranged from complete non-disclosure of data to temporal and spatial restrictions. The identified safeguards concerning the sensitive data management in all use cases led us to create a series of innovative solutions Researchers often wish to restrict the openness of data they have gathered for research purposes These restrictions include embargo periods, limitations on the precision of data and controls on how the data is used. In many cases, however, researchers are willing to allow unrestricted official use of their data in certain cases such as for conservation management or land use planning. In these cases they will often allow storage and restricted use of exact data without an embargo. The same may be true for other data owners, such as nongovernmental organisations (NGOs) or private citizens. To support restrictions to openness, while simultaneously securing mobilisation of valuable datasets, FinBIF applies data sharing contracts including, as a rule, a precondition to share the original data with the public authorities for official use under the Creative Commons 4.0 BY -licence (CC 4.0 BY). The technical solution to enabling the rather complex data policy is that FinBIF stores the collated data in two separate data warehouses: a public one for the distribution of fully open data and temporally and spatially coarsened sensitive data, alongside another containing all data but with restricted access to authorised users. In addition, to allow case-by-case release of restricted data, FinBIF has developed a data request function (Fig. 1). When users of the open data retrieve a dataset using, e.g., taxonomic and spatial filtering, they receive a search result stating whether there are restricted data available based on the filters used. In these cases a user can issue a data request, automatically distributed to all owners of data contained in the collated data batch. Agreeing on the principles about how to apply restrictions to data openness and how to define authoritative use, has not been easy given the lack of precedents. It has required thorough and inclusive consultation with both state administration, conservation practitioners, scientific specialists and lawyers. The two main cultural constraints to overcome have been (1) embracing the FAIR principles of truly 'as open as possible' and only 'as closed as (absolutely) necessary (European Commission 2016); and, perhaps surprisingly, (2) figuring out novel ways to work across different state administrative sectors to share data.
