Bridging the biodiversity data gaps: Recommendations to meet users’ data needs

A strong case has been made for freely available, high quality data on species occurrence, in order to track changes in biodiversity. However, one of the main issues surrounding the provision of such data is that sources vary in quality, scope, and accuracy. Therefore publishers of such data must face the challenge of maximizing quality, utility and breadth of data coverage, in order to make such data useful to users. Here, we report a number of recommendations that stem from a content need assessment survey conducted by the Global Biodiversity Information Facility (GBIF). Through this survey, we aimed to distil the main user needs regarding biodiversity data. We find a broad range of recommendations from the survey respondents, principally concerning issues such as data quality, bias, and coverage, and extending ease of access. We recommend a candidate set of actions for the GBIF that fall into three classes: 1) addressing data gaps, data volume, and data quality, 2) aggregating new kinds of data for new applications, and 3) promoting ease-of-use and providing incentives for wider use. Addressing the challenge of providing high quality primary biodiversity data can potentially serve the needs of many international biodiversity initiatives, including the new 2020 biodiversity targets of the Convention on Biological Diversity, the emerging global biodiversity observation network (GEO BON), and the new Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES)

Unifying European Biodiversity Informatics (BioUnify)

In order to preserve the variety of life on Earth, we must understand it better. Biodiversity research is at a pivotal point with research projects generating data at an ever increasing rate. Structuring, aggregating, linking and processing these data in a meaningful way is a major challenge. The systematic application of information management and engineering technologies in the study of biodiversity (biodiversity informatics) help transform data to knowledge. However, concerted action is required to be taken by existing e-infrastructures to develop and adopt common standards, provisions for interoperability and avoid overlapping in functionality. This would result in the unification of the currently fragmented landscape that restricts European biodiversity research from reaching its full potential. The overarching goal of this COST Action is to coordinate existing research and capacity building efforts, through a bottom-up trans-disciplinary approach, by unifying biodiversity informatics communities across Europe in order to support the long-term vision of modelling biodiversity on earth. BioUnify will: 1. specify technical requirements, evaluate and improve models for efficient data and workflow storage, sharing and re-use, within and between different biodiversity communities; 2. mobilise taxonomic, ecological, genomic and biomonitoring data generated and curated by natural history collections, research networks and remote sensing sources in Europe; 3. leverage results of ongoing biodiversity informatics projects by identifying and developing functional synergies on individual, group and project level; 4. raise technical awareness and transfer skills between biodiversity researchers and information technologists; 5. formulate a viable roadmap for achieving the long-term goals for European biodiversity informatics, which ensures alignment with global activities and translates into efficient biodiversity policy

Biodiversity and Biocollections: Problem of Correspondence

This text is an English translation of those several sections of the original paper in Russian, where collection-related issues are considered. The full citation of the original paper is as following: Pavlinov I.Ya. 2016. [Bioraznoobrazie i biokollektsii: problema sootvetstvia]. In: Pavlinov I.Ya. (comp.). Aspects of Biodiversity. Archives of Zoological Museum of Lomonosov Moscow State University, Vol. 54, Pр. 733–786. Orientation of biology, as a natural science, on the study and explanation of the similarities and differences between organisms led in the second half of the 20th century to the recognition of a specifi c subject area of biological explorations, viz. biodiversity (BD). One of the important general scientifi c prerequisites for this shift was understanding that (at the level of ontology) the structured diversity of the living nature is its fundamental property equivocal to subjecting of some of its manifestations to certain laws. At the level of epistemology, this led to acknowledging that the “diversifi cationary” approach to description of the living beings is as justifi able as the before dominated “unifi cationary” one. This general trend has led to a signifi cant increase in the attention to BD. From a pragmatic perspective, its leitmotif was conservation of BD as a renewable resource, while from a scientifi c perspective the leitmotif was studying it was studying BD as a specifi c natural phenomenon. These two points of view are united by recognition of the need for scientific substantiation of BD conservation strategy, which implies the need for a detailed study of BD itself. At the level of ontology, one of the key problems in the study of BD (leaving aside the question of its genesis) is determination of its structure, which is interpreted as a manifestation of the structure of the Earth’s biota itself. With this, it is acknowledged that the subject area of empirical explorations is not the BD as a whole ( “Umgebung”) but its particular manifestations (“Umwelts”). It is proposed herewith to recognized, within the latter: fragments of BD (especially taxa and ecosystems), hierarchical levels of BD (primarily within- and interorganismal ones), and aspects of BD (before all taxonomic and meronomic ones). Attention is drawn to a new interpretation of bioinformatics as a discipline that studies the information support of BD explorations. An important fraction of this support are biocollections. The scientifi c value of collections means that they make it possible both empirical inferring and testing (verification) of the knowledge about BD. This makes biocollections, in their epistemological status, equivalent to experiments, and so makes studies of BD quite scientific. It is emphasized that the natural objects (naturalia), which are permanently kept in collections, contain primary (objective) information about BD, while information retrieved somehow from them is a secondary (subjective) one. Collection, as an information resource, serves as a research sample in the studies of BD. Collection pool, as the totality of all collection materials kept in repositories according to certain standards, can be treated as a general sample, and every single collection as a local sample. The main characteristic of collection-as-sample is its representativeness; so the basic strategy of development of the collection pool is to maximize its representativeness as a means to ensure correspondence of structure of biocollection pool to that of BD itself. The most fundamental characteristic of collection, as an information resource, is its scientific signifi cance. The following three main groups of more particular characteristics are distinguished: — the “proper” characteristics of every collection are its meaningfulness, informativeness, reliability, adequacy, documenting, systematicity, volume, structure, uniqueness, stability, lability; — the “external” characteristics of collection are resolution, usability, ethic constituent; — the “service” characteristics of collection are its museofication, storage system security, inclusion in metastructure, cost. In the contemporary world, development of the biocollection pool, as a specific resource for BD research, requires considerable organizational efforts, including work on their “information support” aimed at demonstrating the necessity of existence of the biocollections

The Freshwater Information Platform: a global online network providing data, tools and resources for science and policy support

Freshwaters are among the most complex, dynamic, and diverse ecosystems globally. Despite their small share of the earth’s surface (less than 1%) they are home to over 10% of all known animal species. Biodiversity decrease in general and freshwater biodiversity decline in particular have recently received increasing attention, and various policy instruments are now targeting the conservation, protection and enhancement of biodiversity and associated ecosystem services. Surveillance programs as well as a variety of research projects have been producing a tremendous amount of freshwater-related information. Though there have been various attempts to build infrastructures for online collection of such data, tools and reports, they often provide only limited access to resources that can readily be extracted for conducting large scale analyses. Here, we present the Freshwater Information Platform, an open system of relevant freshwater biodiversity-related information. We provide a comprehensive overview of the platform’s core components, highlight their values, present options for their use, and discuss future developments. This is complemented by information on the platform’s current management structure, options for contributing data and research results and an outlook for the future

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

The Bari Manifesto : An interoperability framework for essential biodiversity variables

Essential Biodiversity Variables (EBV) are fundamental variables that can be used for assessing biodiversity change over time, for determining adherence to biodiversity policy, for monitoring progress towards sustainable development goals, and for tracking biodiversity responses to disturbances and management interventions. Data from observations or models that provide measured or estimated EBV values, which we refer to as EBV data products, can help to capture the above processes and trends and can serve as a coherent framework for documenting trends in biodiversity. Using primary biodiversity records and other raw data as sources to produce EBV data products depends on cooperation and interoperability among multiple stakeholders, including those collecting and mobilising data for EBVs and those producing, publishing and preserving EBV data products. Here, we encapsulate ten principles for the current best practice in EBV-focused biodiversity informatics as 'The Bari Manifesto', serving as implementation guidelines for data and research infrastructure providers to support the emerging EBV operational framework based on trans-national and cross-infrastructure scientific workflows. The principles provide guidance on how to contribute towards the production of EBV data products that are globally oriented, while remaining appropriate to the producer's own mission, vision and goals. These ten principles cover: data management planning; data structure; metadata; services; data quality; workflows; provenance; ontologies/vocabularies; data preservation; and accessibility. For each principle, desired outcomes and goals have been formulated. Some specific actions related to fulfilling the Bari Manifesto principles are highlighted in the context of each of four groups of organizations contributing to enabling data interoperability - data standards bodies, research data infrastructures, the pertinent research communities, and funders. The Bari Manifesto provides a roadmap enabling support for routine generation of EBV data products, and increases the likelihood of success for a global EBV framework.Peer reviewe