Background Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of terms.

Biodiversity is a data-intensive science and relies on data from a large number of disciplines in order to build up a coherent picture of the extent and trajectory of life on earth (Bowker 2000). The ability to integrate such data from different disciplines, geographic regions and scales is crucial for making better decisions towards sustainable development. As the Biodiversity Information Standards (TDWG) community tackles standards development and adoption beyond its initial emphases on taxonomy and species distributions, expanding its impact and engaging a wider audience becomes increasingly important. Biological interactions data (e.g., predator-prey, host-parasite, plant-pollinator) have been a topic of interest within TDWG for many years and a Biological Interaction Data Interest Group (IG) was established in 2016 to address that issue. The IG has been working on the complexity of representing interactions data and surveying how Darwin Core (DwC, Wieczorek 2012) is being used to represent them (Salim 2022). The importance of cross-disciplinary science and data inspired the recently funded WorldFAIR project—Global cooperation on FAIR data policy and practice—coordinated by the Committee on Data of the International Science Council (CODATA), with the Research Data Alliance (RDA) as a major partner. WorldFAIR will work with a set of case studies to advance implementation of the FAIR data principles (Fig. 1). The FAIR data principles promote good practices in data management, by making data and metadata Findable, Accessible, Interoperable, and Reusable (Wilkinson 2016). Interoperability will be a particular focus to facilitate cross-disciplinary research. A set of recommendations and a framework for FAIR assessment in a set of disciplines will be developed (Molloy 2022). One of WorldFAIR's case studies is related to plant-pollinator interactions data. Its starting point is the model and schema proposed by Salim (2022) based on the DwC standard, which adheres to the diversifying GBIF data model strategy and on the Plant-Pollinator vocabulary described by Salim (2021). The case study on plant-pollinator interactions originated in the TDWG Biological Interaction Data Interest Group (IG) and within the RDA Improving Global Agricultural Data (IGAD) Community of Practice. IGAD is a forum for sharing experiences and providing visibility to research and work in food and agricultural data and has become a space for networking and blending ideas related to data management and interoperability. This topic was chosen because interoperability of plant-pollinator data is needed for better monitoring of pollination services, understanding the impacts of cultivated plants on wild pollinators and quantifying the contribution of wild pollinators to cultivated crops, understanding the impact of domesticated bees on wild ecosystems, and understanding the behaviour of these organisms and how this influences their effectiveness as pollinators. In addition to the ecological importance of these data, pollination is economically important for food production. In Brazil, the economic value of the pollination service was estimated at US$ 12 billion in 2018 (Wolowski 2019). All eleven case studies within the WorldFAIR project are working on FAIR Implementation Profiles (FIPs), which capture comprehensive sets of FAIR principle implementation choices made by communities of practice and which can accelerate convergence and facilitate cross-collaboration between disciplines (Schultes 2020). The FIPs are published through the FIP Wizard, which allows the creation of FAIR Enabling Resources. The FIPs creation will be repeated by the end of the project and capture results obtained from each case study in order to advance data interoperability. In the first FIP, resources from the Global Biodiversity Information Facility (GBIF) and Global Biotic Interactions (GloBI) were catalogued by the Plant-Pollinator Case Study team, and we expect to expand the existing FAIR Enabling Resources by the end of the project and contribute to plant-pollinator data interoperability and reuse. To tackle the challenge of promoting FAIR data for plant-pollinator interactions within the broad scope of the several disciplines and subdisciplines that generate and use them, we will conduct a survey of existing initiatives handling plant-pollinator interactions data and summarise the current status of best practices in the community. Once the survey is concluded, we will choose at least five agriculture-specific plant-pollination initiatives from our partners, to serve as targets for standards adoption. For data to be interoperable and reusable, it is essential that standards and best practices are community-developed to ensure adoption by the tool builders and data scientists across the globe. TDWG plays an important role in this scenario and we expect to engage the IG and other interested parties in that discussion.

Human demands on resources such as food and energy are increasing through time while global challenges such as climate change and biodiversity loss are becoming more complex to overcome, as well as more widely acknowledged by societies and governments. Reports from initiatives like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) have demanded quick and reliable access to high-quality spatial and temporal data of species occurrences, their interspecific relations and the effects of the environment on biotic interactions. Mapping species interactions is crucial to understanding and conserving ecosystem functioning and all the services it can provide (Tylianakis et al. 2010, Slade et al. 2017). Detailed data has the potential to improve our knowledge about ecological and evolutionary processes guided by interspecific interactions, as well as to assist in planning and decision making for biodiversity conservation and restoration (Menz et al. 2011). Although a great effort has been made to successfully standardize and aggregate species occurrence data, a formal standard to support biotic interaction data sharing and interoperability is still lacking. There are different biological interactions that can be studied, such as predator-prey, host-parasite and pollinator-plant and there is a variety of data practices and data representation procedures that can be used. Plant-pollinator interactions are recognized in many sources from the scientific literature (Abrol 2012, Ollerton 2021) for the importance of ecosystem functioning and sustainable agriculture. Primary data about pollination are becoming increasingly available online and can be accessed from a great number of data repositories. While a vast quantity of data on interactions, and on pollination in particular, is available, data are not integrated among sources, largely because of a lack of appropriate standards. We present a vocabulary of terms for sharing plant-pollinator interactions using one of the existing extensions to the Darwin Core standard (Wieczorek et al. 2012). In particular, the vocabulary is meant to be used for the term measurementType of the Extended Measurement Or Facts extension. The vocabulary was developed by a community of specialists in pollination biology and information science, including members of the TDWG Biological Interaction Data Interest Group, during almost four years of collaborative work. The vocabulary introduces 40 new terms, comprising many aspects of plant-pollinator interactions, and can be used to capture information produced by studies with different approaches and scales. The plant-pollinator interactions vocabulary is mainly a set of terms that can be both understood by people or interpreted by machines. The plant-pollinator vocabulary is composed of a defining a set of terms and descriptive documents explaining how the vocabulary is to be used. The terms in the vocabulary are divided into six categories: Animal, Plants, Flower, Interaction, Reproductive Success and Nectar Dynamics. The categories are not formally part of the vocabulary, they are used only to organize the vocabulary and to facilitate understanding by humans. We expect that the plant-pollinator vocabulary will contribute to data aggregation from a variety of sources worldwide at higher levels than we have experienced, significantly amplify plant-pollinator data availability for global synthesis, and contribute to knowledge in conservation and sustainable use of biodiversity.

Agrobiodiversity, or biodiversity for food and agriculture, plays a major role in the sustainability of food production. As stated by FAO 2019, agrobiodiversity can provide food production systems and society with a variety of services as ecosystem services, crops resilience to threats, sustainable intensification, livelihoods, food security and nutrition. The official definition of the concept has been given by CBD 2000 as "a broad term that includes all components of biological diversity of relevance to food and agriculture, and all components of biological diversity that constitute the agroecosystem: the variety and variability of animals, plants and micro-organisms, at the genetic, species and ecosystem levels, which are necessary to sustain key functions of the agro-ecosystem, its structure and processes". Thus, agrobiodiversity is primarily based on species and their function in agroecosystems. Many projects for sharing agrobiodiversity data in a structured way have emerged over the years. One realizes in looking at the Bioversity International (2018) crop descriptors list that the earliest groups of descriptors for crops and some associated data emerged back in the 1970s. In the same list, there are four multi-crop descriptors and derived standards, which are broad standards for crop-related data, namely: Core descriptors for in situ conservation of crop wild relatives v.1 (Thormann et al. 2013); FAO/Bioversity multi-crop passport descriptors V.2.1 (Alercia et al. 2015); Descriptors for farmers' knowledge of plants (Aknazarov et al. 2009); Descriptors for Genetic Marker Technologies (Vicente et al. 2004). Core descriptors for in situ conservation of crop wild relatives v.1 (Thormann et al. 2013); FAO/Bioversity multi-crop passport descriptors V.2.1 (Alercia et al. 2015); Descriptors for farmers' knowledge of plants (Aknazarov et al. 2009); Descriptors for Genetic Marker Technologies (Vicente et al. 2004). These standards share some core elements in common, as taxon, location, a period of collecting, and were intended to be used in the context of data on the occurrence of species in nature. Darwin Core, a TDWG standard commonly used for sharing data of taxon occurrence in nature (Wieczorek et al. 2012), is a globally used metadata standard, representing "a large majority of the 1.4 billion of species occurrence records shared by the Global Biodiversity Information Facility (GBIF), published by more than 1561 organizations in 59 countries in January 2020" (Body et al. 2020). Darwin Core is a standardized language that applies unique Internationalized Resource Identifiers (IRIs) to each element assigned as a metadata element, plus a label and a definition. It improves the interoperability between databases in the context of the Semantic Web (Duerst and Suignard 2005). We believe it is possible to use Darwin Core to represent agrobiodiversity data if a metadata extension is developed to enroll the agrobiodiversity concepts missing in Darwin Core. Thus, a research project held at the University of São Paulo in partnership with Brazilian Agricultural Research Corporation started to map concepts and descriptors from the literature for agrobiodiversity data representation. This project is the sequence of the research initiated by Soares et al. 2019. The crop descriptors published by Bioversity International (2018) may be integrated into the metadata extension, but also other standards like Global Genome Biodiversity Network (GGBN) Data Standard v1 (Droege et al. 2016) and the Darwin Core germplasm extension (DwC-germplasm). At the moment, we are designing a mind map to organize the agrobiodiversity concepts. We expect the metadata extension will be useful for the scientific community to share agrobiodiversity data as linked data, applying Resource Description Framework (RDF) as a resource relationship model, for example.

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