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This Data Management Plan outlines a comprehensive strategy for handling, storing, and sharing of data generated by digitisation projects of the herbarium at Meise Botanic Garden with Index Herbarium code BR. Its purpose is to establish clear guidelines for both staff and external users, specifying the terms governing data usage and storage. It aims to prioritise the FAIR principles (Findable, Accessible, Interoperable and Reusable), ensure responsible data management, facilitate long-term preservation, uphold legal and ethical obligations, all while aligning with the research excellence mission of Meise Botanic Garden. This plan serves as a guiding document to effectively and efficiently achieve these goals.

Worldwide, herbaria maintain collections of reference specimens representing global plant diversity. These collections are a valuable resource for fundamental botanical research and applied scientific research across various disciplines, and play a significant role in addressing major societal challenges such as biodiversity conservation. The digitisation of herbarium specimens and their online dissemination is one of the most important recent developments in the curation of these collections. Digitisation significantly enhances access to the collections for the research community and facilitates large-scale analysis of biodiversity data. Digitisation also provides a means for preserving the physical specimens, as it reduces the need for handling and transportation. Rapid technological developments have greatly accelerated the rate of databasing and digital imaging of collections. Meise Botanic Garden recently completed a six-year project to mass digitise its herbarium collections of about 3 million specimens mounted on sheets and through this process we have learned valuable lessons. We have captured our experience in 10 recommendations for other collection-holding institutions to take inspiration from as they start planning their own digitisation efforts. We also present case studies where we delve deeper into certain topics as examples.

A new community of research infrastructures has joined forces to provide scientists with seamless access to the plethora of data, services and tools in biodiversity research. New levels of technological innovation and interoperability between infrastructures foster unprecedented access to biodiversity data across all data domains and the entire research lifecycle, thus advancing open science practices and strengthening Europe's position in the global biodiversity research landscape. This policy brief highlights the potential benefits derived from enhanced connectivity and interoperability among various types of biodiversity data, fostering innovation and advancements in biodiversity science, monitoring, conservation, and policy development.

The Distributed System of Scientific Collections (DiSSCo) is a pan-European Research Infrastructure (RI) initiative. DiSSCo aims to bring together natural science collections from 175 museums, botanical gardens, universities and research institutes across 23 countries in a distributed infrastructure that makes these collections physically and digitally open and accessible for all forms of research and innovation. DiSSCo RI entered the ESFRI roadmap in 2018 and successfully concluded its Preparatory Phase in early 2023. The RI is now transitioning towards the constitution of its legal entity (an ERIC) and the start of its scaled-up construction (implementation) programme. This publication is an abridged version of the successful grant proposal for the DiSSCo Transition Project which has the goal of ensuring the seamless transition of the DiSSCo RI from its Preparatory Phase to the Construction Phase (expected to start in 2025). In this transition period, the Project will address five objectives building on the outcomes of the Preparatory Phase project:1) Advance the DiSSCo ERIC process and complete its policy framework, ensuring the smooth early-phase Implementation of DISSCo;2) Engage & support DiSSCo National Nodes to strengthen national commitments;3) Advance the development of core e-services to avoid the accumulation of technical debt before the start of the Implementation Phase;4) Continue international collaboration on standards & best practices needed for the DiSSCo service provision; and5) Continue supporting DiSSCo RI interim governance bodies and transition them to the DiSSCo ERIC formal governance.The Project’s impact will be measured against the increase in the RI's overall Implementation Readiness Level (IRL). More specifically, we will monitor its impact towards reaching the required level of maturity in four of the five dimensions of the IRL that can benefit from further developments. These include the organisational, financial, technological and data readiness levels.

Abstract We investigated the plant‐pollinator interactions of the Mexican grass‐carrying wasp Isodontia mexicana—native to North America and introduced in Europe in the 1960s—through the use of secondary data from citizen science observations. We applied a novel data exchange workflow from two global citizen science platforms, iNaturalist and Pl@ntNet. Images from iNaturalist of the wasp were used to query the Pl@ntNet application to identify possible plant species present in the pictures. Simultaneously, botanists manually identified the plants at family, genus and species levels and additionally documented flower color and biotic interactions. The goals were to calibrate Pl@ntNet's accuracy in relation to this workflow, update the list of plant species that I. mexicana visits as well as its flower color preferences in its native and introduced ranges. In addition, we investigated the types and corresponding frequencies of other biotic interactions incidentally captured on the citizen scientists' images. Although the list of known host plants could be expanded, identifying the flora from images that predominantly show an insect proved difficult for both experts and the Pl@ntNet app. The workflow performs with a 75% probability of correct identification of the plant at the species level from a score of 0.8, and with over 90% chance of correct family and genus identification from a score of 0.5. Although the number of images above these scores may be limited due to the flower parts present on the pictures, our approach can help to get an overview into species interactions and generate more specific research questions. It could be used as a triaging method to select images for further investigation. Additionally, the manual analysis of the images has shown that the information they contain offers great potential for learning more about the ecology of an introduced species in its new range.

There is an increased awareness of the importance of data publication, data sharing, and open science to support research, monitoring and control of vector-borne disease (VBD). Here we describe the efforts of the Global Biodiversity Information Facility (GBIF) as well as the World Health Special Programme on Research and Training in Diseases of Poverty (TDR) to promote publication of data related to vectors of diseases. In 2020, a GBIF task group of experts was formed to provide advice and support efforts aimed at enhancing the coverage and accessibility of data on vectors of human diseases within GBIF. Various strategies, such as organizing training courses and publishing data papers, were used to increase this content. This editorial introduces the outcome of a second call for data papers partnered by the TDR, GBIF and GigaScience Press in the journal GigaByte. Biodiversity and infectious diseases are linked in complex ways. These links can involve changes from the microorganism level to that of the habitat, and there are many ways in which these factors interact to affect human health. One way to tackle disease control and possibly elimination, is to provide stakeholders with access to a wide range of data shared under the FAIR principles, so it is possible to support early detection, analyses and evaluation, and to promote policy improvements and/or development.

Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learning and computer vision. While image analysis has become mainstream in consumer applications, it is still used only on an artisanal basis in the biological collections community, largely because the image corpora are dispersed. Yet, there is massive untapped potential for novel applications and research if images of collection objects could be made accessible in a single corpus. In this paper, we make the case for infrastructure that could support image analysis of collection objects. We show that such infrastructure is entirely feasible and well worth investing in.

IntroductionSpecies distribution models (SDMs) are often used to produce risk maps to guide conservation management and decision-making with regard to invasive alien species (IAS). However, gathering and harmonizing the required species occurrence and other spatial data, as well as identifying and coding a robust modeling framework for reproducible SDMs, requires expertise in both ecological data science and statistics.MethodsWe developed WiSDM, a semi-automated workflow to democratize the creation of open, reproducible, transparent, invasive alien species risk maps. To facilitate the production of IAS risk maps using WiSDM, we harmonized and openly published climate and land cover data to a 1 km2 resolution with coverage for Europe. Our workflow mitigates spatial sampling bias, identifies highly correlated predictors, creates ensemble models to predict risk, and quantifies spatial autocorrelation. In addition, we present a novel application for assessing the transferability of the model by quantifying and visualizing the confidence of its predictions. All modeling steps, parameters, evaluation statistics, and other outputs are also automatically generated and are saved in a R markdown notebook file.ResultsOur workflow requires minimal input from the user to generate reproducible maps at 1 km2 resolution for standard Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emission representative concentration pathway (RCP) scenarios. The confidence associated with the predicted risk for each 1km2 pixel is also mapped, enabling the intuitive visualization and understanding of how the confidence of the model varies across space and RCP scenarios.DiscussionOur workflow can readily be applied by end users with a basic knowledge of R, does not require expertise in species distribution modeling, and only requires an understanding of the ecological theory underlying species distributions. The risk maps generated by our repeatable workflow can be used to support IAS risk assessment and surveillance.

Abstract In the face of the global biodiversity crisis, collecting comprehensive data and making the best use of existing data are becoming increasingly important to understand patterns and drivers of environmental and biological phenomena at different scales. Here we address the concept of secondary data, which refers to additional information unintentionally captured in species records, especially in multimedia‐based citizen science reports. We argue that secondary data can provide a wealth of ecologically relevant information, the utilisation of which can enhance our understanding of traits and interactions among individual organisms, populations and biodiversity dynamics in general. We explore the possibilities offered by secondary data and describe their main types and sources. An overview of research in this field provides a synthesis of the results already achieved using secondary data and different approaches to information extraction. Finally, we discuss challenges to the widespread use of secondary data, such as biases, licensing issues, use of metadata and lack of awareness of this trove of data due to a missing common terminology, as well as possible solutions to overcome these barriers. Although the exploration and use of secondary data is only emerging, the many opportunities identified show how these data can enrich biodiversity research and monitoring.

Abstract The Kunming‐Montreal Global Biodiversity Framework (GBF) calls for a 50% reduction in rates of invasive alien species establishment by 2030. However, estimating changes in rates of introduction and establishment is far from straightforward, particularly on a national scale. Variation in survey effort over time, the absence of data on survey effort, and aspects of the invasion process itself interact in ways that make rate estimates from naive models of invasion trends inaccurate. To support progress toward robust global and national reporting against the GBF invasions target, we illustrate this problem using a combination of simulations, and global and national scale case studies. We provide recommendations and a clear set of steps that are needed for progress. These include routine collection of survey effort data as part of surveillance and monitoring protocols and working closely with researchers to develop meaningful estimates of change in biological invasions. Better awareness of this challenge and investment in developing robust approaches will be required from Parties if progress on Target 6 of the GBF is to be tracked and achieved.

Alien insects represent one of the most species rich groups of organisms introduced to Europe, with some responsible for adverse social-economic, human-health, biodiversity and ecosystem impacts. The impacts of invasive alien species, especially on island ecosystems, have been a hot topic of research worldwide. Cyprus is a Mediterranean island at the biogeographic crossroads of Asia, Africa and Europe. This study presents the database of the alien insects of the island of Cyprus as a whole, created through an extensive review including grey literature and online sources. The Alien to Cyprus Entomofauna (ACE) triples the known number of alien insects and adds supplemental information to existing species. Data concerning a total of 349 alien insects are presented alongside an updated checklist and recommendations for informing management. The status of alien insects on the island, their origin, trophic guilds, establishment, pathways of introduction and impacts are discussed. Developing an alien species inventory for the island is challenging due to its geographic position and the increasing movement of people and goods leading to new species introductions. This publication constitutes an important first step towards providing information for effective actions to tackle invasive alien insects on Cyprus. The checklist and accompanying information can underpin understanding of the status and trends of alien species including providing information for risk assessments. ACE will continue to be maintained and updated as new records for Cyprus are made.

Natural history collections are the foundations upon which all knowledge of natural history is constructed. Biological specimens are the best documentation of variation within each species, increasingly serve as curated sources for reference DNA, and are frequently our only evidence for historical species distribution. Collections represent an enormous multigenerational investment in research infrastructure for the biological sciences, but despite this importance most of the holdings of these institutions remain invisible on the Internet, inaccessible to taxonomists from other countries and hidden from computational biodiversity research.Although comprehensive digitisation of the complete holdings of each natural history collection is the long-term goal, this is an expensive and labor-intensive task and will not be completed in the near future for all collections. However, many benefits could quickly be achieved by publishing high-quality metadata on each collection to increase its visibility, provide the foundations for further digitisation and enable researchers to discover and communicate with collections of interest.This paper summarises the results from a consultation activity carried out in 2020 as part of the SYNTHESYS+ (Synthesys of Systematic Resources), “Developing implementation roadmaps for priority infrastructure areas as part of cooperative RI for biodiversity” project. This consultation was primed through an ideas paper, and introductory webinars and conducted as a facilitated two-week online multilingual discussion around 26 topics grouped under four broad headings (Users, Content, Technology and Governance). The results of these discussions are summarised here, along with the wider context of existing and planned initiatives.

The paper summarises many years of discussions and experience of biodiversity publishers, organisations, research projects and individual researchers, and proposes recommendations for implementation of persistent identifiers for article metadata, structural elements (sections, subsections, figures, tables, references, supplementary materials and others) and data specific to biodiversity (taxonomic treatments, treatment citations, taxon names, material citations, gene sequences, specimens, scientific collections) in taxonomy and biodiversity publishing. The paper proposes best practices on how identifiers should be used in the different cases and on how they can be minted, cited, and expressed in the backend article XML to facilitate conversion to and further re-use of the article content as FAIR data. The paper also discusses several specific routes for post-publication re-use of semantically enhanced content through large biodiversity data aggregators such as the Global Biodiversity Information Facility (GBIF), the International Nucleotide Sequence Database Collaboration (INSDC) and others, and proposes specifications of both identifiers and XML tags to be used for that purpose. A summary table provides an account and overview of the recommendations. The guidelines are supported with examples from the existing publishing practices.

Invasive alien species (IAS) are a key driver of global biodiversity loss. Reducing their spread and impact is a target of the Sustainable Development Goals (SDG target 15.8) and of the EU IAS Regulation 1143/2014. The use of citizen science offers various benefits to alien species’ decision-making and to society, since public participation in research and management boosts awareness, engagement and scientific literacy and can reduce conflict in IAS management. We report the results of a survey on alien species citizen science initiatives within the framework of the European Cooperation in Science and Technology (COST) Action Alien-CSI. We gathered metadata on 103 initiatives across 41 countries, excluding general biodiversity reporting portals, spanning from 2005 to 2020, offering the most comprehensive account of alien species citizen science initiatives on the continent to date. We retrieved information on project scope, policy relevance, engagement methods, data capture, data quality and data management, methods and technologies applied and performance indicators such as the number of records coming from projects, the numbers of participants and publications. The 103 initiatives were unevenly distributed geographically, with countries with a tradition of citizen science showing more active projects. The majority of projects were contributory and were run at a national scale, targeting the general public, alien plants and insects, and terrestrial ecosystems. These factors of project scope were consistent between geographic regions. Most projects focused on collecting species presence or abundance data, aiming to map presence and spread. As 75% of the initiatives specifically collected data on IAS of Union Concern, citizen science in Europe is of policy relevance. Despite this, only half of the projects indicated sustainable funding. Nearly all projects had validation in place to verify species identifications. Strikingly, only about one third of the projects shared their data with open data repositories such as the Global Biodiversity Information Facility or the European Alien Species Information Network. Moreover, many did not adhere to the principles of FAIR data management. Finally, certain factors of engagement, feedback and support, had significant impacts on project performance, with the provision of a map with sightings being especially beneficial. Based on this dataset, we offer suggestions to strengthen the network of IAS citizen science projects and to foster knowledge exchange among citizens, scientists, managers, policy-makers, local authorities, and other stakeholders.

The BiCIKL project is born from a vision that biodiversity data are most useful if they are presented as a network of data that can be integrated and viewed from different starting points. BiCIKL’s goal is to realise that vision by linking biodiversity data infrastructures, particularly for literature, molecular sequences, specimens, nomenclature and analytics. To make those links we need to better understand the existing infrastructures, their limitations, the nature of the data they hold, the services they provide and particularly how they can interoperate. In light of those aims, in the autumn of 2021, 74 people from the biodiversity data community engaged in a total of twelve hackathon topics with the aim to assess the current state of interoperability between infrastructures holding biodiversity data. These topics examined interoperability from several angles. Some were research subjects that required interoperability to get results, some examined modalities of access and the use and implementation of standards, while others tested technologies and workflows to improve linkage of different data types.These topics and the issues in regard to interoperability uncovered by the hackathon participants inspired the formulation of the following recommendations for infrastructures related to (1) the use of data brokers, (2) building communities and trust, (3) cloud computing as a collaborative tool, (4) standards and (5) multiple modalities of access:If direct linking cannot be supported between infrastructures, explore using data brokers to store linksCooperate with open linkage brokers to provide a simple way to allow two-way links between infrastructures, without having to co-organize between many different organisationsFacilitate and encourage the external reporting of issues related to their infrastructure and its interoperability.Facilitate and encourage requests for new features related to their infrastructure and its interoperability.Provide development roadmaps openlyProvide a mechanism for anyone to ask for helpDiscuss issues in an open forumProvide cloud-based environments to allow external participants to contribute and test changes to featuresConsider the opportunities that cloud computing brings as a means to enable shared management of the infrastructure.Promote the sharing of knowledge around big data technologies amongst partners, using cloud computing as a training environmentInvest in standards compliance and work with standards organisations to develop new, and extend existing standardsReport on and review standards compliance within an infrastructure with metrics that give credit for work on standard compliance and developmentProvide as many different modalities of access as possibleAvoid requiring personal contacts to download dataProvide a full description of an API and the data it servesFinally, the hackathons were an ideal meeting opportunity to build, diversify and extend the BiCIKL community further, and to ensure the alignment of the community with a common vision on how best to link data from specimens, samples, sequences, taxonomic names and taxonomic literature.

Scientific collections have been built by people. For hundreds of years, people have collected, studied, identified, preserved, documented and curated collection specimens. Understanding who those people are is of interest to historians, but much more can be made of these data by other stakeholders once they have been linked to the people’s identities and their biographies. Knowing who people are helps us attribute work correctly, validate data and understand the scientific contribution of people and institutions. We can evaluate the work they have done, the interests they have, the places they have worked and what they have created from the specimens they have collected. The problem is that all we know about most of the people associated with collections are their names written on specimens. Disambiguating these people is the challenge that this paper addresses. Disambiguation of people often proves difficult in isolation and can result in staff or researchers independently trying to determine the identity of specific individuals over and over again. By sharing biographical data and building an open, collectively maintained dataset with shared knowledge, expertise and resources, it is possible to collectively deduce the identities of individuals, aggregate biographical information for each person, reduce duplication of effort and share the information locally and globally. The authors of this paper aspire to disambiguate all person names efficiently and fully in all their variations across the entirety of the biological sciences, starting with collections. Towards that vision, this paper has three key aims: to improve the linking, validation, enhancement and valorisation of person-related information within and between collections, databases and publications; to suggest good practice for identifying people involved in biological collections; and to promote coordination amongst all stakeholders, including individuals, natural history collections, institutions, learned societies, government agencies and data aggregators.

Measurement(s) Presence of invasive alien species Technology Type(s) Literature and datasets Factor Type(s) scientificName Sample Characteristic - Organism Multitaxon Sample Characteristic - Environment Multihabitat Sample Characteristic - Location Global

The unprecedented generation of large volumes of biodiversity data is consistently contributing to a wide range of disciplines, including disease ecology. Emerging infectious diseases are usually zoonoses caused by multi-host pathogens. Therefore, their understanding may require the access to biodiversity data related to the ecology and the occurrence of the species involved. Nevertheless, despite several data-mobilization initiatives, the usage of biodiversity data for research into disease dynamics has not yet been fully leveraged.To explore current contribution, trends, and to identify limitations, we characterized biodiversity data usage in scientific publications related to human health, contrasting patterns of studies citing the Global Biodiversity Information Facility (GBIF) with those obtaining data from other sources.We found that the studies mainly obtained data from scientific literature and other not aggregated or standardized sources. Most of the studies explored pathogen species and, particularly those with GBIF-mediated data, tended to explore and reuse data of multiple species (>2). Data sources varied according to the taxa and epidemiological roles of the species involved. Biodiversity data repositories were mainly used for species related to hosts, reservoirs, and vectors, and barely used as a source of pathogens data, which was usually obtained from human and animal-health related institutions. While both GBIF- and not GBIF-mediated data studies explored similar diseases and topics, they presented discipline biases and different analytical approaches.Research on emerging infectious diseases may require the access to geographical and ecological data of multiple species. The One Health challenge requires interdisciplinary collaboration and data sharing, which is facilitated by aggregated repositories and platforms. The contribution of biodiversity data to understand infectious disease dynamics should be acknowledged, strengthened, and promoted.

BiCIKL is an European Union Horizon 2020 project that will initiate and build a new European starting community of key research infrastructures, establishing open science practices in the domain of biodiversity through provision of access to data, associated tools and services at each separate stage of and along the entire research cycle. BiCIKL will provide new methods and workflows for an integrated access to harvesting, liberating, linking, accessing and re-using of subarticle-level data (specimens, material citations, samples, sequences, taxonomic names, taxonomic treatments, figures, tables) extracted from literature. BiCIKL will provide for the first time access and tools for seamless linking and usage tracking of data along the line: specimens > sequences > species > analytics > publications > biodiversity knowledge graph > re-use.

Domestic and captive animals and cultivated plants should be recognised as integral components in contemporary ecosystems. They interact with wild organisms through such mechanisms as hybridization, predation, herbivory, competition and disease transmission and, in many cases, define ecosystem properties. Nevertheless, it is widespread practice for data on domestic, captive and cultivated organisms to be excluded from biodiversity repositories, such as natural history collections. Furthermore, there is a lack of integration of data collected about biodiversity in disciplines, such as agriculture, veterinary science, epidemiology and invasion science. Discipline-specific data are often intentionally excluded from integrative databases in order to maintain the “purity” of data on natural processes. Rather than being beneficial, we argue that this practise of data exclusivity greatly limits the utility of discipline-specific data for applications ranging from agricultural pest management to invasion biology, infectious disease prevention and community ecology. This problem can be resolved by data providers using standards to indicate whether the observed organism is of wild or domestic origin and by integrating their data with other biodiversity data (e.g. in the Global Biodiversity Information Facility). Doing so will enable efforts to integrate the full panorama of biodiversity knowledge across related disciplines to tackle pressing societal questions.

Many species have been introduced beyond their native ranges and many have become global weeds. Human mediated dispersal has removed the geographic isolation of these species, reversing millions of years of independent evolution. Examples are the Oxalis species in section Corniculatae where several species have become invasive. Here we characterize and formally describe a hybrid between O. dillenii and O. corniculata, which occurs spontaneously in Belgium and Japan. Oxalis corniculata is probably native to Japan, but both species are alien to Belgium and O. dillenii is native to North America. We formally name this hybrid as Oxalis × vanaelstii. Although this hybrid is sterile, it is nevertheless vigorous and perennial. Both parent species grow as weeds in gardens; therefore, it is likely to be more common than currently appreciated in countries where these species co-occur.

Abstract Background Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely related projects and initiatives, we need common ground, also known as a “commons.” Wikidata, a public knowledge graph aligned with Wikipedia, is such a commons and uses unique identifiers to link knowledge in other knowledge bases. However, Wikidata may not always have the right schema for the urgent questions. In this paper, we address this problem by showing how a data schema required for the integration can be modeled with entity schemas represented by Shape Expressions. Results As a telling example, we describe the process of aligning resources on the genomes and proteomes of the SARS-CoV-2 virus and related viruses as well as how Shape Expressions can be defined for Wikidata to model the knowledge, helping others studying the SARS-CoV-2 pandemic. How this model can be used to make data between various resources interoperable is demonstrated by integrating data from NCBI (National Center for Biotechnology Information) Taxonomy, NCBI Genes, UniProt, and WikiPathways. Based on that model, a set of automated applications or bots were written for regular updates of these sources in Wikidata and added to a platform for automatically running these updates. Conclusions Although this workflow is developed and applied in the context of the COVID-19 pandemic, to demonstrate its broader applicability it was also applied to other human coronaviruses (MERS, SARS, human coronavirus NL63, human coronavirus 229E, human coronavirus HKU1, human coronavirus OC4).

We describe an effective approach to automated text digitisation with respect to natural history specimen labels. These labels contain much useful data about the specimen including its collector, country of origin, and collection date. Our approach to automatically extracting these data takes the form of a pipeline. Recommendations are made for the pipeline's component parts based on state-of-the-art technologies.Optical Character Recognition (OCR) can be used to digitise text on images of specimens. However, recognising text quickly and accurately from these images can be a challenge for OCR. We show that OCR performance can be improved by prior segmentation of specimen images into their component parts. This ensures that only text-bearing labels are submitted for OCR processing as opposed to whole specimen images, which inevitably contain non-textual information that may lead to false positive readings. In our testing Tesseract OCR version 4.0.0 offers promising text recognition accuracy with segmented images.Not all the text on specimen labels is printed. Handwritten text varies much more and does not conform to standard shapes and sizes of individual characters, which poses an additional challenge for OCR. Recently, deep learning has allowed for significant advances in this area. Google's Cloud Vision, which is based on deep learning, is trained on large-scale datasets, and is shown to be quite adept at this task. This may take us some way towards negating the need for humans to routinely transcribe handwritten text.Determining the countries and collectors of specimens has been the goal of previous automated text digitisation research activities. Our approach also focuses on these two pieces of information. An area of Natural Language Processing (NLP) known as Named Entity Recognition (NER) has matured enough to semi-automate this task. Our experiments demonstrated that existing approaches can accurately recognise location and person names within the text extracted from segmented images via Tesseract version 4.0.0.We have highlighted the main recommendations for potential pipeline components. The paper also provides guidance on selecting appropriate software solutions. These include automatic language identification, terminology extraction, and integrating all pipeline components into a scientific workflow to automate the overall digitisation process.

This report reviews the current state-of-the-art applied approaches on automated tools, services and workflows for extracting information from images of natural history specimens and their labels. We consider the potential for repurposing existing tools, including workflow management systems; and areas where more development is required. This paper was written as part of the SYNTHESYS+ project for software development teams and informatics teams working on new software-based approaches to improve mass digitisation of natural history specimens.

We compare different approaches to transcribing natural history data and summarise the advantages and disadvantages of each approach using six case studies from four different natural history collections. We summarise the main cost considerations when planning a transcription project and discuss the limitations we current have in understanding the costs behind transcription and data quality.

Biodiversity data are being collected at unprecedented rates. Such data often have significant value for purposes beyond the initial reason for which they were collected, particularly when they are combined and collated with other data sources. In the field of invasion ecology, however, integrating data represents a major challenge due to the notorious lack of standardisation of terminologies and categorisations, and the application of deviating concepts of biological invasions. Here, we introduce the SInAS workflow, short for Standardising and Integrating Alien Species data. The SInAS workflow standardises terminologies following Darwin Core, location names using a proposed translation table, taxon names based on the GBIF backbone taxonomy, and dates of first records based on a set of predefined rules. The output of the SInAS workflow provides various entry points that can be used both to improve coherence among the databases and to check and correct the original data. The workflow is flexible and can be easily adapted and extended to the needs of different users. We illustrate the workflow using a case-study integrating five widely used global databases of information on biological invasions. The comparison of the standardised databases revealed a surprisingly low degree of overlap, which indicates that the amount of data may currently not be fully exploited in the original databases. We highly recommend the use and development of publicly available workflows to ensure that the integration of databases is reproducible and transparent. Workflows, such as SInAS, ultimately increase trust in data, study results, and conclusions.

DiSSCo, the Distributed System of Scientific Collections, is a pan-European Research Infrastructure (RI) mobilising, unifying bio- and geo-diversity information connected to the specimens held in natural science collections and delivering it to scientific communities and beyond. Bringing together 120 institutions across 21 countries and combining earlier investments in data interoperability practices with technological advancements in digitisation, cloud services and semantic linking, DiSSCo makes the data from natural science collections available as one virtual data cloud, connected with data emerging from new techniques and not already linked to specimens. These new data include DNA barcodes, whole genome sequences, proteomics and metabolomics data, chemical data, trait data, and imaging data (Computer-assisted Tomography (CT), Synchrotron, etc.), to name but a few; and will lead to a wide range of end-user services that begins with finding, accessing, using and improving data. DiSSCo will deliver the diagnostic information required for novel approaches and new services that will transform the landscape of what is possible in ways that are hard to imagine today.With approximately 1.5 billion objects to be digitised, bringing natural science collections to the information age is expected to result in many tens of petabytes of new data over the next decades, used on average by 5,000 – 15,000 unique users every day. This requires new skills, clear policies and robust procedures and new technologies to create, work with and manage large digital datasets over their entire research data lifecycle, including their long-term storage and preservation and open access. Such processes and procedures must match and be derived from the latest thinking in open science and data management, realising the core principles of 'findable, accessible, interoperable and reusable' (FAIR).Synthesised from results of the ICEDIG project ("Innovation and Consolidation for Large Scale Digitisation of Natural Heritage", EU Horizon 2020 grant agreement No. 777483) the DiSSCo Conceptual Design Blueprint covers the organisational arrangements, processes and practices, the architecture, tools and technologies, culture, skills and capacity building and governance and business model proposals for constructing the digitisation infrastructure of DiSSCo. In this context, the digitisation infrastructure of DiSSCo must be interpreted as that infrastructure (machinery, processing, procedures, personnel, organisation) offering Europe-wide capabilities for mass digitisation and digitisation-on-demand, and for the subsequent management (i.e., curation, publication, processing) and use of the resulting data. The blueprint constitutes the essential background needed to continue work to raise the overall maturity of the DiSSCo Programme across multiple dimensions (organisational, technical, scientific, data, financial) to achieve readiness to begin construction.Today, collection digitisation efforts have reached most collection-holding institutions across Europe. Much of the leadership and many of the people involved in digitisation and working with digital collections wish to take steps forward and expand the efforts to benefit further from the already noticeable positive effects. The collective results of examining technical, financial, policy and governance aspects show the way forward to operating a large distributed initiative i.e., the Distributed System of Scientific Collections (DiSSCo) for natural science collections across Europe. Ample examples, opportunities and need for innovation and consolidation for large scale digitisation of natural heritage have been described. The blueprint makes one hundred and four (104) recommendations to be considered by other elements of the DiSSCo Programme of linked projects (i.e., SYNTHESYS+, COST MOBILISE, DiSSCo Prepare, and others to follow) and the DiSSCo Programme leadership as the journey towards organisational, technical, scientific, data and financial readiness continues.Nevertheless, significant obstacles must be overcome as a matter of priority if DiSSCo is to move beyond its Design and Preparatory Phases during 2024. Specifically, these include:Organisational:Strengthen common purpose by adopting a common framework for policy harmonisation and capacity enhancement across broad areas, especially in respect of digitisation strategy and prioritisation, digitisation processes and techniques, data and digital media publication and open access, protection of and access to sensitive data, and administration of access and benefit sharing.Pursue the joint ventures and other relationships necessary to the successful delivery of the DiSSCo mission, especially ventures with GBIF and other international and regional digitisation and data aggregation organisations, in the context of infrastructure policy frameworks, such as EOSC. Proceed with the explicit aim of avoiding divergences of approach in global natural science collections data management and research.Technical:Adopt and enhance the DiSSCo Digital Specimen Architecture and, specifically as a matter of urgency, establish the persistent identifier scheme to be used by DiSSCo and (ideally) other comparable regional initiatives.Establish (software) engineering development and (infrastructure) operations team and direction essential to the delivery of services and functionalities expected from DiSSCo such that earnest engineering can lead to an early start of DiSSCo operations.Scientific:Establish a common digital research agenda leveraging Digital (extended) Specimens as anchoring points for all specimen-associated and -derived information, demonstrating to research institutions and policy/decision-makers the new possibilities, opportunities and value of participating in the DiSSCo research infrastructure.Data:Adopt the FAIR Digital Object Framework and the International Image Interoperability Framework as the low entropy means to achieving uniform access to rich data (image and non-image) that is findable, accessible, interoperable and reusable (FAIR).Develop and promote best practice approaches towards achieving the best digitisation results in terms of quality (best, according to agreed minimum information and other specifications), time (highest throughput, fast), and cost (lowest, minimal per specimen).FinancialBroaden attractiveness (i.e., improve bankability) of DiSSCo as an infrastructure to invest in.Plan for finding ways to bridge the funding gap to avoid disruptions in the critical funding path that risks interrupting core operations; especially when the gap opens between the end of preparations and beginning of implementation due to unsolved political difficulties.Strategically, it is vital to balance the multiple factors addressed by the blueprint against one another to achieve the desired goals of the DiSSCo programme. Decisions cannot be taken on one aspect alone without considering other aspects, and here the various governance structures of DiSSCo (General Assembly, advisory boards, and stakeholder forums) play a critical role over the coming years.

Digitisation of natural history collections has evolved from creating databases for the recording of specimens’ catalogue and label data to include digital images of specimens. This has been driven by several important factors, such as a need to increase global accessibility to specimens and to preserve the original specimens by limiting their manual handling. The size of the collections pointed to the need of high throughput digitisation workflows. However, digital imaging of large numbers of fragile specimens is an expensive and time-consuming process that should be performed only once. To achieve this, the digital images produced need to be useful for the largest set of applications possible and have a potentially unlimited shelf life. The constraints on digitisation speed need to be balanced against the applicability and longevity of the images, which, in turn, depend directly on the quality of those images. As a result, the quality criteria that specimen images need to fulfil influence the design, implementation and execution of digitisation workflows. Different standards and guidelines for producing quality research images from specimens have been proposed; however, their actual adaptation to suit the needs of different types of specimens requires further analysis. This paper presents the digitisation workflow implemented by Meise Botanic Garden (MBG). This workflow is relevant because of its modular design, its strong focus on image quality assessment, its flexibility that allows combining in-house and outsourced digitisation, processing, preservation and publishing facilities and its capacity to evolve for integrating alternative components from different sources. The design and operation of the digitisation workflow is provided to showcase how it was derived, with particular attention to the built-in audit trail within the workflow, which ensures the scalable production of high-quality specimen images and how this audit trail ensures that new modules do not affect either the speed of imaging or the quality of the images produced.

European natural history collections are a critical infrastructure for meeting the most important challenge humans face over the next 30 years – creating a sustainable future for ourselves and the natural systems on which we depend – and for answering fundamental scientific questions about ecological, evolutionary, and geological processes. Since 2004 SYNTHESYS has been an essential instrument supporting this community, underpinning new ways to access and exploit collections, harmonising policy and providing significant new insights for thousands of researchers, while fostering the development of new approaches to face urgent societal challenges. SYNTHESYS+ is a fourth iteration of this programme, and represents a step change in the evolution of this community. For the first time SYNTHESYS+ brings together the European branches of the global natural science organisations (GBIF https://www.gbif.org/, TDWG https://www.tdwg.org/, GGBN http://www.ggbn.org/ggbn_portal/ and CETAF https://cetaf.org/) with an unprecedented number of collections, to integrate, innovate and internationalise our efforts within the global scientific collections community. Major new developments addressed by SYNTHESYS+ include the delivery of a new virtual access programme, providing digitisation on demand services to a significantly expanded user community; the construction of a European Loans and Visits System (ELViS) providing, for the first time, a unified gateway to accessing digital, physical and molecular collections; and a new data processing platform (the Specimen Data Refinery), applying cutting edge artificial intelligence to dramatically speed up the digital mobilisation of natural history collections. The activities of SYNTHESYS+ form a critical dependency for DiSSCo - the Distributed System of Scientific Collections (https://dissco.eu/), which is the European Research Infrastructure for natural science collections, under the ESFRI umbrella. DiSSCo will undertake the maintenance and sustainability of SYNTHESYS+ products at the end of the programme.

Oxalis bowiei W.T.Aiton ex G.Don (Oxalidaceae) from South Africa was described in 1831, but has not been typified. Although no preserved material was mentioned in the original description, an illustration by Thomas Duncanson painted a few years earlier would have been available to W.T. Aiton at the time he described it and it matches his description. Therefore this illustration is designated as the lectotype for Oxalis bowiei.

There is no sign of saturation in accumulation of alien species (AS) introductions worldwide, additionally the rate of spread for some species has also been shown to be increasing. However, the challenges of gathering information on AS are recognized. Recent developments in citizen science (CS) provide an opportunity to improve data flow and knowledge on AS while ensuring effective and high quality societal engagement with the issue of IAS (Invasive Alien Species). Advances in technology, particularly on-line recording and smartphone apps, along with the development of social media, have revolutionized CS and increased connectivity while new and innovative analysis techniques are emerging to ensure appropriate management, visualization, interpretation and use and sharing of the data. In early July 2018 we launched a European CO-operation in Science and Technology (COST) Action to address multidisciplinary research questions in relation to developing and implementing CS, advancing scientific understanding of AS dynamics while informing decision-making specifically implementation of technical requirements of relevant legislation such as the EU Regulation 1143/2014 on IAS. It will also support the EU biodiversity goals and embedding science within society. The Action will explore and document approaches to establishing a European-wide CS AS network. It will embrace relevant innovations for data gathering and reporting to support the implementation of monitoring and surveillance measures, while ensuring benefits for society and citizens, through an AS CS European network. The Action will, therefore, increase levels of participation and quality of engagement with current CS initiatives, ensuring and evaluating educational value, and improve the value outcomes for potential users including citizens, scientists, alien species managers, policy-makers, local authorities, industry and other stakeholders.

Natural history collection data available digitally on the web have so far only made limited use of the potential of semantic links among themselves and with cross-disciplinary resources. In a pilot study, botanical collections of the Consortium of European Taxonomic Facilities (CETAF) have therefore begun to semantically annotate their collection data, starting with data on people, and to link them via a central index system. As a result, it is now possible to query data on collectors across different collections and automatically link them to a variety of external resources. The system is being continuously developed and is already in production use in an international collection portal.

Observations reported by citizens are crucial to the ability of scientists to inform policy on biodiversity. This is particularly relevant in the case of preventing and controlling biological invasions; that is, the introduction and spread of species outside their natural ranges as a consequence of human activity. Such invasions of natural ecosystems represent one of the main threats to biodiversity, economy, and human well-being globally, and policies on tackling this issue require a strong evidence base that increasingly is built on citizen science. Many citizens are motivated to collect data for their own interest, while presumably, few expect to make a major impact on policy. The needs of policy-makers are not always aligned with the approaches used by citizens to collect and share data. Therefore, how can we motivate citizen science for the needs of policy without compromising the enjoyment that citizens gain from collecting biodiversity observations? How can policy-makers support citizens to collect the data they need? Solutions require two components, a combination of social and technological innovation. Initiatives aimed at supporting decision-making processes should involve more societal actors and be built in a more collaborative or even co-created manner with citizens, scientists, and policy-makers. Technological solutions can be achieved through regular, rapid, and open publication of biodiversity data products. We envisage frequent publication of maps and indicators from rapidly mobilized data, with clear pointers to gaps in knowledge. Improving the links between data collection and delivery of policy-relevant information demonstrates – to citizens and their organizations – the need for their data, and gives them a clear view on the impact of their data on policy. This visibility also empowers stakeholder organizations in the policy development process.

Abstract According to the Convention on Biological Diversity, by 2020 invasive alien species (IAS) should be identified and their impacts assessed, so that species can be prioritized for implementation of appropriate control strategies and measures put in place to manage invasion pathways. For one quarter of the IAS listed as the “100 of the world's worst” environmental impacts are linked to diseases of wildlife (undomesticated plants and animals). Moreover, IAS are a significant source of “pathogen pollution” defined as the human‐mediated introduction of a pathogen to a new host or region. Despite this, little is known about the biology of alien pathogens and their biodiversity impacts after introduction into new regions. We argue that the threats posed by alien pathogens to endangered species, ecosystems, and ecosystem services should receive greater attention through legislation, policy, and management. We identify 10 key areas for research and action, including those relevant to the processes of introduction and establishment of an alien pathogen and to prediction of the spread and associated impact of an alien pathogen on native biota and ecosystems. The development of interdisciplinary capacity, expertise, and coordination to identify and manage threats was seen as critical to address knowledge gaps.

There are a multitude of biodiversity informatics projects, datasets, databases and initiatives at the global level, and many more at regional, national, and sometimes local levels. In such a complex landscape, it can be unclear how different elements relate to each other. Based on a high-level review of global and European-level elements, we present a map of the biodiversity informatics landscape. This is a first attempt at identifying key datasets/databases and data services, and mapping them in a way that can be used to identify the links, gaps and redundancies in the landscape. While the map is predominantly focused on elements with a global scope, the sub-global focus at the European-level was incorporated in the map in order to demonstrate how a regional network such as the European Biodiversity Observation Network (EU BON) can usefully contribute to connecting some of the nodes within the landscape. We identify 74 elements, and find that the informatics landscape is complex in terms of the characteristics and diversity of these elements, and that there is high variability in their level of connectedness. Overall, the landscape is highly connected, with one element boasting 28 connections. The average "degrees of separation" between elements is low, and the landscape is deemed relatively robust to failures since there is no single point that information flows through. Examples of possible effort duplication are presented, and the inclusion of five policy-level elements in the map helps illustrate how informatics products can contribute to global processes that define and direct political targets. Beyond simply describing the existing landscape, this map will support a better understanding of the landscape’s current structure and functioning, enabling responsible institutions to establish or strengthen collaborations, work towards avoiding effort duplication, and facilitate access to the biodiversity data, information and knowledge required to support effective decision-making, in the context of comparatively limited funding for biodiversity knowledge and conservation. To support this, we provide the input matrix and code that created this map as supplementary materials, so that readers can more closely examine the links in the landscape, and edit the map to suit their own purposes.

The EU BON (“Building the European Biodiversity Observation Network”) project has made important contributions towards the achievement of global conservation targets. This infographic illustrates EU BON's contributions towards the achievement of Aichi Biodiversity Target 19 "By 2020, knowledge, the science base and technologies relating to biodiversity, its values, functioning, status and trends, and the consequences of its loss, are improved, widely shared and transferred, and applied.”

The paper provides an updated checklist of the alien flora of Turkey with information on its structure. The alien flora of Turkey comprises 340 taxa, among which there are 321 angiosperms, 17 gymnosperms and two ferns. Of the total number of taxa, 228 (68%) are naturalized and 112 (32%) are casual. There are 275 neophytes (172 naturalized and 103 casual) and 61 archaeophytes (52 naturalized and 9 casual); four species could not be classified with respect to the residence time. In addition, 47 frequently planted taxa with a potential to escape are also listed. The richest families are Asteraceae (38 taxa), Poaceae (30), Fabaceae (23) and Solanaceae (22). As for the naturalized alien plants, the highest species richness is found in Asteraceae (31 taxa), Poaceae (22), Amaranthaceae (18) and Solanaceae (15). The majority of alien taxa are perennial (63.8% of the total number of taxa with this life history assigned, including those with multiple life histories), annuals contribute 33.8% and 2.4% are biennial aliens. Among perennials the most common life forms are phanerophytes, of which 20.3% are trees and 12.6% shrubs; woody vines, stem succulents, and aquatic plants are comparatively less represented. Most of the 340 alien taxa introduced to Turkey have their native ranges in Americas (44.7%) and Asia (27.6%). Of other regions, 9.1% originated in Africa, 4.4% in Eurasia, 3.8% in Australia and Oceania and 3.5% in the Mediterranean. The majority of taxa (71.9%) were introduced intentionally, whereas the remaining (28.1%) were introduced accidentally. Among the taxa introduced intentionally, the vast majority are ornamental plants (55.2%), 10.0% taxa were introduced for forestry and 6.7% as crops. Casual alien plants are most commonly found in urban and ruderal habitats (40.1%) where naturalized taxa are also often recorded (27.3%). Plants that occur as agricultural weeds are typically naturalized rather than casual (16.0% vs 7.1%, respectively). However, (semi)natural habitats in Turkey are often invaded by alien taxa, especially by those that are able to naturalize.

Imagine a future where dynamically, from year to year, we can track the progression of alien species (AS), identify emerging problem species, assess their current and future risk and timely inform policy in a seamless data-driven workflow. One that is built on open science and open data infrastructures. By using international biodiversity standards and facilities, we would ensure interoperability, repeatability and sustainability. This would make the process adaptable to future requirements in an evolving AS policy landscape both locally and internationally. In recent years, Belgium has developed decision support tools to inform invasive alien species (IAS) policy, including information systems, early warning initiatives and risk assessment protocols. However, the current workflows from biodiversity observations to IAS science and policy are slow, not easily repeatable, and their scope is often taxonomically, spatially and temporally limited. This is mainly caused by the diversity of actors involved and the closed, fragmented nature of the sources of these biodiversity data, which leads to considerable knowledge gaps for IAS research and policy. We will leverage expertise and knowledge from nine former and current BELSPO projects and initiatives: Alien Alert, Invaxen, Diars, INPLANBEL, Alien Impact, Ensis, CORDEX.be, Speedy and the Belgian Biodiversity Platform. The project will be built on two components: 1) The establishment of a data mobilization framework for AS data from diverse data sources and 2) the development of data-driven procedures for risk evaluation based on risk modelling, risk mapping and risk assessment. We will use facilities from the Global Biodiversity Information Facility (GBIF), standards from the Biodiversity Information Standards organization (TDWG) and expertise from Lifewatch to create and facilitate a systematic workflow. Alien species data will be gathered from a large set of regional, national and international initiatives, including citizen science with a wide taxonomic scope from marine, terrestrial and freshwater environments. Observation data will be funnelled in repeatable ways to GBIF. In parallel, a Belgian checklist of AS will be established, benefiting from various taxonomic and project-based checklists foreseen for GBIF publication. The combination of the observation data and the checklist will feed indicators for the identification of emerging species; their level of invasion in Belgium; changes in their invasion status and the identification of areas and species of concern that could be impacted upon by bioinvasions. Data-driven risk evaluation of identified emerging species will be supported by niche and climate modelling and consequent risk mapping using critical climatic variables for the current and projected future climate periods at high resolution. The resulting risk maps will complement risk assessments performed with the recently developed Harmonia+ protocol to assess risks posed by emergent species to biodiversity and human, plant, and animal health. The use of open data will ensure that interested stakeholders in Belgium and abroad can make use of the information we generate. The open science ensures everyone is free to adopt and adapt the workflow for different scenarios and regions. The checklist will be used at national level, but will also serve as the Belgian reference for international databases (IUCN - GRIIS, EASIN) and impact assessments (IPBES, SEBI). The workflow will be showcased through GEO BON, the Invasivesnet network and the COST Actions Alien Challenge and ParrotNet. The observations and outcomes of risk evaluations will be used to provide science-based support for the implementation of IAS policies at the regional, federal and EU levels. The publication of Belgian data and checklists on IAS is particularly timely in light of the currently ongoing EU IAS Regulation and its implementation in Belgium. By proving that automated workflows can provide rapid and repeatable production of information, we will open up this technology for other conservation assessments.

The digitization of herbaria and their online access will greatly facilitate access to plant collections around the world. This will improve the efficiency of taxonomy and help reduce inequalities between scientists. The Botanic Garden Meise, Belgium, is currently digitizing 1.2 million specimens including label data. In this paper we describe the user requirements analysis conducted for a new herbarium web portal. The aim was to identify the required functionality, but also to assist in the prioritization of software development and data acquisition. The Garden conducted the analysis in cooperation with Clockwork, the digital engagement agency of Ordina. Using a series of interactive interviews, potential users were consulted from universities, research institutions, science-policy initiatives and the Botanic Garden Meise. Although digital herbarium data have many potential stakeholders, we focused on the needs of taxonomists, ecologists and historians, who are currently the primary users of the Meise herbarium data portal. The three categories of user have similar needs, all wanted as much specimen data as possible, and for those data, to be interlinked with other digital resources within and outside the Garden. Many users wanted an interactive system that they could comment on, or correct online, particularly if such corrections and annotations could be used to rank the reliability of data. Many requirements depend on the quality of the digitized data associated with each specimen. The essential data fields are the taxonomic name; geographic location; country; collection date; collector name and collection number. Also all researchers valued linkage between biodiversity literature and specimens. Nevertheless, to verify digitized data the researchers still want access to high quality images, even if fully transcribed label information is provided. The only major point of disagreement is the level of access users should have and what they should be allowed to do with the data and images. Not all of the user requirements are feasible given the current technical and regulatory landscape, however, the potential of these suggestions is discussed. Currently, there is no off-the-shelf solution to satisfy all these user requirements, but the intention of this paper is to guide other herbaria who are prioritising their investment in digitization and online web functionality.

The present paper describes policies and guidelines for scholarly publishing of biodiversity and biodiversity-related data, elaborated and updated during the Framework Program 7 EU BON project, on the basis of an earlier version published on Pensoft's website in 2011. The document discusses some general concepts, including a definition of datasets, incentives to publish data and licenses for data publishing. Further, it defines and compares several routes for data publishing, namely as (1) supplementary files to research articles, which may be made available directly by the publisher, or (2) published in a specialized open data repository with a link to it from the research article, or (3) as a data paper, i.e., a specific, stand-alone publication describing a particular dataset or a collection of datasets, or (4) integrated narrative and data publishing through online import/download of data into/from manuscripts, as provided by the Biodiversity Data Journal. The paper also contains detailed instructions on how to prepare and peer review data intended for publication, listed under the Guidelines for Authors and Reviewers, respectively. Special attention is given to existing standards, protocols and tools to facilitate data publishing, such as the Integrated Publishing Toolkit of the Global Biodiversity Information Facility (GBIF IPT) and the DarwinCore Archive (DwC-A). A separate section describes most leading data hosting/indexing infrastructures and repositories for biodiversity and ecological data.

Essential Biodiversity Variables (EBVs) are measurements required for study, reporting, and management of biodiversity change. They are being developed to support consistency, from the collection to the reporting of biodiversity data at the national, regional and global scales. However, "EBV stakeholders" need to strike a balance between 'doing innovative research' and 'having positive impact' on biodiversity management decisions. This paper reports on a workshop entitled Identifying joint pathways to address the challenges of biodiversity data provision and decision-making and presents the main workshop’s output, a “researcher’s brief” entitled Guiding principles for promoting the application of EBVs for current and future needs of decision-makers. These guiding principles are: Speak with a common voice; Clearly define what is an EBV and how it relates to indicators; Engage beyond the research world; Be realistic about what can be done now and later; Define criteria for good EBVs; Use EBV as a clearing house; Convey the limitations of EBVs; Clarify what impact EBVs should have; Be salient, credible, legitimate, iterative; Don't put an EBV skin on everything you do; Don't create too many EBVs; and Don't reduce EBVs to building blocks of indicators. This brief is of relevance to the wider GEO BON (Group on Earth Observation Biodoversity Observation Network) community, and in particular those scientists/researchers interested in the application of EBVs.

Citizen science is an approach of public participation in scientific research which has gained significant momentum in recent years. This is particularly evident in biology and environmental sciences where input from citizen scientists has greatly increased the number of publicly available observation data. However, there are still challenges in effective networking, data sharing and securing data quality. EU BON project has analyzed the citizen science landscape in Europe with regards to biodiversity research and proposes several policy recommendations. One of the recommendations is a Pan-European citizen science gateway for biodiversity data with dedicated tools for data collection and management. The prototypes of the gateway components are part of the EU BON biodiversity portal and described in current report.

Europe is building its Open Science Cloud; a set of robust and interoperable e-infrastructures with the capacity to provide data and computational solutions through cloud-based services. The development and sustainable operation of such e-infrastructures are at the forefront of European funding priorities. The research community, however, is still reluctant to engage at the scale required to signal a Europe-wide change in the mode of operation of scientific practices. The striking differences in uptake rates between researchers from different scientific domains indicate that communities do not equally share the benefits of the above European investments. We highlight the need to support research communities in organically engaging with the European Open Science Cloud through the development of trustworthy and interoperable Virtual Research Environments. These domain-specific solutions can support communities in gradually bridging technical and socio-cultural gaps between traditional and open digital science practice, better diffusing the benefits of European e-infrastructures.

A fundamental constituent of a biodiversity observation network is the technological infrastructure that underpins it. The European Biodiversity Network project (EU BON) has been working with and improving upon pre-existing tools for data mobilization, sharing and description. This paper provides conceptual and practical advice for the use of these tools. We review tools for managing metadata, occurrence data, and ecological data and give detailed description of these tools, their capabilities and limitations. This is followed by recommendations on their deployment and possible future enhancements. This is done from the perspective of the needs of the biodiversity observation community with a view to the development of a unified user interface to these data – the European Biodiversity Portal (EBP). We described the steps taken to develop, adapt, deploy and test these tools. This document also gives an overview of the objectives that still need to be achieved and challenges to be addressed for the remainder of the project.