A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo)

Persistent identifiers (PID) to identify digital representations of physical specimens in natural science collections (i.e., digital specimens) unambiguously and uniquely on the Internet are one of the mechanisms for digitally transforming collections-based science. Digital Specimen PIDs contribute to building and maintaining long-term community trust in the accuracy and authenticity of the scientific data to be managed and presented by the Distributed System of Scientific Collections (DiSSCo) research infrastructure planned in Europe to commence implementation in 2024. Not only are such PIDs valid over the very long timescales common in the heritage sector but they can also transcend changes in underlying technologies of their implementation. They are part of the mechanism for widening access to natural science collections. DiSSCo technical experts previously selected the Handle System as the choice to meet core PID requirements. Using a two-step approach, this options appraisal captures, characterises and analyses different alternative Handle-based PID schemes and the possible operational modes of use. In a first step a weighting and ranking the options has been applied followed by a structured qualitative assessment of social and technical compliance across several assessment dimensions: levels of scalability, community trust, persistence, governance, appropriateness of the scheme and suitability for future global adoption. The results are discussed in relation to branding, community perceptions and global context to determine a preferred PID scheme for DiSSCo that also has potential for adoption and acceptance globally. DiSSCo will adopt a ‘driven-by DOI’ persistent identifier (PID) scheme customised with natural sciences community characteristics. Establishing a new Registration Agency in collaboration with the International DOI Foundation is a practical way forward to support the FAIR (findable, accessible interoperable, reusable) data architecture of DiSSCo research infrastructure. This approach is compatible with the policies of the European Open Science Cloud (EOSC) and is aligned to existing practices across the global community of natural science collections

Highlights and outcomes of the 2021 Global Community Consultation

International collaboration between collections, aggregators, and researchers within the biodiversity community and beyond is becoming increasingly important in our efforts to support biodiversity, conservation and the life of the planet. The social, technical, logistical and financial aspects of an equitable biodiversity data landscape – from workforce training and mobilization of linked specimen data, to data integration, use and publication – must be considered globally and within the context of a growing biodiversity crisis. In recent years, several initiatives have outlined paths forward that describe how digital versions of natural history specimens can be extended and linked with associated data. In the United States, Webster (2017) presented the “extended specimen”, which was expanded upon by Lendemer et al. (2019) through the work of the Biodiversity Collections Network (BCoN). At the same time, a “digital specimen” concept was developed by DiSSCo in Europe (Hardisty 2020). Both the extended and digital specimen concepts depict a digital proxy of an analog natural history specimen, whose digital nature provides greater capabilities such as being machine-processable, linkages with associated data, globally accessible information-rich biodiversity data, improved tracking, attribution and annotation, additional opportunities for data use and cross-disciplinary collaborations forming the basis for FAIR (Findable, Accessible, Interoperable, Reproducible) and equitable sharing of benefits worldwide, and innumerable other advantages, with slight variation in how an extended or digital specimen model would be executed. Recognizing the need to align the two closely-related concepts, and to provide a place for open discussion around various topics of the Digital Extended Specimen (DES; the current working name for the joined concepts), we initiated a virtual consultation on the discourse platform hosted by the Alliance for Biodiversity Knowledge through GBIF. This platform provided a forum for threaded discussions around topics related and relevant to the DES. The goals of the consultation align with the goals of the Alliance for Biodiversity Knowledge: expand participation in the process, build support for further collaboration, identify use cases, identify significant challenges and obstacles, and develop a comprehensive roadmap towards achieving the vision for a global specification for data integration. In early 2021, Phase 1 launched with five topics: Making FAIR data for specimens accessible; Extending, enriching and integrating data; Annotating specimens and other data; Data attribution; and Analyzing/mining specimen data for novel applications. This round of full discussion was productive and engaged dozens of contributors, with hundreds of posts and thousands of views. During Phase 1, several deeper, more technical, or additional topics of relevance were identified and formed the foundation for Phase 2 which began in May 2021 with the following topics: Robust access points and data infrastructure alignment; Persistent identifier (PID) scheme(s); Meeting legal/regulatory, ethical and sensitive data obligations; Workforce capacity development and inclusivity; Transactional mechanisms and provenance; and Partnerships to collaborate more effectively. In Phase 2 fruitful progress was made towards solutions to some of these complex functional and technical long-term goals. Simultaneously, our commitment to open participation was reinforced, through increased efforts to involve new voices from allied and complementary fields. Among a wealth of ideas expressed, the community highlighted the need for unambiguous persistent identifiers and a dedicated agent to assign them, support for a fully linked system that includes robust publishing mechanisms, strong support for social structures that build trustworthiness of the system, appropriate attribution of legacy and new work, a system that is inclusive, removed from colonial practices, and supportive of creative use of biodiversity data, building a truly global data infrastructure, balancing open access with legal obligations and ethical responsibilities, and the partnerships necessary for success. These two consultation periods, and the myriad activities surrounding the online discussion, produced a wide variety of perspectives, strategies, and approaches to converging the digital and extended specimen concepts, and progressing plans for the DES -- steps necessary to improve access to research-ready data to advance our understanding of the diversity and distribution of life. Discussions continue and we hope to include your contributions to the DES in future implementation plans

Digital Extended Specimens: Enabling an Extensible Network of Biodiversity Data Records as Integrated Digital Objects on the Internet

The early twenty-first century has witnessed massive expansions in availability and accessibility of digital data in virtually all domains of the biodiversity sciences. Led by an array of asynchronous digitization activities spanning ecological, environmental, climatological, and biological collections data, these initiatives have resulted in a plethora of mostly disconnected and siloed data, leaving to researchers the tedious and time-consuming manual task of finding and connecting them in usable ways, integrating them into coherent data sets, and making them interoperable. The focus to date has been on elevating analog and physical records to digital replicas in local databases prior to elevating them to ever-growing aggregations of essentially disconnected discipline-specific information. In the present article, we propose a new interconnected network of digital objects on the Internet—the Digital Extended Specimen (DES) network—that transcends existing aggregator technology, augments the DES with third-party data through machine algorithms, and provides a platform for more efficient research and robust interdisciplinary discovery

The senescent secretome drives PLVAP expression in cultured human hepatic endothelia to promote monocyte transmigration

Liver sinusoidal endothelial cells (LSEC) undergo significant phenotypic change in chronic liver disease (CLD), and yet the factors that drive this process and the impact on their function as a vascular barrier and gatekeeper for immune cell recruitment are poorly understood. Plasmalemma-vesicle-associated protein (PLVAP) has been characterized as a marker of LSEC in CLD; notably we found that PLVAP upregulation strongly correlated with markers of tissue senescence. Furthermore, exposure of human LSEC to the senescence-associated secretory phenotype (SASP) led to a significant upregulation of PLVAP. Flow-based assays demonstrated that SASP-driven leukocyte recruitment was characterized by paracellular transmigration of monocytes while the majority of lymphocytes migrated transcellularly. Knockdown studies confirmed that PLVAP selectively supported monocyte transmigration mediated through PLVAP's impact on LSEC permeability by regulating phospho-VE-cadherin expression and endothelial gap formation. PLVAP may therefore represent an endothelial target that selectively shapes the senescence-mediated immune microenvironment in liver disease. [Abstract copyright: © 2023 The Author(s).

Community engagement: The ‘last mile’ challenge for European research e-infrastructures

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

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

Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a 'Big Data' approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence-absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals

BioVeL : a virtual laboratory for data analysis and modelling in biodiversity science and ecology

Background: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. Results: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on- line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Conclusions: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.Peer reviewe