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At least 29% of the world’s terrestrial ecosystems have been significantly modified by human activity (Ellis 2011). Total livestock biomass is 15 times greater than that of wild mammals (Bar-On et al. 2018). Crops such as maize, soybean, rice, and wheat cover 23% of available agricultural land (Ritchie and Roser 2013). Even where land is not farmed, it is often converted to highly modified habitats such as urban ecosystems. Within the matrix of anthropogenic ecosystems spread around the world are many wild species (i.e., free-living, non-domesticated or feral). Some native species persist from the original ecosystems, while others colonize anthropogenic ecosystems including alien invasive species. Thus, wild flora and fauna in many areas are part of ecosystems that are dominated by, and often characterised by, the domestic and cultivated organisms that exist in them. Examples include large herbivores raised for milk and meat production, and omnivorous and carnivorous species such as both domestic and feral dogs and cats. Moreover, crops are typically grown in monoculture plots including tree plots in commercial forestry, and an enormous array of cultivated plants are grown in gardens, parks, and along streets in urban areas. Tellingly, in many ecosystems the domestic bee is the primary pollinator and domestic cats are the main predator. Domestic and cultivated organisms are not isolated from wild organisms and indeed they interact in many ways, including predation, parasitism, and herbivory, competition for biotic and abiotic resources, and pathogen transmission. If we are to understand modern ecosystems, clearly we cannot ignore the domesticated and cultivated components of ecosystems. So where are the observational data on these species? iNaturalist reluctantly tolerates them but does not publish them to the Global Biodiversity Information Facility (GBIF), eBird actively discourages recording them, and GBIF doesn’t encourage their submission either. Some information can be gleaned from land cover maps and remote sensing, but without knowing the specific species present in the land use category it is hard to build a holistic picture of an ecosystem. Data on domesticated and cultivated organisms have many uses, including horizon scanning and risk assessment for invasive species, understanding the impacts of invasive species, predicting the spread of disease, the spillover of disease to and from wild and domestic organisms, and many others (Groom et al. 2021). Evidently there are important components of ecosystems largely missing from our public databases. As data on biodiversity becomes more intergrated, such as implementing Digital Extended Specimens (Webster et al. 2021), it will become increasingly important to access data from all aspects of an ecosystem, included those that are domestic and cultivated. In this talk we will expand on why we should be mobilising such data. They can be published without ruining the integrity of data on wild organisms, so why don’t we embrace and use these fundamentally important, but much ignored, data?

Natural history collections play a pivotal role in taxonomy, which in turn supports all of biology, but particularly conservation and biodiversity policy. However, to provide this role, it is necessary to know what specimens are stored where, and how complete the collection is. The biodiversity held within collections globally remains uncertain, with an estimated 1.2 to 2.1 billion (109) specimens (Ariño 2010), of which around 200 million are represented on the Global Biodiversity Information Facility (GBIF). Here we estimate the total biodiversity in collections worldwide by extrapolating from those specimens we know about. Data aggregators such as GBIF provide an ever-changing window into the contents of collections. We use non-parametric estimators that allow for the approximation of the number of classes in an incomplete set, such as the number of species within a collection, but also the proportion of biodiversity preserved on a national or continental level (for example within a taxonomic group, compared to the world or to a continent). Because the contents of data aggregators such as GBIF, are in constant flux, our workflow is made to be repeatable on the monthly snapshots that GBIF provides. The results of the workflow expose data gaps in GBIF, namely that collections from some large geographical regions, such as Asia, are poorly represented, but also taxonomic gaps exist, such as several Coleoptera families where many more species are accepted in the backbone than are represented on GBIF. As more data are published to GBIF the estimates for these taxon groups and geographical regions will improve. The detection of data gaps within data aggregators such as GBIF, and the subsequent mobilisation of missing information remains a priority for both aggregators and researchers (GBIF Secretariat 2022, Collen et al. 2008, Hochkirch et al. 2020). Our workflow will allow for continuous monitoring of collections and groups of collections of their coverage of global biodiversity, and the results can inform their collection development strategy.

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

DiSSCo Flanders aims at developing a standardised natural science collections management infrastructure, ensuring proper long-term conservation, and future re-usage of the collections. Meise Botanic Garden coordinates the Flemish consortium. This four-year project, funded by the FWO (Research Foundation – Flanders), started in January 2021. The consortium brings together both the more classical ‘museum’ collections (Meise Botanic Garden, Ghent University Museum), with research collections (Research Institute for Nature and Forest, Flanders Research Institute for Agriculture, Fisheries and Food, Flanders Marine Institute, universities), and living collections (Belgian Association of Botanic Gardens and Arboreta, Zoo of Antwerp (Poo 2022)). Many of the research collections are smaller orphan collections, lacking a (full-time) curator, for which collection management is not the core business of the hosting institute. The Belgian federal DiSSCo members are associated with the project, allowing close collaboration between European, national and regional (digital) collection management inititatives. Building on the expertise of the European DiSSCo-related projects, an initial high-level inventory and assessment of the collections has been made and will provide a better understanding of the collections landscape in Flanders (Van Baelen 2022). This step in the digitization will increase the findability of the diverse regional collections and highlight the available knowledge to the research community. Close collaboration with the TDWG Collections Descriptions interest group and the development of the Latimer Core standard (Woodburn 2021) will ensure maximal interoperability of the collection data. In order to be relevant for research, the Flemish collections need to be more interconnected and linked to other data sources. To ensure that collection data is adhering to the FAIR principles (Findable, Accessible, Interoperable and Resuable) and ready to connect to the DiSSCo research infrastructure, DiSSCo Flanders will have a large focus on the collection(s) management system (CMS). Depending on the needs and specificities of each collection, a strategy will be chosen to implement and/or collection data will be migrated to (an) optimised system(s). Parallel to the digital inventory and CMS choice, the consortium addresses specific themes in the format of working groups. Most of the institutes have identified that their molecular collection (DNA, tissues) has not been properly acknowledged as a separate long-term collection. Challenges such as the storage and curation of e-DNA and environmental samples (e.g., soil) have been identified. Very often it will only be feasible to add basic data in the CMS and essential data is not available to the researchers. DiSSCo Flanders invests in the enrichment of specimen data to ensure that a maximal amount of information becomes available to the community. This can be accomplished either through the use of citizen science/crowdsourcing using the DoeDat platform (Groom 2018), or by using machine learning techniques performed by the IDLab at Ghent University (Thirukokaranam Chandrasekar 2021). Besides the technical aspects of the DiSSCo research infrastructure, the consortium is covering topics such as data publication, legal aspects of collections, standard operating procedures, etc. through knowledge sharing and active dialog.

The BiCIKL Project is born from a vision that biodiversity data are most useful if they are viewed as a network of data that can be integrated and viewed from different starting points. BiCIKL’s goal is to realize that vision by linking biodiversity data infrastructures, particularly for literature, molecular sequences, specimens, nomenclature and analytics. BiCIKL is an Open Science project creating Open FAIR data and services for the whole research community. BiCIKL intends to inspire novel, innovative, research and build services that can produce new and valuable knowledge, necessary for the protection of biodiversity and of our environment. BiCIKL will develop methods and workflows to harvest, link and access data extracted from literature. Yet, as the project gets underway, 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. To do this we organised a week-long hackathon where small teams worked on a number of pilot projects (Table 1) that were chosen to test the existing linkages between infrastructures and to extract novel ones. We will present our experience of running a hackathon and our evaluation of how successfully it achieved its aims. We will also give examples of the projects we conducted and how successful they were. Finally we will give our preliminary evaluation of what we learned about the interoperability of infrastructures and what recommendations we can give to improve their interoperability, whether that is improvements to the data standards used, the means to access the data and analyse them, or even the physical bandwidth and computational restrictions that limit the potential for research.

There are an estimated 8.7 million eukaryotic species globally and knowledge of those organisms is organised about their scientific names and the specimens we have of those species (Sweetlove 2011, Mora et al. 2011). Likewise there are between 1.2 and 2.1 billion (109) specimens held in biodiversity collections globally (Ariño 2010). These collections constitute an infrastructure and scientific tool to understand, catalogue and study biodiversity. Yet we find it hard to answer the simple question, how many species are in a collection? This is not trivial to answer, collections are not completely inventoried, do not use the same taxonomy, and the volume of data is vast (Samy et al. 2013, Ariño 2010). We have developed a method that allows us to take a list of collections and to estimate the species richness contained within them. By doing this we will have a deeper insight into the scientific value of the world's biodiversity collections. Dealing with non-homogeneous and non-random, but incomplete, sampling of sites is a common issue that occurs in many ecological studies (Magurran and McGill 2011, Colwell et al. 2012, Gotelli and Colwell 2001). By using techniques and toolboxes, such as iNEXT (Chao et al. 2014b) and vegan (Oksanen et al. 2020) we can estimate species richness under these conditions. In the case of collections we consider not only the digitized and published proportion of preserved collections, but make extrapolations to the specimens that have not made their way to the Global Biodiversity Information Facility (GBIF) yet. Nevertheless, to calculate on such large datasets we need to employ innovative Big Data analytic tools. GBIF contains 1.8 billion observations that amount to 120 GB of data compressed. This can then be interrogated in the cloud or locally using tools such as Galaxy, which has made it possible to process large numbers of records in a single batch. We can now evaluate the biodiversity within collections, and divide the result by taxon and geographical region, and compare them to one another. Ultimately, this work will allow individual collections and consortia to evaluate their coverage of biodiversity and help them better target their collecting strategies.

The utopian vision is of a future where a digital representation of each object in our collections is accessible through the internet and sustainably linked to other digital resources. This is a long term goal however, and in the meantime there is an urgent need to share data about our collections at a higher level with a range of stakeholders (Woodburn et al. 2020). To sustainably achieve this, and to aggregate this information across all natural science collections, the data need to be standardised (Johnston and Robinson 2002). To this end, the Biodiversity Information Standards (TDWG) Collection Descriptions (CD) Interest Group has developed a data standard for describing collections, which is approaching formal review for ratification as a new TDWG standard. It proposes 20 classes (Suppl. material 1) and over 100 properties that can be used to describe, categorise, quantify, link and track digital representations of natural science collections, from high-level approximations to detailed breakdowns depending on the purpose of a particular implementation. The wide range of use cases identified for representing collection description data means that a flexible approach to the standard and the underlying modelling concepts is essential. These are centered around the ‘ObjectGroup’ (Fig. 1), a class that may represent any group (of any size) of physical collection objects, which have one or more common characteristics. This generic definition of the ‘collection’ in ‘collection descriptions’ is an important factor in making the standard flexible enough to support the breadth of use cases. For any use case or implementation, only a subset of classes and properties within the standard are likely to be relevant. In some cases, this subset may have little overlap with those selected for other use cases. This additional need for flexibility means that very few classes and properties, representing the core concepts, are proposed to be mandatory. Metrics, facts and narratives are represented in a normalised structure using an extended MeasurementOrFact class, so that these can be user-defined rather than constrained to a set identified by the standard. Finally, rather than a rigid underlying data model as part of the normative standard, documentation will be developed to provide guidance on how the classes in the standard may be related and quantified according to relational, dimensional and graph-like models. So, in summary, the standard has, by design, been made flexible enough to be used in a number of different ways. The corresponding risk is that it could be used in ways that may not deliver what is needed in terms of outputs, manageability and interoperability with other resources of collection-level or object-level data. To mitigate this, it is key for any new implementer of the standard to establish how it should be used in that particular instance, and define any necessary constraints within the wider scope of the standard and model. This is the concept of the ‘collection description scheme,’ a profile that defines elements such as: which classes and properties should be included, which should be mandatory, and which should be repeatable; which controlled vocabularies and hierarchies should be used to make the data interoperable; how the collections should be broken down into individual ObjectGroups and interlinked, and how the various classes should be related to each other. which classes and properties should be included, which should be mandatory, and which should be repeatable; which controlled vocabularies and hierarchies should be used to make the data interoperable; how the collections should be broken down into individual ObjectGroups and interlinked, and how the various classes should be related to each other. Various factors might influence these decisions, including the types of information that are relevant to the use case, whether quantitative metrics need to be captured and aggregated across collection descriptions, and how many resources can be dedicated to amassing and maintaining the data. This process has particular relevance to the Distributed System of Scientific Collections (DiSSCo) consortium, the design of which incorporates use cases for storing, interlinking and reporting on the collections of its member institutions. These include helping users of the European Loans and Visits System (ELViS) (Islam 2020) to discover specimens for physical and digital loans by providing descriptions and breakdowns of the collections of holding institutions, and monitoring digitisation progress across European collections through a dynamic Collections Digitisation Dashboard. In addition, DiSSCo will be part of a global collections data ecosystem requiring interoperation with other infrastructures such as the GBIF (Global Biodiversity Information Facility) Registry of Scientific Collections, the CETAF (Consortium of European Taxonomic Facilities) Registry of Collections and Index Herbariorum. In this presentation, we will introduce the draft standard and discuss the process of defining new collection description schemes using the standard and data model, and focus on DiSSCo requirements as examples of real-world collection descriptions use cases.

When sequencing molecules from an organism it is standard practice to create voucher specimens. This ensures that the results are repeatable and that the identification of the organism can be verified. It also means that the sequence data can be linked to a whole host of other data related to the specimen, including traits, other sequences, environmental data, and geography. It is therefore critical that explicit, preferably machine readable, links exist between voucher specimens and sequence. However, such links do not exist in the databases of the International Nucleotide Sequence Database Collaboration (INSDC). If it were possible to create permanent bidirectional links between specimens and sequence it would not only make data more findable, but would also open new avenues for research. In the Biohackathon we built a semi-automated workflow to take specimen data from the Meise Herbarium and search for references to those specimens in the European Nucleotide Archive (ENA). We achieved this by matching data elements of the specimen and sequence together and by adding a “human-in-the-loop” process whereby possible matches could be confirmed. Although we found that it was possible to discover and match sequences to their vouchers in our collection, we encountered many problems of data standardization, missing data and errors. These problems make the process unreliable and unsuitable to rediscover all the possible links that exist. Ultimately, improved standards and training would remove the need for retrospective relinking of specimens with their sequence. Therefore, we make some tentative recommendations for how this could be achieved in the future.

Many institutions harbor living collections in the form of living plants, animals, microrganisms or seeds. In the framework of the TDWG collections and specimen descriptions standards, it has become important to align exisiting standards for living collections and specimens or to identify where concepts or controlled vocabularies would be needed in the current TDWG standards. In September 2021 a workshop was organized in the framework of the COST Action Mobilise (https://www.mobilise-action.eu/) to get a better common understanding of the different types of living collections to consider and set the scene for further work on standards alignments. The EU COST Action CA17106 on “Mobilising Data, Experts and Policies in Scientific Collections”. Invited experts to these workshop were representatives of the TDWG Collection Description Group, the GGBN and TDWG molecular collections group, living plants collections and seed banks (Botanic Gardens Conservation International: BGCI, https://www.bgci.org/), living animal and biobanks (European Association of Zoos and Aquaria: EAZA, https://www.eaza.net/) and the culture collections (World Federation for Culture Collections: WFCC, http://www.wfcc.info/), who gave presentations on their currently used standards and challenges. The second day was devoted to break out sessions to brainstorm the specific needs for the different living collections with the aim to check and update the controlled vocabularies and concepts as needed. Identified topics were : Session 1: Voucher specimens of living accessions. Session 2: Living collections and GBIF. Session 3: How do we compare botanical gardens with herbaria? Session 4: How do we compare zoos and aquaria with natural history collections? Session 5: Culture collections: best practices and guidelines. Session 1: Voucher specimens of living accessions. Session 2: Living collections and GBIF. Session 3: How do we compare botanical gardens with herbaria? Session 4: How do we compare zoos and aquaria with natural history collections? Session 5: Culture collections: best practices and guidelines. The goal of this presentation is to address the outcome of these sessions and recommend future steps in collaboration with TDWG and the different identified stakeholders.

Digitisation and publication of museum specimen data is happening worldwide, but far from complete. Museums can start by sharing what they know about their holdings at a higher level, long before each object has its own record. Information about what is held in collections worldwide is needed by many stakeholders including collections managers, funders, researchers, policy-makers, industry, and educators. To aggregate this information from collections, the data need to be standardised (Johnston and Robinson 2002). So, the Biodiversity Information Standards (TDWG) Collection Descriptions (CD) Task Group is developing a data standard for describing collections, which gives the ability to provide: automated metrics, using standardised collection descriptions and/or data derived from specimen datasets (e.g., counts of specimens) and a global registry of physical collections (i.e., digitised or non-digitised). automated metrics, using standardised collection descriptions and/or data derived from specimen datasets (e.g., counts of specimens) and a global registry of physical collections (i.e., digitised or non-digitised). Outputs will include a data model to underpin the new standard, and guidance and reference implementations for the practical use of the standard in institutional and collaborative data infrastructures. The Task Group employs a community-driven approach to standard development. With international participation, workshops at the Natural History Museum (London 2019) and the MOBILISE workshop (Warsaw 2020) allowed over 50 people to contribute this work. Our group organized online "barbecues" (BBQs) so that many more could contribute to standard definitions and address data model design challenges. Cloud-based tools (e.g., GitHub, Google Sheets) are used to organise and publish the group's work and make it easy to participate. A Wikibase instance is also used to test and demonstrate the model using real data. There are a range of global, regional, and national initiatives interested in the standard (see Task Group charter). Some, like GRSciColl (now at the Global Biodiversity Information Facility (GBIF)), Index Herbariorum (IH), and the iDigBio US Collections List are existing catalogues. Others, including the Consortium of European Taxonomic Facilities (CETAF) and the Distributed System of Scientific Collections (DiSSCo), include collection descriptions as a key part of their near-term development plans. As part of the EU-funded SYNTHESYS+ project, GBIF organized a virtual workshop: Advancing the Catalogue of the World's Natural History Collections to get international input for such a resource that would use this CD standard. Some major complexities present themselves in designing a standardised approach to represent collection descriptions data. It is not the first time that the natural science collections community has tried to address them (see the TDWG Natural Collections Description standard). Beyond natural sciences, the library community in particular gave thought to this (Heaney 2001, Johnston and Robinson 2002), noting significant difficulties. One hurdle is that collections may be broken down into different degrees of granularity according to different criteria, and may also overlap so that a single object can be represented in more than one collection description. Managing statistics such as numbers of objects is complex due to data gaps and variable degrees of certainty about collection contents. It also takes considerable effort from collections staff to generate structured data about their undigitised holdings. We need to support simple, high-level collection summaries as well as detailed quantitative data, and to be able to update as needed. We need a simple approach, but one that can also handle the complexities of data, scope, and social needs, for digitised and undigitised collections. The data standard itself is a defined set of classes and properties that can be used to represent groups of collection objects and their associated information. These incorporate common characteristics ('dimensions') by which we want to describe, group and break down our collections, metrics for quantifying those collections, and properties such as persistent identifiers for tracking collections and managing their digital counterparts. Existing terms from other standards (e.g. Darwin Core, ABCD) are re-used if possible. The data model (Fig. 1) underpinning the standard defines the relationships between those different classes, and ensures that the structure as well as the content are comparable across different datasets. It centres around the core concept of an 'object group', representing a set of physical objects that is defined by one or more dimensions (e.g., taxonomy and geographic origin), and linked to other entities such as the holding institution. To the object group, quantitative data about its contents are attached (e.g. counts of objects or taxa), along with more qualitative information describing the contents of the group as a whole. In this presentation, we will describe the draft standard and data model with examples of early adoption for real-world and example data. We will also discuss the vision of how the new standard may be adopted and its potential impact on collection discoverability across the collections community.

Data standards allow us to aggregate, compare, compute and communicate data from a wide variety of origins. However, for historical reasons, data are most likely to be stored in many different formats and conform to different models. Every data set might contain a huge amount of information, but it becomes tremendously difficult to compare them without a common way to represent the data. That is when standards development jumps in. Developing a standard is a formidable process, often involving many stakeholders. Typically the initial blueprint of a standard is created by a limited number of people who have a clear view of their use cases. However, as development continues, additional stakeholders participate in the process. As a result, conflicting opinions and interests will influence the development of the standard. Compromises need to be made and the standard might look very different from the initial concept. In order to address the needs of the community, a high level of engagement in the development process is encouraged. However, this does not necessarily increase the usability of the standard. To mitigate this, there is a need to test the standard during the early stages of development. In order to facilitate this, we explored the use of Wikibase to create an initial implementation of the standard. Wikibase is the underlying technology that drives Wikidata. The software is open-source and can be customized for creating collaborative knowledge bases. In addition to containing an RDF (Resource Description Framework) triple store under the hood, it provides users with an easy-to-use graphical user interface (see Fig. 1). This facilitates the use of an implementation of a standard by non-technical users. The Wikibase remains fully flexible in the way data are represented and no data model is enforced. This allows users to map their data onto the standard without any restrictions. Retrieving information from RDF data can be done through the SPARQL query language (W3C 2020). The software package has also a built-in SPARQL endpoint, allowing users to extract the relevant information: Does the standard cover all use cases envisioned? Are parts of the standard underdeveloped? Are the controlled vocabularies sufficient to describe the data? Does the standard cover all use cases envisioned? Are parts of the standard underdeveloped? Are the controlled vocabularies sufficient to describe the data? This strategy was applied during the development of the TDWG Collection Description standard. After completing a rough version of the standard, the different terms that were defined in the first version were transferred to a Wikibase instance running on WBStack (Addshore 2020). Initially, collection data were entered manually, which revealed several issues. The Wikibase allowed us to easily define controlled vocabularies and expand them as needed. The feedback reported from users then flowed back to the further development of the standard. Currently we envisage creating automated scripts that will import data en masse from collections. Using the SPARQL query interface, it will then be straightforward to ensure that data can be extracted from the Wikibase to support the envisaged use cases.

Discussions about the need to document and describe collections at a gross level have been in progress for at least two decades. The original form was the 2008 Natural Collection Description (NCD), which was never ratified. Although a number of implementations were set up using it, it was by and large, acknowledged to be cumbersome and out-of-date even at inception. Over the past three years there has been a concerted effort by the Collection Description Standard (CD) Interest Group to rationalise and create a practical and usable formulation. This presentation describes its use to document the real collections of the Field Museum. We attempted to model a set of Collections Description records by using a range of organizational levels within the Field Museum Collections, beginning at the institution-level by referencing the "Field Museum of Natural History" Global Registry of Scientific Collections (GrSciColl) record, and including its departments (e.g., "Zoology Collections"), collections (e.g., "Invertebrates Collection"), and more specific accessions (e.g., "Philip Carpenter Collection"). We then added our modeled records to a CD Wikibase site developed by Maarten Trekels to see how the CD standard could work in that system. No underlying structure was in place in Wikibase, and this allowed us to compare interpretations. It became clear very soon into the process that it was imperative to understand and clearly map out the connections between records at the different levels before attempting data entry. It was not a fun surprise as an afterthought and so systems built to implement this standard will need clear guidance on preparatory steps for data validation. In some cases, data fit easily into the CD fields as defined, but others were more complex to think about and manipulate. Further issues included fields duplicated unnecessarily between dimensions, and some fields missing entirely. It was also difficult to compare and match newly defined terms for describing the standard (e.g., Dimension and Class) with terms defined by Wikibase (e.g., Item and property). Some aspects of the standard were confusing especially where museum concept and research needs were less than obviously aligned. Ultimately we need something useful for researchers and understandable by Collection staff. Overall, documentation beyond plain field definitions needs to be included with the release of the standard. It should contain, but not be limited to, required core fields, fields needed to create hierarchical relationships, definitions of the difference between hierarchical and lateral relationships and resource roles associated with dimensions. Examples are also needed regarding how to plan and structure CD records that represent a complex collection. We foresee a need for extensive documentation to spare users difficulty and ultimately make the standard more usable.

The coexistence of superconductivity and ferromagnetism is investigated in granular Sn-Co nanocomposites. The nanocomposites have been prepared by co-deposition of Sn atoms and Co clusters, the morphology and composition of which can be tuned by varying the deposition rate of Co clusters relative to Sn atoms. Flat isolated Sn islands are obtained at zero or low Co cluster flux, while granular nanocomposites are formed with increasing Co cluster flux, reaching Co concentrations up to 44 vol.%. Interfaces with a low electronic transparency between superconductor and ferromagnet are obtained by a combination of the granular nature of the nanocomposites and the formation of Sn-Co alloys at the Sn/Co interfaces. The structure and composition of the nanocomposites have been thoroughly characterized by atomic force microscopy, x-ray diffraction and conversion electron Mössbauer spectroscopy. Over the entire Co concentration range, the hybrids show a ferromagnetic response. The superconducting phase boundary and the Meissner response depend on the morphology and composition of the nanocomposites. In particular, the superconducting critical temperature decreases with increasing Co concentration, while the Meissner response varies from a reversible to a strongly hysteretic behaviour depending on the morphology of the samples with different Co content. The persistence of superconductivity at high Co concentrations is attributed to a suppression of the superconducting proximity effect in these nanocomposites, which is ascribed to the low interface transparency between the Sn and Co components that make up these hybrid systems. publisher: Elsevier articletitle: Coexistence of superconductivity and ferromagnetism in cluster-assembled Sn–Co nanocomposites journaltitle: Journal of Alloys and Compounds articlelink: http://dx.doi.org/10.1016/j.jallcom.2015.03.007 content_type: article copyright: Copyright © 2015 Elsevier B.V. All rights reserved. ispartof: Journal of Alloys and Compounds vol:637 pages:509-516 status: published

Lewis acid Snβ-type zeolites with varying amounts of Bronsted acid Al in the framework were synthesized using a simple two-step procedure comprising partial dealumination of β zeolite under action of acid, followed by grafting with SnCl4·5H2O in dry isopropanol. Characterization of the thus-prepared Al-containing Snβ (Sn/pDeAlβ) zeolites with ICP, (pyridine probed) FTIR, and 27Al MAS NMR demonstrates the presence of Bronsted acid framework AlIII. Tetrahedral Lewis acidic SnIV is present, as ascertained by a combination of techniques such as EPMA, 119Sn Moβbauer, XPS, (pyridine probed) FTIR, and UV–vis. A closed SnIV configuration was implied by comparing of 119Sn solid-state MAS NMR and deuterated acetonitrile probed FTIR spectra with literature. The catalytic activity of the Al-containing Snβ was tested for the conversion of 1,3-dihydroxyacetone (DHA) into ethyl lactate (ELA), proceeding via pyruvic aldehyde (PAL). Despite the difference in synthesis between the classic hydrothermal Snβ reference and Sn/...

$\ensuremath{\gamma}\text{\ensuremath{-}}\mathrm{Fe}$ and related alloys are model systems of the coupling between structure and magnetism in solids. Since different electronic states (with different volumes and magnetic ordering states) are closely spaced in energy, small perturbations can alter which one is the actual ground state. Here, we demonstrate that the ferromagnetic state of $\ensuremath{\gamma}\text{\ensuremath{-}}\mathrm{Fe}$ nanoparticles is associated with a tetragonal distortion of the fcc structure. Combining a wide range of complementary experimental techniques, including low-temperature M\"ossbauer spectroscopy, advanced transmission electron microscopy, and synchrotron radiation techniques, we unambiguously identify the tetragonally distorted ferromagnetic ground state, with lattice parameters $a=3.76(2)\phantom{\rule{4pt}{0ex}}\AA{}$ and $c=3.50(2)\phantom{\rule{4pt}{0ex}}\AA{}$, and a magnetic moment of 2.45(5) ${\ensuremath{\mu}}_{B}$ per Fe atom. Our findings indicate that the ferromagnetic order in nanostructured $\ensuremath{\gamma}\text{\ensuremath{-}}\mathrm{Fe}$ is generally associated with a tetragonal distortion. This observation motivates a theoretical reassessment of the electronic structure of $\ensuremath{\gamma}\text{\ensuremath{-}}\mathrm{Fe}$ taking tetragonal distortion into account.

© 2017 American Physical Society. To unravel the effects of phonon confinement, the influence of size and morphology on the atomic vibrations is investigated in Sn nanoislands and cluster-assembled films. Nuclear resonant inelastic x-ray scattering is used to probe the phonon densities of states of the Sn nanostructures which show significant broadening of the features compared to bulk phonon behavior. Supported by ab initio calculations, the broadening is attributed to phonon scattering and can be described within the damped harmonic oscillator model. Contrary to the expectations based on previous research, the appearance of high-energy modes above the cutoff energy is not observed. From the thermodynamic properties extracted from the phonon densities of states, it was found that grain boundary Sn atoms are bound by weaker forces than bulk Sn atoms. ispartof: Physical Review B vol:95 issue:15 status: published

Composite multiferroics are a new class of material where magneto-electric coupling is achieved by creating an interface between a ferromagnetic and a ferroelectric compound. The challenge of understanding the chemical and magnetic properties of such interface is a key to achieve good magneto-electric coupling. The unique possibilities offered by isotope sensitive techniques are used to selectively investigate the interface's chemistry and magnetism in Fe/BaTiO3 and Fe/LiNbO3 systems during the application of an electric field. With a large enough electric field, a strong oxidation of Fe is triggered, which creates a magnetically dead interface. This leads to an irreversible decrease of the magneto-electric coupling properties. Material parameters are identified that determine under which electric field the interface may be modified. The results are confirmed on the two systems and are expected to be widespread in this new class of hybrid material.

We describe an experimental setup for conversion electron Mossbauer spectroscopy (CEMS) at low temperature. The setup is composed of a continuous flow cryostat (temperature range of 4.2-500 K), detector housing, three channel electron multipliers, and corresponding electronics. We demonstrate the capabilities of the setup with CEMS measurements performed on a sample consisting of a thin enriched 57Fe film, with a thickness of 20 nm, deposited on a silicon substrate. We also describe exchangeable adaptations (lid and sample holder) which extend the applicability of the setup to emission Mossbauer spectroscopy as well as measurements under an applied magnetic field.

We investigate the link between superconductivity and atomic vibrations in Nb3Sn films with a thickness ranging from 10 to 50 nm. The challenge of measuring the phonon density of states (PDOS) of these films has been tackled by employing the technique of nuclear inelastic scattering by 119Sn isotopes to reveal the Sn-partial phonon density of states. With the support of ab initio calculations, we evaluate the effect of reduced film thickness on the PDOS. This approach allows us to estimate the changes in superconducting critical temperature Tc induced by phonon confinement, which turned out to be limited to a few tenths of K. The presented method is successful for the Nb3Sn system and paves the way for more systematic studies of the role of phonon confinement in Sn-containing superconductors. ispartof: Physical Review B, Condensed Matter and Materials Physics vol:88 issue:4 status: published

The Pippard coherence length xi(0) (the size of a Cooper pair) in two extreme type-I superconductors (In and Sn) was determined directly through high-resolution measurement of the nonlocal electrodynamic effect combining low-energy muon spin rotation spectroscopy and polarized neutron reflectometry. The renormalization factor Z = m*(cp)/2m (m*(cp) and m are the mass of the Cooper pair and the electron, respectively) resulting from the electron-phonon interaction, and the temperature-dependent London penetration depth lambda(L)(T) were determined as well. An expression linking xi(0), Z, and lambda(L)(0) is introduced and experimentally verified. This expression allows one to determine experimentally the Pippard coherence length in any superconductor, independent of whether the superconductor is local or nonlocal, conventional or unconventional. DOI: 10.1103/PhysRevB.87.104508

We studied the exchange-spring behavior in FePt-Fe hard-soft magnetic heterostructures. We present a study of the spin structure of the soft Fe layer of Fe-FePt bilayers by nuclear forward scattering of synchrotron radiation. The orientation of the Fe moments close to the top of the soft layer was determined quantitatively as a function of the soft-layer thickness. We show that for a few monolayers of Fe, the magnetically hard FePt layer pins the magnetization in the soft Fe layer to the out-of-plane direction. With increasing Fe-layer thickness, the influence of the FePt diminishes and the magnetization cants toward the in-plane Fe[001] direction. The significance of the exchange coupling constant as the relevant parameter for the exchange-spring behavior is demonstrated by one-dimensional micromagnetic simulations.

We present an approach to probe the magnetization inside superconducting films using ultrathin Fe-57 probe layers excited by synchrotron radiation. We investigate the evolution of the Fe-57 hyperfine field orientation as a function of magnetic field above and below the superconducting transition temperature T-c for a Nb(50 nm)/Fe-57(0.6 nm)/Nb(50 nm) trilayer. It is found that significant screening of the external field in the superconductor occurs only at low field, leading to a change in the hyperfine field angle below T-c. The presented approach allows to study the influence of magnetic fields and vortex induced electron correlations in complex layered structures incorporating superconductors. (C) 2011 American Institute of Physics. [doi:10.1063/1.3625941] ispartof: Applied Physics Letters vol:99 issue:9 status: published