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Collection objects in natural science collections span a diverse set of object types of substantially different origin, physical composition, and relevance for different fields and methodologies of research and application. Object provenance is often characterized by elaborate series of interventions from collecting or observing originals in a natural state to generating derived objects that can be physically persistent or are suitable for a given use. This sequence of events gives rise to intermediate objects or object states that can be of a persistent or ephemeral nature in their own right. Detailed metadata on object provenance is vital to enable informed use of collection objects for research and other application areas. Providing the ability to generate, maintain, update and access such accounts is an important requirement for Collection Management Software (CMS). DINA (Digital Information System for Natural History Data, Glöckler et al. 2020)-compliant collection management software meets this challenge by using process- and state-based representation of object histories and modular application architecture as the main conceptual and architectural principles, respectively (Bölling et al. 2021). In applying these principles, we showcase how object provenance can be represented in the DINA system in cases where multiple objects, possibly of varying types, are derived from a single object, objects consist of parts of different biological individuals, object histories involve different types of objects such as living biological individuals, samples, and preserved specimens. multiple objects, possibly of varying types, are derived from a single object, objects consist of parts of different biological individuals, object histories involve different types of objects such as living biological individuals, samples, and preserved specimens. We highlight how the abstractions and categories used in the DINA model can be used to meet a variety of challenging use cases for representing collection object provenance. For instance, while the connections and relationships between living, preserved, and even destructively processed samples can be documented in DINA, these are ordinarily difficult to accommodate in a single information system.

ABCD (Access to Biological Collection Data, Holetschek et al. 2012) 2.06 was ratified by Biodiversity Information Standards (TDWG) in September 2005. In 2017, TDWG ratified the Standards Documentation Standard (SDS, Vocabulary Maintenance Specification Task Group 2017), which is a set of regulations and guidelines on how TDWG standards should be structured and documented. Since then, ABCD has been classified with “2005 standards” on the TDWG standards website. However, with the planned ratifications of the ABCD Extension for Geoscience (ABCD EFG, Petersen et al. 2018) and the more semantic ABCD 3.0 (Fichtmueller et al. 2019), it became necessary to also ratify ABCD 2.06 under the SDS rules. In this talk, we will report on the progress of the ratification processes, both for ABCD 2.06 and ABCD EFG. In particular we want to address the specific challenges that arose from fitting existing XML schemas into the SDS structure and documenting them accordingly.

Biodiversity data is obtained by a variety of methodological approaches—including observation surveys, environmental sampling and biological object collection—employing diverse sample processing protocols and data transformations. While complete and accurate accounts of these data-generating processes are important to enable integration and informed reuse of data, the structure and content of published biodiversity data currently are often shaped by specific application goals. For example, data publishers that export specimen-based data from collection management systems for inclusion in aggregations like those in the Global Biodiversity Information Facility (GBIF) must frequently relax their internal models and produce unnatural joins to fit GBIF’s occurrences-based data structure. Third-party assertions over these aggregated data therefore assume the risk of irreproducibility or concept drift. Here we introduce process- and state-based representation of object histories as the main organizing principle for data about specimens and samples in Digital Information System for Natural History Data (DINA, Glöckler et al. 2020)-compliant collection management software (Fig. 1). Specimens, samples and objects in general are subjected to a variety of processes, including planned actions involving the object, e.g., collecting, preparing, subsampling, loaning. Object states are any particular mode of being of an object at a certain point in time. For example, any one intermediate step in preparing a collected specimen for long-term conservation in a collection would constitute an individual object state. An object’s history is the entire chain of these interrelated processes and states. We argue that using object histories as main conceptual modeling paradigm in DINA offers the generality required to accommodate a diverse, open set of use cases in biodiversity data representation, yet also offers the versatility to serve as basis for use-case specific data aggregation and presentation. Specifically, a representation based on object histories provides a coherent structure for documenting individual processes and states for any given object and for linking this documentation (e.g., textual descriptions or images pertaining to a given process or state), a natural representational structure of the real-world sequence of processes an object participates in and for the data generated in these processes (e.g., a DNA-extraction procedure and sequence information generated on its basis), a straightforward structure to link data about related objects (e.g., tissue samples, the biological specimen a bone is derived from) in a network of connected object histories. a coherent structure for documenting individual processes and states for any given object and for linking this documentation (e.g., textual descriptions or images pertaining to a given process or state), a natural representational structure of the real-world sequence of processes an object participates in and for the data generated in these processes (e.g., a DNA-extraction procedure and sequence information generated on its basis), a straightforward structure to link data about related objects (e.g., tissue samples, the biological specimen a bone is derived from) in a network of connected object histories. The approach is designed to be embedded in DINA’s modular application architecture, so that information on object histories can be accessed via corresponding APIs either through its own interfaces (Fig. 2) or by integration with external web services (Fig. 3). Viewing collection management tasks as part of object histories also informs delineation of modules to support these tasks with specialized functions and interfaces. It also admits the use of persistent, dereferencable identifiers for individual processes and states in object histories and for linking their representations to elements in ontologies and controlled vocabularies. In this contribution to the symposium, DINA's object histories as a main organizing principle for collection object data will be discussed and the utility of using it in the context of modular application architecture, data federation, and data integration in projects like BiCIKL will be illustrated.

In the last two decades, various projects and initiatives have conducted research on how to share, exchange, and link information from natural science collection objects. This profound (technical) knowledge, standards, tools, and best practices are essential to the development of any new research infrastructure facilitating research on bio- and geodiversity. However, the knowledge and research results are usually not easily accessible at a single point and particularly not in a well-curated form. Here, the Knowledgebase developed for the Distributed System of Scientific Collections (DiSSCo) comes into play. This information hub will act as trusted source for project outcomes and other relevant resources (e.g., web services, Persistent Identifier Systems, controlled vocabularies, domain-specific ontologies and standards) for users and developers of DiSSCo and other research infrastructures worldwide. In this talk, we will present the current version of the DiSSCo Knowledgebase, its developmental approach, and the opportunity for this source to act as an e-service for various stakeholder groups interested in and working with natural science collections worldwide.

To support future research based on natural sciences collection data, DiSSCo (Distributed System of Scientific Collections) – the European Research Infrastructure for Natural Science Collections – adopts Digital Object Architecture as the basis for its planned data infrastructure. Using the outputs of one Research Data Alliance (RDA) interest group (IG) and five working groups (WGs) we show how RDA recommendations and supporting documents have been applied to the various stages of the DiSSCo data lifecycle.

The DINA Consortium (DINA = “DIgital information system for NAtural history data”, https://dina-project.net) is a framework for like-minded practitioners of natural history collections to collaborate on the development of distributed, open source software that empowers and sustains collections management. Target collections include zoology, botany, mycology, geology, paleontology, and living collections. The DINA software will also permit the compilation of biodiversity inventories and will robustly support both observation and molecular data. The DINA Consortium focuses on an open source software philosophy and on community-driven open development. Contributors share their development resources and expertise for the benefit of all participants. The DINA System is explicitly designed as a loosely coupled set of web-enabled modules. At its core, this modular ecosystem includes strict guidelines for the structure of Web application programming interfaces (APIs), which guarantees the interoperability of all components (https://github.com/DINA-Web). Important to the DINA philosophy is that users (e.g., collection managers, curators) be actively engaged in an agile development process. This ensures that the product is pleasing for everyday use, includes efficient yet flexible workflows, and implements best practices in specimen data capture and management. There are three options for developing a DINA module: create a new module compliant with the specifications (Fig. 1), modify an existing code-base to attain compliance (Fig. 2), or wrap a compliant API around existing code that cannot be or may not be modified (e.g., infeasible, dependencies on other systems, closed code) (Fig. 3). create a new module compliant with the specifications (Fig. 1), modify an existing code-base to attain compliance (Fig. 2), or wrap a compliant API around existing code that cannot be or may not be modified (e.g., infeasible, dependencies on other systems, closed code) (Fig. 3). All three of these scenarios have been applied in the modules recently developed: a module for molecular data (SeqDB), modules for multimedia, documents and agents data and a service module for printing labels and reports: The SeqDB collection management and molecular tracking system (Bilkhu et al. 2017) has evolved through two of these scenarios. Originally, the required architectural changes were going to be added into the codebase, but after some time, the development team recognised that the technical debt inherent in the project wasn’t worth the effort of modification and refactoring. Instead a new codebase was created bringing forward the best parts of the system oriented around the molecular data model for Sanger Sequencing and Next Generation Sequencing (NGS) workflows. In the case of the Multimedia and Document Store module and the Agents module, a brand new codebase was established whose technology choices were aligned with the DINA vision. These two modules have been created from fundamental use cases for collection management and digitization workflows and will continue to evolve as more modules come online and broaden their scope. The DINA Labels & Reporting module is a generic service for transforming data in arbitrary printable layouts based on customizable templates. In order to use the module in combination with data managed in collection management software Specify (http://specifysoftware.org) for printing labels of collection objects, we wrapped the Specify 7 API with a DINA-compliant API layer called the “DINA Specify Broker”. This allows for using the easy-to-use web-based template engine within the DINA Labels & Reports module without changing Specify’s codebase. In our presentation we will explain the DINA development philosophy and will outline benefits for different stakeholders who directly or indirectly use collections data and related research data in their daily workflows. We will also highlight opportunities for joining the DINA Consortium and how to best engage with members of DINA who share their expertise in natural science, biodiversity informatics and geoinformatics.

Digital specimens (Hardisty 2018, Hardisty 2020) are the cyberspace equivalent to objects in a physical, often museum-based collection. They consist of references to data and metadata related to the collection object. Through the ongoing process of digitizing legacy data, gaining knowledge from new field collections or research, and annotating and linking to related resources, a digital specimen can evolve independently from the original physical object. Especially the provenance records cannot always be assigned to the physical object when the knowledge was gained solely from the digital representation. A physical specimen can also be understood as a physical preparation (or a set of multiple preparations, e.g. DNA samples taken from a preserved organism) accompanied by related digital and non-digital data sources (e.g. images, descriptions in fieldbooks, research data) rather than just a single object. This concept of an extended specimen has been described by Webster (2017) and is used in the initiative The Extended Specimen Network (Lendemer et al. 2019) to enhance the access and research potential of specimens. Digital specimens need to reflect both, eventual complexity of the physical object (extended specimen) and the knowledge gained from and linked to the digital object itself. In order to provide, track and make use of the digital specimens, the community of collection-holding institutions might need to think of digital specimens as standalone virtual collections that emanate from physical collections. Additionally, new versions of a digital specimen continuously derive from changes of the physical specimen as the (meta)data are being updated in collection management systems to document the state and treatment of the physical objects. Consequently, there is a challenge to enable the management of both: linked digital specimens in the World Wide Web and the local data of physical specimens in databases of collection-holding institutions and other tools and services. In this panel discussion, central questions about the requirements, obstacles and opportunities of implementing the concepts of digital specimens and extended specimens in software tools like collection management systems are discussed. The aim is to identify the major tasks and priorities regarding the transformation of tools and services from multiple perspectives: local collection data management, international data infrastructures like the Distributed System of Scientific Collections (DiSSCo) and the Global Biodiversity Information Facility (GBIF), and data usage outside of domain-specific subject areas.

Museums and their collections have specially customized databases in order to optimally gather and record their contents and associated metadata associated with their specimens. To share, exchange, and publish data, an appropriate data standard is essential. ABCD (Access to Biological Collection Data) is a standard for biological collection units, including living and preserved specimen, together with field observation data. Its extension, EFG (Extension for Geoscience), enables sharing and publishing data related to paleontological, mineralogical, and petrological objects. The standard is very granular and allows detailed descriptions, including information about the collection event itself, the holding institution, stratigraphy, chemical analysis, and host rock. The standard extension was developed in 2006 and has been used since then by different initiatives and applied for the publication of collection-related data in domain-specific and interdisciplinary portals.

The DINA Consortium (“DIgital information system for NAtural history data”, https://dina-project.net ) was formed in order to provide a framework for like-minded large natural history collection-holding institutions to collaborate through a distributed Open Source development model to produce a flexible and sustainable collection management system. Target collections include zoological, botanical, mycological, geological and paleontological collections, living collections, biodiversity inventories, observation records, and molecular data. DINA is funded by the participating member institutions. DINA Core Members are organizations or individuals who commit at least one half-time equivalent of resources to the development of the consortium goals, at least half of which should be available for code development. The DINA system is architected as a loosely-coupled set of several web-based modules. The conceptual basis for this modular ecosystem is a compilation of comprehensive guidelines for Web application programming interfaces (APIs) to guarantee the interoperability of its components. Thus, all DINA components can be modified or even replaced by other components without crashing the rest of the system as long as they are DINA compliant. Furthermore, the modularity enables the institutions to host only the components they need. DINA focuses on an Open Source software philosophy and on community-driven open development, so the contributors share their development resources and expertise outside of their own institutions. One of the overarching reasons to develop a new collection management system is the need to better model complex relationships between collection objects (typically specimens), research data and associated workflows. We will present the enhancements provided by the approach of the DINA system focussing on the flexibility to plug in compliant components and accommodate additional (meta-)data and specimen related research data with the help of a generic data module. Furthermore, we will discuss challenges in the governance of the development activities such as organizing the distributed code development of the core modules, the code review process and the choice of the software stack. These organizational challenges will be overcome with the help of a revised Memorandum of Understanding.

For the last 15 years, Biodiversity Information Standards (TDWG) has recognized two competing standards for organism occurrence data, ABCD (Access to Biological Collections Data; Holetschek et al. 2012) and DarwinCore (Wieczorek et al. 2012). These two representations emerged from contrasting strategies for mobilizing information about organism occurrences (also commonly called species occurrence data). ABCD was capable of representing details of more kinds of information, but was necessarily more complicated. DarwinCore, on the other hand, was simpler but more limited in its ability to represent data of different kinds and formats. TDWG endorsed both standards because the different projects and communities that generated them remained dedicated to their different strategies and tool sets, and the Global Biodiversity Information Facility (GBIF) developed the ability to integrate data published in either standard. Since their inceptions, DarwinCore and ABCD have become more similar. DarwinCore has gotten more complicated through the addition of terms and has begun to assign terms to classes. ABCD is now expressed in RDF (Resource Description Framework), potentially enabling re-use of terms with alternative structures among classes. At the same time, methodologies for conceptual modeling and representing complex scientific data have continued to evolve. In particular, a suite of modeling and data representation methods related to linked data and the semantic web, i.e., RDF, SKOS (Simple Knowledge Organization System), and OWL (web Ontology Language), promise to make it easier for us to reconcile shared concepts among different representations or schemas. A mapping between ABCD 2.1 and DarwinCore has existed since before 2005.*1 ABCD 3.0 and DarwinCore are both now represented in RDF. In addition, the BioCollections Ontology (BCO) covers many of the shared concepts and is derived from the Basic Formal Ontology (BFO), an upper level ontology that has oriented many other biomedical ontologies. Reconciling ABCD and DarwinCore through alignment with BCO (in the OBO Foundry; Smith et al. 2007) would better connect TDWG standards to other domains in biology. We appreciate that many working scientists and data managers perceive ontologies as overly complicated. To mitigate the steep learning curve associated with ontologies, we expect to create simpler application profiles or schemas to guide and serve narrower communities of practice within the wider biodiversity domain. We also plan to integrate the current work of the Taxonomic Names and Concepts Interest Group and thereby eliminate the redundancy between DarwinCore and Taxonomic Concepts Transfer Schema (TCS; Kennedy et al. 2006). At the time of this writing, we have only agreements from the authors (i.e., conveners of relevant TDWG Interest Groups and other key stakeholders) to collaborate in pursuit of these common goals. In this presentation we will give a more detailed description of our objectives and products, the methods we are using to achieve them, and our progress to date.

The TDWG standard ABCD (Access to Biological Collections Data task group 2007) was aimed at harmonizing terminologies used for modelling biological collection information and is used as a comprehensive data format for transferring collection and observation data between software components. The project ABCD 3.0 (A community platform for the development and documentation of the ABCD standard for natural history collections) was financed by the German Research Council (DFG). It addressed the transformation of ABCD into a semantic web-compliant ontology by deconstructing the XML-schema into individually addressable RDF (Resource Description Framework) resources published via the TDWG Terms Wiki (https://terms.tdwg.org/wiki/ABCD_2). In a second step, informal properties and concept-relations described by the original ABCD-schema were transformed into a machine-readable ontology and revised (Güntsch et al. 2016). The project was successfully finished in January 2019. The ABCD 3 setup allows for the creation of standard-conforming application schemas. The XML variant of ABCD 3.0 was restructured, simplified and made more consistent in terms of element names and types as compared to version 2.x. The XML elements are connected to their semantic concepts using the W3C SAWSDL (Semantic Annotation for Web Services Description Language and XML Schema) standard. The creation of specialized applications schemas is encouraged, the first use case was the application schema for zoology. It will also be possible to generate application schemas that break the traditional unit-centric structure of ABCD. Further achievements of the project include creating a Wikibase instance as the editing platform, with related tools for maintenance queries, such as checking for inconsistencies in the ontology and automated export into RDF. This allows for fast iterations of new or updated versions, e.g. when additional mappings to other standards are done. The setup is agnostic to the data standard created, it can therefore also be used to create or model other standards. Mappings to other standards like Darwin Core (https://dwc.tdwg.org/) and Audubon Core (https://tdwg.github.io/ac/) are now machine readable as well. All XPaths (XML Paths) of ABCD 3.0 XML have been mapped to all variants of ABCD 2.06 and 2.1, which will ease transition to the new standard. The ABCD 3 Ontology will also be uploaded to the GFBio Terminology Server (Karam et al. 2016), where individual concepts can be easily searched or queried, allowing for better interactive modelling of ABCD concepts. ABCD documentation now adheres to TDWG’s Standards Documentation Standard (SDS, https://www.tdwg.org/standards/sds/) and is located at https://abcd.tdwg.org/. The new site is hosted on Github: https://github.com/tdwg/abcd/tree/gh-pages.

The DINA Symposium (“DIgital information system for NAtural history data”, https://dina-project.net) ends with a plenary session involving the audience to discuss the interplay of collection management and software tools. The discussion will touch different areas and issues such as: (1) Collection management using modern technology: How should and could collections be managed using current technology – What is the ultimate objective of using a new collection management system? How should traditional management processes be changed? (2) Development and community Why are there so many collection management systems? Why is it so difficult to create one system that fits everyone’s requirements? How could the community of developers and collection staff be built around DINA project in the future? (3) Features and tools How to identify needs that are common to all collections? What are the new tools and technologies that could facilitate collection management? How could those tools be implemented as DINA compliant services? (4) Data What data must be captured about collections and specimens? What criteria need to be applied in order to distinguish essential and “nice-to-have” information? How should established data standards (e.g. Darwin Core & ABCD (Access to Biological Collection Data)) be used to share data from rich and diverse data models? In addition to the plenary discussion around these questions, we will agree on a streamlined format for continuing the discussion in order to write a white paper on these questions. The results and outcome of the session will constitute the basis of the paper and will be subsequently refined.

The DINA Consortium (“DIgital information system for NAtural history data”, https://dina-project.net, Fig. 1) was formed in order to provide a framework for like-minded large natural history collection-holding institutions to collaborate through a distributed Open Source development model to produce a flexible and sustainable collection management system. Target collections include zoological, botanical, mycological, geological and paleontological collections, living collections, biodiversity inventories, observation records, and molecular data. The DINA system is architected as a loosely-coupled set of several web-based modules. The conceptual basis for this modular ecosystem is a compilation of comprehensive guidelines for Web application programming interfaces (APIs) to guarantee the interoperability of its components. Thus, all DINA components can be modified or even replaced by other components without crashing the rest of the system as long as they are DINA compliant. Furthermore, the modularity enables the institutions to host only the components they need. DINA focuses on an Open Source software philosophy and on community-driven open development, so the contributors share their development resources and expertise outside of their own institutions. One of the overarching reasons to develop a new collection management system is the need to better model complex relationships between collection objects (typically specimens) involving their derivatives, preparations and storage. We will discuss enhancements made in the DINA data model to better represent these relationships and the influence it has on the management of these objects, and on the sharing of information. Technical detail of various components of the DINA system will be shown in other talks in this symposium followed by a discussion session.

With biodiversity research activities being increasingly shifted to the web, the need for a system of persistent and stable identifiers for physical collection objects becomes increasingly pressing. The Consortium of European Taxonomic Facilities agreed on a common system of HTTP-URI-based stable identifiers which is now rolled out to its member organizations. The system follows Linked Open Data principles and implements redirection mechanisms to human-readable and machine-readable representations of specimens facilitating seamless integration into the growing semantic web. The implementation of stable identifiers across collection organizations is supported with open source provider software scripts, best practices documentations and recommendations for RDF metadata elements facilitating harmonized access to collection information in web portals. Database URL : http://cetaf.org/cetaf-stable-identifiers.

In the natural history community a high diversity of collection management systems exist. This enables institutions to choose from a large variety of systems, but this choice requires extensive effort to evaluate and commit to an appropriate system to cover all long-term requirements. As the different kinds of natural history data generated by a given domain and associated research-related data can typically not be handled within a single system, most institutions have several specialized software components and consequently have to cope with serious limitations in interacting and querying across the systems. This reality is costly and not sustainable. Further, even if a monolithic system would cover all needs, being dependent on only one software and vendor holds a relatively high risk in assuring long-term maintenance. The DINA consortium ("DIgital Information system for NAtural history data", https://dina-project.net) is attempting to address these challenges by using a distributed open-source development model across multiple institutions. The goal is to produce an open-source web-based information management system for natural history data developed and maintained in a community-driven approach by several large institutions with dedicated resources. DINA was founded in 2014 by six natural history collection institutions in Europe and North America and is open to new members. The DINA system is designed as a mesh of several web-based modules. The conceptual basis for this ecosystem is a compilation of comprehensive guidelines for application programming interfaces (APIs) to guarantee the interoperability of its components. Thus, all DINA components can be modified or even replaced by other components without crashing the rest of system as long as they are DINA compliant. Furthermore, the modularity enables the institutions to host only the components they need. DINA focuses on an open-source software philosophy and on community-driven open development, so the contributors share their development resources and expertise outside of their own institutions. Consequently, this approach reduces both, individual costs and risks, and increases the sustainability of the system. We will present an overview of DINA focusing on the open-source software philosophy, our current achievements, challenges and future developments.

The data schema ABCD (Access to Biological Collection Data version 2.06) is a standard for biological collection units, including living and preserved specimen, together with field observation data. Its extension EFG (Extension for Geosciences) is suitable for sharing and publishing data related to paleontological, mineralogical, and petrological objects. In addition to detailed object descriptions and collection events, ABCD EFG provides fine-grained data structures for information on stratigraphy, chemical analyses and host rock composition. The comprehensive EFG was developed in 2006. Since then it has been used by different initiatives, including the publication of collection-related data in domain-specific and interdisciplinary portals such as GBIF, GeoCASe, GFBio and Europeana. The TDWG Paleo Interest Group meeting 2017 will include a focus on the relationship between Darwin Core and ABCD EFG, and following that theme this presentation will give an introduction to the current state of ABCD EFG, its common use cases and an outlook towards the next version ABCD 3.0. We expect that the ABCD EFG terms are suitable for embedding elements into the Darwin Core Paleo Context. Thus, this talk will also initiate the discussion about the most important elements for further use cases from the paleobiological community.

The German Federation for Biological Data (GFBio; Diepenbroek et al. 2014) is implementing a national infrastructure for the preservation, integration, and publication of biological data collected in German research projects. GFBio is built upon an archive infrastructure comprised of nine data centers including PANGAEA and the major German Natural Science Collections (German Federation for Biological Data (GFBio) 2017a). Creating and running GFBio requires close collaborations within a highly interdisciplinary consortium. Bringing together expertise from collections, scientists in the relevant fields, biodiversity informaticians and computer scientists proved to be essential for designing and building this system. GFBio is currently in its second funding phase. Essential services, required for the operation of the future infrastructure, have been successfully implemented. The realized technologies and tools use globally accepted standards as well as innovative concepts e.g., for data visualisation or semantic integration. A portal (https://www.gfbio.org) provides a common point of access to all GFBio services: data submission, data discovery, data visualisation and analysis, a terminology service, and a help desk. In addition, archived research data is shared with international information infrastructures such as the Global Biodiversity Information Facility (GBIF) and the Biological Collection Access Service (BioCASE). As the data centers use different systems and thus internally build upon different data structures (German Federation for Biological Data (GFBio) 2017b), the search functionality integrated in the portal is an good example of the collaboration between teams of different expertise. Since the aim was to provide an integrated, faceted search, it was necessary to agree on common fields that can be used to feed the facets. Therefore, the GFBio data centers agreed on using ABCD 2.06 (Access to Biological Collection Data) as a common standard and specified thirty elements for data exchange. Here, it was essential to bring together (1) domain experts for defining which facets they consider useful for an effective search, (2) computer scientists for providing the implementation based on Elasticsearch (Elasticsearch 2017), (3) biodiversity informaticians for defining mappings between different standards and (4) data curators from the GFBio data centers and long-term repositories for negotiating the set of mandatory fields. The starting point for broader research data management workflows was derived from high-quality data provided via publishing pipelines established at each data center. With that, primary collection and research data are available with metadata and data units according to the ABCD community standard and are ready to be reused following the FAIR data principles (Wilkinson et al. 2016): Findable, Accessible, Interoperable, Re-usable. Consequently, interdisciplinary cooperation is the GFBio data portal's measure of success.

In the project "Stadtnatur entdecken" (discovering nature in the city) a multidisciplinary team of specialists in biology, informatics, urban ecology and social sciences is looking into how to effectively communicate educational content on environmental topics to young adults and to allow them to contribute as citizen scientists. The mobile app "Naturblick" presents on experience of nature in an urban setting. Several tools are combined in the app that allows users to identify species. The team developed auditory and visual pattern recognition tools that will automatically identify sound recordings and photographs and multi-access identification keys for flora and fauna. There is a map function that will help explore nature in the users' immediate vicinity in Berlin, Germany, highlighting the diversity of species to be found. Users are able to share their observations and records. The project is designed to involve user participation and continuous improvement based on user feedback of both the content and technology.

Fauna Europaea is Europe's main zoological taxonomic index, making the scientific names and distributions of all living, currently known, multicellular, European land and freshwater animals species integrally available in one authoritative database. Fauna Europaea covers about 260,000 taxon names, including 145,000 accepted (sub)species, assembled by a large network of (>400) leading specialists, using advanced electronic tools for data collations with data quality assured through sophisticated validation routines. Fauna Europaea started in 2000 as an EC funded FP5 project and provides a unique taxonomic reference for many user-groups such as scientists, governments, industries, nature conservation communities and educational programs. Fauna Europaea was formally accepted as an INSPIRE standard for Europe, as part of the European Taxonomic Backbone established in PESI. Fauna Europaea provides a public web portal at faunaeur.org with links to other key biodiversity services, is installed as a taxonomic backbone in wide range of biodiversity services and actively contributes to biodiversity informatics innovations in various initiatives and EC programs.

In 2010, we launched the Global Index of Vegetation-Plot Databases (GIVD; http://www.givd.info), an internet-based resource offering metadata of existing electronic vegetation databases. On 11 May 2012, 182 databases containing more than 2.8 million non-overlapping vegetation plots had been registered in GIVD. The majority of these plots were from European databases (123 databases, 1.87 million plots). The oldest plot record dated from 1864, but the vast majority of the plots had been collected since 1970. Most of the plots had areas between 1 and 1,000 m2. A total of 68 databases also stored time series and/or nested-plot data. The vegetation-plot data registered in GIVD constitute a major resource for biodiversity research, not only through the large number of species occurrence records, but especially due to the storage of species co-occurrence information, complemented with site-specific structural data and plot-based environmental data. The increased ease of discovering and accessing such datasets, owing to their registration in GIVD, offers significant opportunities for large-scale studies in areas such as community ecology, macroecology, and global-change research. The results from such studies could be very important for nature conservation practice and policy.

Question: How many vegetation plot observations (releves) are available in electronic databases, how are they geographically distributed, what are their properties and how might they be discovered and located for research and application? Location: Global. Methods: We compiled the Global Index of Vegetation-Plot Databases (GIVD; http://www.givd.info), an Internet resource aimed at registering metadata on existing vegetation databases. For inclusion, databases need to (i) contain temporally and spatially explicit species co-occurrence data and (ii) be accessible to the scientific public. This paper summarizes structure and data quality of databases registered in GIVD as of 30 December 2010. Results: On the given date, 132 databases containing more than 2.4 million non-overlapping plots had been registered in GIVD. The majority of these data were in European databases (83 databases, 1.6 million plots), whereas other continents were represented by substantially less (North America 15, Asia 13, Africa nine, South America seven, Australasia two, multi-continental three). The oldest plot observation was 1864, but most plots were recorded after 1970. Most plots reported vegetation on areas of 1 to 1000 m2; some also stored time-series and nested-plot data. Apart from geographic reference (required for inclusion), most frequent information was on altitude (71%), slope aspect and inclination (58%) and land use (38%), but rarely soil properties (

The DINA system (“DIgital information system for NAtural history data”, https://dina-project.net) consists of several web-based services that fulfill specific tasks. Most of the existing services are covering single core features in the collection management system and can be used either as integrated components in the DINA environment, or as stand-alone services. In this presentation single services will be highlighted as they represent technically interesting approaches and practical solutions for daily challenges in collection management, data curation and migration workflows. The focus will be on the following topics: (1) a generic reporting and label printing service, (2) practical decisions on taxonomic references in collection data and (3) the generic management and referencing of related research data and metadata: Reporting as presented in this context is defined as an extraction and subsequent compilation of information from the collection management system rather than just summarizing statistics. With this quite broad understanding of the term the DINA Reports & Labels Service (Museum für Naturkunde Berlin 2018) can assist in several different collection workflows such as generating labels, barcodes, specimen lists, vouchers, paper loan forms etc. As it is based on customizable HTML templates, it can be even used for creating customized web forms for any kind of interaction (e.g. annotations). Many collection management systems try to cope with taxonomic issues, because in practice taxonomy is used not only for determinations, but also for organizing the collections and categorizing storage units (e.g. “Coleoptera hall”). Addressing taxonomic challenges in a collection management system can slow down development and add complexity for the users. The DINA system uncouples these issues in a simple taxonomic service for the sole assignment of names to specimens, for example determinations. This draws a clear line between collection management and taxonomic research, of which the latter can be supported in a separate service. While the digitization of collection data and workflows proceeds, linking related data is essential for data management and enrichment. In many institutions research data is disconnected from the collection specimen data because the type and structure cannot be easily included in the collection management databases. With the DINA Generic Data Module (Museum für Naturkunde Berlin 2017) a service exists that allows for attaching any relational data structures to the DINA system. It can also be used as a standalone service that accommodates structured data within a DINA compliant interface for data management.

The BioCASe Monitor Service (BMS) is a web-based tool for coordinators of distributed data networks that provide information to web-portals and data aggregators via the BioCASe Provider Software. Building on common standards and protocols, it has three main purposes: (1) monitoring provider's progress in data provision, (2) facilitating checks of data mappings with a focus on the structure, plausibility and completeness, and (3) verifying compliance of provided data for transformation into other target schemas. Herein two use cases, GBIF-D and OpenUp!, are presented in which the BMS is being applied for monitoring the progress in data provision and performing quality checks on the ABCD (Access to Biological Collection Data) schema mapping. However, the BMS can potentially be used with any conceptual data schema and protocols for querying web services. Through flexible configuration options it is highly adaptable to specific requirements and needs. Thus, the BMS can be easily implemented into coordination workflows and reporting duties within other distributed data network projects.