Descriptive Data in the EDIT Platform for Cybertaxonomy

This paper describes the integration of structured descriptive data in the EDIT platform for Cybertaxonomy. The platform is composed of several software modules supporting the taxonomic workflow from data capture and storage to publication. Descriptive data play an important role within the taxonomic work process. The integration of these data via import/export modules to and from the platform and the publication as natural language output or as keys are explained

Cactaceae at Caryophyllales.org- A dynamic online species-level taxonomic backbone for the family

This data paper presents a largely phylogeny-based online taxonomic backbone for the Cactaceae compiled from literature and online sources using the tools of the EDIT Platform for Cybertaxonomy. The data will form a contribution of the Caryophyllales Network for the World Flora Online and serve as the base for further integration of research results from the systematic research community. The final aim is to treat all effectively published scientific names in the family. The checklist includes 150 accepted genera, 1851 accepted species, 91 hybrids, 746 infraspecific taxa (458 heterotypic, 288 with autonyms), 17,932 synonyms of accepted taxa, 16 definitely excluded names, 389 names of uncertain application, 672 unresolved names and 454 names belonging to (probably artificial) named hybrids, totalling 22,275 names. The process of compiling this database is described and further editorial rules for the compilation of the taxonomic backbone for the Caryophyllales Network are proposed. A checklist depicting the current state of the taxonomic backbone is provided as supplemental material. All results are also available online on the website of the Caryophyllales Network and will be constantly updated and expanded in the future. Citation: Korotkova N., Aquino D., Arias S., Eggli U., Franck A., Gómez-Hinostrosa C., Guerrero P. C., Hernández H. M., Kohlbecker A., Köhler M., Luther K., Majure L. C., Müller A., Metzing D., Nyffeler R., Sánchez D., Schlumpberger B. & Berendsohn W. G. 2021: Cactaceae at Caryophyllales.org- A dynamic online species-level taxonomic backbone for the family.-Willdenowia 51: 251-270. Version of record first published online on 31 August 2021 ahead of inclusion in August 2021 issue. Data published through: Http://caryophyllales.org/cactaceae/Checklis

Grundlagen des Autonomen Rechnens

Das vegetative Nervensystem (engl. autonomous nervous system) des Menschen kann das, wovon in der IT-Industrie noch geträumt wird. Abhängig von der aktuellen Umgebung und Tätigkeit reguliert das vegetative Nervensystem mandatorische Körperfunktionen wie Herzfrequenz und Atmung. Reflexe, die dem Selbstschutz dienen, werden automatisch ausgelöst. Verletzungen heilen von selbst, ohne dass man seine normalen Tätigkeiten dafür unterbrechen müsste. Im Rahmen des Seminars „Autonomic Computing“ im Sommersemester 2003 am Institut für Programmstrukturen und Datenorganisation der Universität Karlsruhe wurden Grundlagen dieses Autonomen Rechnens besprochen. Als Basis für Selbstkonfiguration und Selbstoptimierung werden in „Kontextbewusstsein: Ein Überblick“ Techniken zur Erfassung des physischen und sozialen Kontexts einer Anwendung erläutert. Die dienstorientierte Architektur und konkrete Implementierungen wie z.B. UPnP, Jini oder Bluetooth werden in „Aktuelle Technologien zur Realisierung dienstorientierter Architekturen“ behandelt. Die Arbeit „Service- Orientierung und das Semantic Web“ beschreibt, wie Semantic Web Technologien zur Beschreibung von Web Services verwendet werden können mit dem Ziel der automatischen Dienstfindung. Danach wird der Begriff „Selbstbewusstsein“ in bezug auf Software anhand zweier komplementärer Forschungsprojekte definiert. Technologien zur Überwachung des Laufzeitverhaltens von Rechnersystemen mit dem Ziel der selbstständigen Optimierung sind Gegenstand der Arbeit „Selbst-Überwachung und Selbst-Optimierung“. Der Artikel „Selbst-Schutz“ fasst die Sicherheitsanforderungen zusammen, die an ein autonomes Computersystem gestellt werden müssen und die Techniken, um solche Anforderungen zu erfüllen. Ansätze aus dem Bereich wiederherstellungsorientiertes- und fehlertolerantes Rechnen werden in „Selbst-Heilung“, „ROC – Recovery Oriented Computing“ und „Recovery Oriented Computing: Modularisierung und Redundanz“ vorgestellt. Alle Ausarbeitungen und Präsentationen sind auch elektronisch auf der diesem Band beiliegenden CD oder unter www.autonomic-computing.org verfügbar

Edit Platform for Cybertaxonomy, TaxEditor, User manual, appendix

The Common Data Model (CDM) is the underlying data structure of the EDIT Platform for Cybertaxonomy, representing a complete model of data used in biological taxonomy and systematics. CDM-light is a set of relational tables produced by one of the export functions of the EDIT Platform. As compared to the CDM itself, the relational model is simplified and data are partially aggregated. CDM-light may be used as a transfer format, to generate statistics about the data in a CDM database, to control data quality, or to produce document-type output from CDM databases

EDIT Platform Projects: What’s Next

The EDIT Platform for Cybertaxonomy has come a long way towards providing a complete, standards-based and reliable set of tools and services supporting the taxonomic workflow (Ciardelli et al. 2009). The Platform is firmly grounded in the organisational structure of the BGBM, with several positions directly dedicated to maintenance and further development of the Platform, complemented by numerous projects that are carried out in international and national cooperation. Furthermore, we continue to count on the collaboration of the teams in Paris and Tervuren, for descriptive data and geographic mapping functionalities, respectively. However, there are a number of areas where further research and development is needed, and of course the speed of development is often limited by the available resources. Among the topics under discussion are, inter alia: The integration of regional treatments (e.g. floras or faunas) with global monographic ones Efficient ways towards an integrated management of literature references Alternative approaches towards generating morphological descriptions and identification tools The integration of data quality indicators The handling of taxon concepts in a (present or absent) phylogenetic context How concept relations (Berendsohn & al., this session) can be handled efficiently in user interfaces Assignment of stable identifiers to core objects such as scientific names and taxa (needs community agreement both as to the technical implementation and as to rules applicable to identifiers when changes of objects occur). Synchronisation of taxonomic datasets in multiple instances of the EDIT Platform with overlapping information areas

EDIT Platform Web Services in the Biodiversity Infrastructure Landscape

The EDIT Platform for Cybertaxonomy is a standards based suite of software components supporting the taxonomic research workflow from field work to publication in journals and dynamic web portals (FUB, BGBM 2011). The underlying Common Data Model (CDM) covers the main biodiversity informatics foci such as names, classifications, descriptions, literature, multimedia, literature as well as specimens and observations and their derived objects. Today, more than 30 instances of the platform are serving data to the international biodiversity research communities. An often overlooked feature of the platform is its well defined web service layer which provides capable functions for machine access and integration into the growing service-based biodiversity informatics landscape (FUB, BGBM 2010). All platform instances have a pre-installed and open service layer serving three different use cases: The CDM REST API provides a platform independent RESTful (read-only) interface to all resources represented in the CDM. In addition, a set of portal services have been designed to meet the special functional requirements of CDM data portals and their advanced navigation capabilities. While the "raw" REST API has already all functions for searching and browsing the entire information space spanned by the CDM, the integration of CDM services into external infrastructures and workflows requires an additional set of streamlined service endpoints with a special focus on documentation and version stability. To this end, the platform provides a set of "catalogue services" with optimized functions for (fuzzy) name, taxon, and occurrence data searches (FUB, BGBM 2013, FUB, BGBM 2014). A good example for the integration of EDIT platform catalogue services into broader workflows is the "Taxonomic Data Refinement Workflow" implemented in the context of the EU 7th Framework Program Project BioVeL (Hardisty et al. 2016). The workflow uses the service layer of an EDIT Platform based instance of the Catalogue of Life (CoL) for resolving taxonomic discrepancies between specimen datasets (Mathew et al. 2014). The same service is also part of the Unified Taxonomic Information Service (UTIS) providing an easy-to-use interface for running simultaneous searches across multiple taxonomic checklists (FUB, BGBM 2016)

A Comprehensive and Standards-Aware Common Data Model (CDM) for Taxonomic Research

The EDIT Common Data Model (CDM) (FUB, BGBM 2008) is the centrepiece of the EDIT Platform for Cybertaxonomy (FUB, BGBM 2011, Ciardelli et al. 2009). Building on modelling efforts reaching back to the 1990ies, it aims to combine existing standards relevant to the taxonomic domain (but often designed for data exchange) with requirements of modern taxonomic tools. Modelled in the Unified Modelling Language (UML) (Booch et al. 2005), it offers an object oriented view on the information domain managed by expert taxonomists that is implemented independent of the used operating system and database management system (DBMS). Being used in various national and international research projects with diverse foci over the past decade, the model evolved and became the common base of a variety of taxonomic projects, such as floras, faunas and checklists (see FUB, BGBM 2016 for a number of data portals created and made publicly available by different projects). The CDM is strictly oriented towards the needs of the taxonomic experts community. Where requirements are complex it tries to reflect them reasonably rather than introducing ambiguity or reduced functionality via (over-)simplification. Where simplification is possible it tries to stay or become simple. Simplification on the model level is achieved by implementing business rules via constraints rather than via typification and subclassing. Simplification on the user interface level is achieved by numerous options for customisation. Being used as a generic model for a variety of application types and use cases, it is adaptable and extendable by users and developers. It uses a combination of static and dynamic typification to allow both efficient handling of complex but well-defined data domains such as taxonomic classifications and nomenclature as well as less well-defined flexible domains like factual and descriptive data. Additionally it allows the creation of more than 30 types of user defined vocabularies such as those for taxonomic rank, nomenclatural status, name-to-name relationships, geographic area, presence status, etc. A strong focus is set on good scientific praxis by making the source of almost all data citable in detail and offering data lineage to trace data back to its roots. It is also easy to reflect multiple opinions in parallel, e.g. differing taxonomic concepts (Berendsohn 1995, Berendsohn & al., this session) or several descriptive treatments obtained from different regional floras or faunas. The CDM attempts to comprehensively cover the data used in the taxonomic domain - nomenclature, taxonomy (including concepts), taxon distribution data, descriptive data of all kinds, including morphological data referring to taxa and/or specimens, images and multimedia data of various kinds, and a complex system covering specimens and specimen derivatives down to DNA samples and sequences (Kilian et al. 2015, Stöver and Müller 2015) that mirrors the complexity of knowledge accumulation in the taxonomic research process. In the context of the EDIT Platform, several applications have been developed based on the CDM and the library that provides the API and web Service interfaces based on the CDM (see Kohlbecker & al. and Güntsch & al., this session). In some areas the CDM is still evolving - although the basic structures are present, questions of application development feed back into modelling decisions. However, a "no-shortcuts" approach to modelling has variously delayed application development in the past, but it now pays off: the Platform can rapidly adapt to changing requirements from different projects and taxonomic specialists

PhycoBank: Repository for algal novelties

The International Code of Nomenclature (ICN) for algae, fungi, and plants calls for indexing of names in nomenclatural repositories (Turland 2018, Art. 42). Scientific names, new combinations, validations, and typifications of algae are novelties tracked by PhycoBank, the registration system for algae.PhycoBank was established and institutionalized at the Botanic Garden Berlin as the repository for nomenclatural acts concerning algae. Since June 2018, PhycoBank staff have been operating the registration system permanently. All data entered into the system undergo a curatorial process to assure a high level of data quality.PhycoBank’s three main components comprise a user-friendly data entry web application available for all registered submitters (self-registration allowed) and curators, a public data access portal, and a search engine that integrates most of the larger online repositories for algae names. The latter is not only a prerequisite for reliable data curation during the registration process but also a valuable, publicly available online tool for algae names. A fourth component still under development is handling the tight integration of the registration system with the workflow of digital publishers.The resulting data are expected to be of high quality and to have been intensively checked against existing nomenclatural acts worldwide. A crucial requirement for the data entry application is thus an intensive support for data validation and curation. Besides the search index giving access to a huge number of existing external names, the data entry application offers a set of tools for quality assurance. It supports and requires the creation of mostly fully atomized data that strictly follow the rules of the ICN. Additionally, completeness for core data is mandatory. Both, atomization and completeness are a precondition to achieve the required uniqueness in the dataset. Completeness also implies that new combinations can only be registered after or together with their original name. The same applies to bi- or trinomials and the respective uni- and binomials they are built on. The publicly available data portal allows accessing published registrations by searching for scientific names, nomenclatural authors, higher ranks and for each part of a bibliographic reference (such as bibliographic author, journal, title, year) stored in PhycoBank.Being a name centric application PhycoBank is neutral with respect to taxonomic opinions. Therefore, only nomenclatural synonymies (basionym or replaced synonym relationships) are stored in the system and names are not attached to a unique classification. Instead, to facilitate search via higher ranks as required by users, classification information is stored as a directed graph of higher taxa with registered names linking to this graph. By this, searches can be performed on multiple classifications simultaneously and can return all possible matches.PhycoBank uses http-based persistent identifiers (e.g. http://phycobank.org/102170), which makes them resolvable and actionable. These identifiers link to nomenclatural acts only and not to the information in the act. That is, a PhycoBank identifier should not be used to refer to a scientific name even if this name was established in the nomenclatural act.PhycoBank makes use of the application stack offered by the EDIT Platform for Cybertaxonomy (Kohlbecker 2017). However, as registration workflows essentially differ from other taxonomic workflows, a completely new user interface for editing has been developed, which provides the users with an intuitive and fluent user experience despite the high complexity of the data.The Common Data Model (Müller 2017) is the core data model for the Platform and already covered the vast majority of data types and fields required by the registration in terms of completeness and degree of atomization. For PhycoBank, it only needed to be extended by a single data type representing the registration/nomenclatural act itself.As of July 2022, PhycoBank includes 4,332 registrations, of which 4,202 are name novelties (1,523 in preparation or ready, 239 under curation, 2,407 published, and 33 rejected); 130 registrations refer to lectotypes or epitypes of existing names.PhycoBank will apply for recognition as a repository in 2022. This is a prerequisite for a proposal to make registration of nomenclatural acts for algae mandatory. This is possible before, at or after the 20th International Botanical Congress 2024

EDIT Platform Web Services in the Biodiversity Infrastructure Landscape

The EDIT Platform for Cybertaxonomy is a standards based suite of software components supporting the taxonomic research workflow from field work to publication in journals and dynamic web portals (FUB, BGBM 2011). The underlying Common Data Model (CDM) covers the main biodiversity informatics foci such as names, classifications, descriptions, literature, multimedia, literature as well as specimens and observations and their derived objects. Today, more than 30 instances of the platform are serving data to the international biodiversity research communities. An often overlooked feature of the platform is its well defined web service layer which provides capable functions for machine access and integration into the growing service-based biodiversity informatics landscape (FUB, BGBM 2010). All platform instances have a pre-installed and open service layer serving three different use cases: The CDM REST API provides a platform independent RESTful (read-only) interface to all resources represented in the CDM. In addition, a set of portal services have been designed to meet the special functional requirements of CDM data portals and their advanced navigation capabilities. While the "raw" REST API has already all functions for searching and browsing the entire information space spanned by the CDM, the integration of CDM services into external infrastructures and workflows requires an additional set of streamlined service endpoints with a special focus on documentation and version stability. To this end, the platform provides a set of "catalogue services" with optimized functions for (fuzzy) name, taxon, and occurrence data searches (FUB, BGBM 2013, FUB, BGBM 2014). A good example for the integration of EDIT platform catalogue services into broader workflows is the "Taxonomic Data Refinement Workflow" implemented in the context of the EU 7th Framework Program Project BioVeL (Hardisty et al. 2016). The workflow uses the service layer of an EDIT Platform based instance of the Catalogue of Life (CoL) for resolving taxonomic discrepancies between specimen datasets (Mathew et al. 2014). The same service is also part of the Unified Taxonomic Information Service (UTIS) providing an easy-to-use interface for running simultaneous searches across multiple taxonomic checklists (FUB, BGBM 2016)

Biodiversity information platforms: From standards to interoperability

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