EFFECTIVELY SEARCHING SPECIMEN AND OBSERVATION DATA WITH TOQE, THE THESAURUS OPTIMIZED QUERY EXPANDER

Today’s specimen and observation data portals lack a flexible mechanism, able to link up thesaurus-enabled data sources such as taxonomic checklist databases and expand user queries to related terms, significantly enhancing result sets. The TOQE system (Thesaurus Optimized Query Expander) is a REST-like XML web-service implemented in Python and designed for this purpose. Acting as an interface between portals and thesauri, TOQE allows the implementation of specialized portal systems with a set of thesauri supporting its specific focus. It is both easy to use for portal programmers and easy to configure for thesaurus database holders who want to expose their system as a service for query expansions. Currently, TOQE is used in four specimen and observation data portals. The documentation is available from http://search.biocase.org/toqe/

Sample data processing in an additive and reproducible taxonomic workflow by using character data persistently linked to preserved individual specimens

We present the model and implementation of a workflow that blazes a trail in systematic biology for the re-usability of character data (data on any kind of characters of pheno- and genotypes of organisms) and their additivity from specimen to taxon level. We take into account that any taxon characterization is based on a limited set of sampled individuals and characters, and that consequently any new individual and any new character may affect the recognition of biological entities and/or the subsequent delimitation and characterization of a taxon. Taxon concepts thus frequently change during the knowledge generation process in systematic biology. Structured character data are therefore not only needed for the knowledge generation process but also for easily adapting characterizations of taxa. We aim to facilitate the construction and reproducibility of taxon characterizations from structured character data of changing sample sets by establishing a stable and unambiguous association between each sampled individual and the data processed from it. Our workflow implementation uses the European Distributed Institute of Taxonomy Platform, a comprehensive taxonomic data management and publication environment to: (i) establish a reproducible connection between sampled individuals and all samples derived from them; (ii) stably link sample-based character data with the metadata of the respective samples; (iii) record and store structured specimen-based character data in formats allowing data exchange; (iv) reversibly assign sample metadata and character datasets to taxa in an editable classification and display them and (v) organize data exchange via standard exchange formats and enable the link between the character datasets and samples in research collections, ensuring high visibility and instant re-usability of the data. The workflow implemented will contribute to organizing the interface between phylogenetic analysis and revisionary taxonomic or monographic work

Toward a service-based workflow for automated information extraction from herbarium specimens

Over the past years, herbarium collections worldwide have started to digitize millions of specimens on an industrial scale. Although the imaging costs are steadily falling, capturing the accompanying label information is still predominantly done manually and develops into the principal cost factor. In order to streamline the process of capturing herbarium specimen metadata, we specified a formal extensible workflow integrating a wide range of automated specimen image analysis services. We implemented the workflow on the basis of OpenRefine together with a plugin for handling service calls and responses. The evolving system presently covers the generation of optical character recognition (OCR) from specimen images, the identification of regions of interest in images and the extraction of meaningful information items from OCR. These implementations were developed as part of the Deutsche Forschungsgemeinschaft-funded a standardised and optimised process for data acquisition from digital images of herbarium specimens (StanDAP-Herb) Project

Adding content to content -a generic annotation system for biodiversity data

suMMArY -Adding content to content -a generic annotation system for biodiversity data -Biodiversity information networks such as GBiF and BiocAse provide access to a rapidly growing number of collection records, ranging from simple occurrence information to high resolution images. today, about 150 million observation and collection records are available at a global level. Although the technology for providing and retrieving primary biodiversity data is reasonably mature, the development of advanced techniques for feedback using annotations has been neglected. We have developed and implemented a web-based annotation system which fills this gap. rather than sending the annotation as a message to the collection holder, the system allows for adding, changing and removing information in a copy of the collection record. the modified record is then stored on a public annotation server together with all previous versions. this allows collection holders to compare the different versions and decide whether a given annotation will be fed back into the collection database. the system works with any GBiF-compliant information network. riAssunto -Aggiungere contenuti ai contenuti -un sistema per la gestione delle annotazioni per dati relativi alla biodiversità -le reti informatiche per i dati sulla biodiversità, come GBiF e BiocAse, consentono l'accesso a un numero, in rapido incremento, di schede sugli esemplari catalogati appartenenti a varie collezioni: le informazioni in esse contenute spaziano da semplici occorrenze in un'area geografica fino a immagini ad alta risoluzione. oggigiorno, a livello globale, sono disponibili circa 150 milioni di osservazioni e schede riferite a esemplari collezionati. sebbene la tecnologia in grado di fornire e recuperare dati primari relativi alla biodiversità si sia evoluta raggiungendo livelli di funzionalità ragionevoli, è stato tuttavia trascurato lo sviluppo di tecniche avanzate di feedback che fanno uso di annotazioni. Abbiamo allora elaborato e implementato un sistema di annotazioni basato sul web che colma questa lacuna. invece di inviare l'annotazione al curatore della collezione sotto forma di messaggio, tale sistema consente di aggiungere, cambiare e rimuovere informazioni in una copia della scheda catalogata della collezione. la scheda modificata viene quindi salvata su un server pubblico per le annotazioni insieme a tutte le versioni precedenti. Questo consente ai curatori delle collezioni di paragonare le differenti versioni e di decidere se accettare una certa annotazione nel database della collezione. il sistema può operare con qualsiasi rete informatica compatibile con GBiF

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

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

A botanical demonstration of the potential of linking data using unique identifiers for people

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

The EDIT Platform for Cybertaxonomy - an integrated software environment for biodiversity research data management

The Platform for Cybertaxonomy [1], developed as part of the EU Network of Excellence EDIT (European Distributed Institute of Taxonomy), is an open-source software framework covering the full breadth of the taxonomic workflow, from fieldwork to publication [2]. It provides a number of tools for full, customized access to taxonomic data, editing and management, and collaborative team work. At the core of the platform is the Common Data Model [3], offering a comprehensive information model covering all relevant data domains: names and classifications, descriptive data (morphological and molecular), media, geographic information, literature, specimens, persons, and external resources [4]. The model adheres to community standards developed by the Biodiversity Information Standards organization TDWG [5]. Apart from its role as a software suite supporting the taxonomic workflow, the platform is a powerful information broker for a broad range of taxonomic data providing solid and open interfaces including a Java programmer’s library and a CDM Rest Service Layer. In the context of the DFG-funded "Additivity" project ("Achieving additivity of structured taxonomic character data by persistently linking them to preserved individual specimens", DFG project number 310530378), we are developing components for capturing and processing formal descriptions of specimens as well as algorithms for aggregating data from individual specimens in order to compute species-level descriptions [6]. Well-defined and agreed descriptive vocabularies referring to structures, characters and character states are instrumental in ensuring the consistency and comparability of measurements. This will be addressed with a new EDIT Platform module for specifying vocabularies based on existing ontologies for descriptive data. To ensure that these vocabularies can be re-used in different contexts, we are planning an interface to the Terminology Service developed by the German Federation for Biological Data (GFBio) [7]. The Terminology Service provides a semantic standards aware and harmonised access point for distributed or locally stored ontologies required for biodiversity research data management, archiving and publication processes [8]. The interface will work with a new OWL export function of the CDM library, which provides EDIT Platform vocabularies in a format that can be read by the import module of the Terminology Service. In addition, the EDIT Platform will be equipped with the ability to import semantic concepts from the Terminology Service using its API and keeping a persistent link to the original concept. With an active pipeline between the EDIT Platform and the GFBio Terminology Service, terminologies originating from the taxonomic research process can be re-used in different research contexts as well as for the semantic annotation and integration of existing research data processed by the GFBio archiving and data publication infrastructure. KEYWORDS: taxonomic computing, descriptive data, terminology, inference REFERENCES: 1. EDIT Platform for Cybertaxonomy. http://www.cybertaxonomy.org (accessed 17 May 2018). 2. Ciardelli, P., Kelbert, P., Kohlbecker, A., Hoffmann, N., Güntsch, A. & Berendsohn, W. G., 2009. The EDIT Platform for Cybertaxonomy and the Taxonomic Workflow: Selected Components, in: Fischer, S., Maehle, E., Reischuk, R. (Eds.): INFORMATIK 2009 – Im Focus das Leben. GI-Edition: Lecture Notes in Informatics (LNI) – Proceedings 154. Köllen Verlag, Bonn, pp. 28;625-638. 3. Müller, A., Berendsohn, W. G., Kohlbecker, A., Güntsch, A., Plitzner, P. & Luther, K., 2017. A Comprehensive and Standards-Aware Common Data Model (CDM) for Taxonomic Research. Proceedings of TDWG 1: e20367. https://doi.org/10.3897/tdwgproceedings.1.20367. 4. EDIT Common Data Model. https://dev.e-taxonomy.eu/redmine/projects/edit/wiki/CommonDataModel (accessed 17 May 2018). 5. Biodiversity Information Standards TDWG. http://www.tdwg.org/ (accessed 17 May 2018). 6. Henning T., Plitzner P., Güntsch A., Berendsohn W. G., Müller A. & Kilian N., 2018. Building compatible and dynamic character matrices – Current and future use of specimen-based character data. Bot. Lett. https://doi.org/10.1080/23818107.2018.1452791. 7. Diepenbroek, M., Glöckner, F., Grobe, P., Güntsch, A., Huber, R., König-Ries, B., Kostadinov, I., Nieschulze, J., Seeger, B.; Tolksdorf, R. & Triebel, D., 2014. Towards an Integrated Biodiversity and Ecological Research Data Management and Archiving Platform: The German Federation for the Curation of Biological Data (GFBio), in: Plödereder, E., Grunske, L., Schneider, E., Ull, D. (Eds.): Informatik 2014 – Big Data Komplexität meistern. GI-Edition: Lecture Notes in Informatics (LNI) – Proceedings 232. Köllen Verlag, Bonn, pp. 1711-1724. 8. Karam, N., Müller-Birn, C., Gleisberg, M., Fichtmüller, D., Tolksdorf, R., & Güntsch, A., 2016. A Terminology Service Supporting Semantic Annotation, Integration, Discovery and Analysis of Interdisciplinary Research Data. Datenbank-Spektrum, 16(3), 195–205. https://doi.org/10.1007/s13222-016-0231-8

People are essential to linking biodiversity data

People are one of the best known and most stable entities in the biodiversity knowledge graph. The wealth of public information associated with people and the ability to identify them uniquely open up the possibility to make more use of these data in biodiversity science. Person data are almost always associated with entities such as specimens, molecular sequences, taxonomic names, observations, images, traits and publications. For example, the digitization and the aggregation of specimen data from museums and herbaria allow us to view a scientist’s specimen collecting in conjunction with the whole corpus of their works. However, the metadata of these entities are also useful in validating data, integrating data across collections and institutional databases and can be the basis of future research into biodiversity and science. In addition, the ability to reliably credit collectors for their work has the potential to change the incentive structure to promote improved curation and maintenance of natural history collections

A benchmark dataset of herbarium specimen images with label data

More and more herbaria are digitising their collections. Images of specimens are made available online to facilitate access to them and allow extraction of information from them. Transcription of the data written on specimens is critical for general discoverability and enables incorporation into large aggregated research datasets. Different methods, such as crowdsourcing and artificial intelligence, are being developed to optimise transcription, but herbarium specimens pose difficulties in data extraction for many reasons. To provide developers of transcription methods with a means of optimisation, we have compiled a benchmark dataset of 1,800 herbarium specimen images with corresponding transcribed data. These images originate from nine different collections and include specimens that reflect the multiple potential obstacles that transcription methods may encounter, such as differences in language, text format (printed or handwritten), specimen age and nomenclatural type status. We are making these specimens available with a Creative Commons Zero licence waiver and with permanent online storage of the data. By doing this, we are minimising the obstacles to the use of these images for transcription training. This benchmark dataset of images may also be used where a defined and documented set of herbarium specimens is needed, such as for the extraction of morphological traits, handwriting recognition and colour analysis of specimens

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

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