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  • 1
    In: Biodiversity Information Science and Standards, Pensoft Publishers, Vol. 5 ( 2021-09-14)
    Abstract: 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 Na tural 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.
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2021
    detail.hit.zdb_id: 3028709-1
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  • 2
    In: Biodiversity Information Science and Standards, Pensoft Publishers, Vol. 6 ( 2022-09-07)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2022
    detail.hit.zdb_id: 3028709-1
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  • 3
    Online Resource
    Online Resource
    Pensoft Publishers ; 2020
    In:  Biodiversity Information Science and Standards Vol. 4 ( 2020-10-06)
    In: Biodiversity Information Science and Standards, Pensoft Publishers, Vol. 4 ( 2020-10-06)
    Abstract: The DINA Consortium (DINA = “ DI gital information system for NA tural 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 & amp; 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 & amp; 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.
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2020
    detail.hit.zdb_id: 3028709-1
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  • 4
    Online Resource
    Online Resource
    Pensoft Publishers ; 2022
    In:  Biodiversity Information Science and Standards Vol. 6 ( 2022-08-23)
    In: Biodiversity Information Science and Standards, Pensoft Publishers, Vol. 6 ( 2022-08-23)
    Abstract: The Biodiversity Information Standards (TDWG) Material Sample Task Group*1 kicked off in the third quarter of 2021. The group’s initial focus was to 1) achieve a clear conceptual delineation between the terms MaterialSample , PreservedSpecimen , LivingSpecimen , and FossilSpecimen (the terms used in basisOfRecord in the current DwC-A provided to the Integrated Publishing Toolkit (IPT) for describing physical material) 2) define the conceptual relationship between these terms and the term Organism 3) consider the possible implications of the activities towards the diversification of the Global Biodiversity Information Facility (GBIF) data model*2 and what standards already exist that should inform our work. Based on this conceptual work, the group is now developing a concrete proposal for a clarification of a MaterialSample class with its own properties. Our presentation will provide a brief review of the task group's progress and our thoughts about what comes next.
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2022
    detail.hit.zdb_id: 3028709-1
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  • 5
    Online Resource
    Online Resource
    Trans Tech Publications, Ltd. ; 2018
    In:  Applied Mechanics and Materials Vol. 885 ( 2018-11), p. 156-169
    In: Applied Mechanics and Materials, Trans Tech Publications, Ltd., Vol. 885 ( 2018-11), p. 156-169
    Abstract: Narrow tolerances are commonly used to control uncertainty in the production of technicalcomponents. However, narrow tolerances lead to financial expense and limit flexibility. In this paperthe concept of a resilient process chain is presented. This concept covers the product life cycle phases ofproduction and usage. It is enabled by the digitalization in mechanical engineering and offers access tovariable process windows instead of rigid tolerances. First steps of this concept are then applied to the TU Darmstadt active air spring. The active air spring can be used to increase the driving comfort in avehicle or, for instance, to minimize kinetosis during autonomous driving. The focus hereby is toidentify possible production influences on the behaviour of the components usage. For this purpose, theactuator of the active air spring is specifically manufactured with typical uncertainty of high precisionmachining of the bore and characterized experimentally in a test rig. The results show an influenceof the production on the efficiency of the actuator. The measurements are fundamental to establish aresilient process chain on the active air spring.
    Type of Medium: Online Resource
    ISSN: 1662-7482
    URL: Issue
    Language: Unknown
    Publisher: Trans Tech Publications, Ltd.
    Publication Date: 2018
    detail.hit.zdb_id: 2251882-4
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  • 6
    Online Resource
    Online Resource
    Trans Tech Publications, Ltd. ; 2018
    In:  Applied Mechanics and Materials Vol. 885 ( 2018-11), p. 255-266
    In: Applied Mechanics and Materials, Trans Tech Publications, Ltd., Vol. 885 ( 2018-11), p. 255-266
    Abstract: Fine machining processes are of great importance in automotive series production, e.g. the machining of valve guide and seat in the cylinder head of a combustion engine. In industrial manufacturing processes, disturbances are inevitable and provide a measure of uncertainty in each production step. Increasingly, the influence of such uncertainties is being evaluated using simulation models. In this paper, a modeling approach for simulation of multi-stage fine machining processes with step tools is presented and investigations regarding influence of uncertainty caused by disturbances are performed.
    Type of Medium: Online Resource
    ISSN: 1662-7482
    URL: Issue
    Language: Unknown
    Publisher: Trans Tech Publications, Ltd.
    Publication Date: 2018
    detail.hit.zdb_id: 2251882-4
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  • 7
    In: PLOS ONE, Public Library of Science (PLoS), Vol. 15, No. 2 ( 2020-2-21), p. e0229271-
    Type of Medium: Online Resource
    ISSN: 1932-6203
    Language: English
    Publisher: Public Library of Science (PLoS)
    Publication Date: 2020
    detail.hit.zdb_id: 2267670-3
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  • 8
    In: Strahlentherapie und Onkologie, Springer Science and Business Media LLC, Vol. 185, No. S2 ( 2009-8), p. 3-4
    Type of Medium: Online Resource
    ISSN: 0179-7158 , 1439-099X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2009
    detail.hit.zdb_id: 2003907-4
    detail.hit.zdb_id: 84983-2
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  • 9
    Online Resource
    Online Resource
    Acoustical Society of America (ASA) ; 2020
    In:  The Journal of the Acoustical Society of America Vol. 148, No. 4_Supplement ( 2020-10-01), p. 2481-2481
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 148, No. 4_Supplement ( 2020-10-01), p. 2481-2481
    Abstract: Knowledge of hearing abilities, as represented in audiograms, is vital for understanding animal acoustic physiology, behaviour, and ecology. Additionally, such knowledge plays an important role for measuring, predicting, or counteracting effects of anthropogenic noise on the environment. Currently, audiogram data is usually only available embedded in individual scientific publications and in various unstandardized formats, which makes access to and analysis of audiograms across sources cumbersome. We established a newly database that presents audiograms along with data on the audio-physiological experiments and original publications in a structured and easily accessible way. The interface enables combination of audiogram data for comparative analysis of different species, experimental conditions or publications. Focusing currently on marine vertebrates its content is the result of an extensive survey of the scientific literature and manual curation of the contained audio-physiological data. The database is designed to accommodate audiogram data on any biological group and purposed to be extended and serve as a reference source for audiogram data. It is publicly accessible at https://animalaudiograms.museumfuernaturkunde.berlin. [The database was developed as part of the project “Hearing in Penguins” funded by the German Environment Agency (UBA) with means from the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU, FKZ3717182440).]
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    RVK:
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2020
    detail.hit.zdb_id: 1461063-2
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  • 10
    In: Biodiversity Information Science and Standards, Pensoft Publishers, Vol. 7 ( 2023-09-11)
    Abstract: Insects account for half of the total described living organisms on Earth, with a vast number of species awaiting description. Insects play a major role in ecosystems but are yet threatened by habitat destruction, intensive farming, and climate change. Museum collections around the world house millions of insect specimens and large-scale digitization initiatives, such as the digitization street digitize! at the Museum für Naturkunde, have been undertaken recently to unlock this data. Accurate and efficient extraction of insect specimen label information is vital for building comprehensive databases and facilitating scientific investigations, sustainability of the collected data, and efficient knowledge transfer. Despite the advancements in high-throughput imaging techniques for specimens and their labels, the process of transcribing label information remains mostly manual and lags behind the pace of digitization efforts. In order to address this issue, we propose a three step semi-automated pipeline that focuses on extracting and processing information from individual insect labels. Our solution is primarily designed for printed insect labels, as the OCR (optical character recognition) technology performs well for printed text while handwritten texts still yield mixed results. The pipeline incorporates computer vision (CV) techniques, OCR, and a clustering algorithm. The initial stage of our pipeline involves image analysis using a convolutional neural network (CNN) model. The model was trained using 2100 images from three distinct insect label datasets, namely AntWeb (ant specimen labels from various collections), Bees & Bytes (bee specimen labels from the Museum für Naturkunde), and LEP_PHIL (Lepidoptera specimen labels from the Museum für Naturkunde). The first model enables the identification and isolation of single labels within an image, effectively segmenting the label region from the rest of the image, and crops them into multiple new, single-label image files. It also assigns the labels to different classes, i.e., printed text or handwritten, with handwritten labels sorted out from the printed ones. In the second step, labels classified as “printed” are then parsed by an OCR engine to extract the text information from the labels. Tesseract and Google Vision OCRs were both tested to assess their performance. While Google Vision OCR is a cloud-based service with limited configurability, Tesseract provides the flexibility to fine-tune settings and enhance its performance for our specific use cases. In the third step, the OCR outputs are aggregated by similarity using a clustering algorithm. This step allows for the identification and formation of clusters that consist of labels sharing identical or highly similar content. Ultimately, these clusters are compared against a curated database of labels and are assigned to a known label or highlighted as new and manually added to the database. In order to assess the efficiency of our pipeline, we performed benchmarking experiments using a set of images similar to those the models were trained on, as well as additional image sets obtained from various museum collections. Our pipeline offers several advantages, streamlining the data entry process, and reducing manual extraction time and effort, while also minimizing potential human errors and inconsistencies in label transcription. The pipeline holds the promise of accelerating metadata extraction from insect specimens, promoting scientific research and enabling large-scale analyses to achieve a more profound understanding of the collections.
    Type of Medium: Online Resource
    ISSN: 2535-0897
    Language: Unknown
    Publisher: Pensoft Publishers
    Publication Date: 2023
    detail.hit.zdb_id: 3028709-1
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