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- ItemWorkshop on PIDs within NFDI: Report of the Working Group “Persistent Identifiers (PID)” of the Section Common Infrastructures of the NFDI(Zenodo, 2023) Arend, Daniel; Bach, Janete; Elger, Kirsten; Göller, Sandra; Hagemann-Wilholt, Stephanie; Krahl, Rolf; Lange, Matthias; Linke, David; Mayer, Desiree; Mutschke, Peter; Reimer, Lorenz; Scheidgen, Markus; Schrader, Antonia C.; Selzer, Michael; Wieder, PhilippIn order to gain an overview of the current state of the discussion on PIDs and for the identification of use cases for the initiation phase of a PID service within the NFDI basic services, the working group Persistent Identifier of the Section Common Infrastructures of the NFDI hosted an online workshop in January 2023. In the course of the workshop, members of nine different NFDI consortia presented the current application of PIDs in their consortia.
- ItemBridging the Gap Between (AI-) Services and Their Application in Research and Clinical Settings Through Interoperability: the OMI-Protocol(Hannover : Technische Informationsbibliothek, 2024-02) Sigle, Stefan; Werner, Patrick; Schweizer, Simon; Caldeira, Liliana; Hosch, René; Dyrba, Martin; Fegeler, Christian; Sigle, Stefan; Werner, Patrick; Schweizer, Simon; Caldeira, Liliana; Hosch, René; Dyrba, Martin; Fegeler, Christian; Grönke, Ana; Seletkov, Dmitrii; Kotter, Elmar; Nensa, Felix; Wehrle, Julius; Kaufmes, Kevin; Scherer, Lucas; Nolden, Marco; Boeker, Martin; Schmidt, Marvin; Pelka, Obioma; Braren, Rickmer; Stump, Shura-Roman; Graetz, Teresa; Pogarell, Tobias; Susetzky, Tobias; Wieland, Tobias; Parmar, Vicky; Wang, YuanbinArtificial Intelligence (AI) in research and clinical contexts is transforming the areas of medical and life sciences permanently. Aspects like findability, accessibility, interoperability, and reusability are often neglected for AI-based inference services. The Open Medical Inference (OMI) protocol aims to support remote inference by addressing the aforementioned aspects. Key component of the proposed protocol is an interoperable registry for remote inference services, which addresses the issue of findability for algorithms. It is complemented by information on how to invoke services remotely. Together, these components lay the basis for the implementation of distributed inference services beyond organizational borders. The OMI protocol considers prior work for aspects like data representation and transmission standards wherever possible. Based on Business Process Modeling of prototypical use cases for the service registry and common inference processes, a generic information model for remote services was inferred. Based on this model, FHIR resources were identified to represent AI-based services. The OMI protocol is first introduced using AI-services in radiology but is designed to be generalizable to other application domains as well. It provides an accessible, open specification as blueprint for the introduction and implementation of remote inference services.
- ItemConcept for Setting up the Persistent Identifier Services Working Group in the NFDI Section "Common Infrastructures"(Zenodo, 2022) Bingert, Sven; Brase, Jan; Burger, Felix; Dreyer, Britta; Hagemann-Wilholt, Stephanie; Vierkant, Paul; Wieder, PhilippThe aim of this NFDI working group is to develop a common strategy for the implementation and extension of PID services that is closely aligned with the needs of NFDI consortia. Resulting solutions should enable FAIR research workflows balancing out generic metadata requirements for PIDs that maximise resource discoverability on the one hand and subject-specific needs on the other. At the technical level, the partners want to realise interoperability between PID types and established systems and build on a high level of maturity here; jointly developed services should be able to be rolled out for the entire NFDI.
- ItemDiscussion on Existing Standards and Quality Criteria in Nanosafety Research : Summary of the NanoS-QM Expert Workshop(Zenodo, 2021) Binder, Kunigunde; Bonatto Minella, Christian; Elberskirchen, Linda; Kraegeloh, Annette; Liebing, Julia; Petzold, Christiane; Razum, Matthias; Riefler, Norbert; Schins, Roel; Sofranko, Adriana; van Thriel, Christoph; Unfried, KlausThe partners of the research project NanoS-QM (Quality- and Description Standards for Nanosafety Research Data) identified and invited relevant experts from research institutions, federal agencies, and industry to evaluate the traceability of the results generated with the existing standards and quality criteria. During the discussion it emerged that numerous studies seem to be of insufficient quality for regulatory purposes or exhibit weaknesses with regard to data completeness. Deficiencies in study design could be avoided by more comprehensive use of appropriate standards, many of which already exist. The use of Electronic Laboratory Notebooks (ELNs) that allow for early collection of metadata and enrichment of datasets could be one solution to enable data re-use and simplify quality control. Generally, earlier provision and curation of data and metadata indicating their quality and completeness (e.g. guidelines, standards, standard operating procedures (SOPs) that were used) would improve their findability, accessibility, interoperability, and reusability (FAIR) in the nanosafety research field.
- ItemPID Network Deutschland: Netzwerk für die Förderung von persistenten Identifikatoren in Wissenschaft und Kultur(Potsdam : Helmholtz Open Science Office, 2023) Bertelmann, Roland; Buys, Matthew; Kett, Jürgen; Pampel, Heinz; Pieper, Dirk; Scholze, Frank; Sens, Irina; Burger, Felix; Dreyer, Britta; Glagla-Dietz, Stephanie; Hagemann- Wilholt, Stephanie; Hartmann, Sarah; Schrader, Antonia C.; Schirrwagen, Jochen; Summann, Friedrich; Vierkant, Paul[No abstract available]
- ItemKnowledge Graphs - Working Group Charter (NFDI section-metadata) (1.2)(Genève : CERN, 2023) Stocker, Markus; Rossenova, Lozana; Shigapov, Renat; Betancort, Noemi; Dietze, Stefan; Murphy, Bridget; Bölling, Christian; Schubotz, Moritz; Koepler, OliverKnowledge Graphs are a key technology for implementing the FAIR principles in data infrastructures by ensuring interoperability for both humans and machines. The Working Group "Knowledge Graphs" in Section "(Meta)data, Terminologies, Provenance" of the German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur (NFDI) e.V.) aims to promote the use of knowledge graphs in all NFDI consortia, to facilitate cross-domain data interlinking and federation following the FAIR principles, and to contribute to the joint development of tools and technologies that enable transformation of structured and unstructured data into semantically reusable knowledge across different domains.
- ItemRegulating bacterial behavior within hydrogels of tunable viscoelasticity(New York : Cold Spring Harbor Laboratory, 2022) Bhusari, Shardul; Sankaran, Shrikrishnan; del Campo, AránzazuEngineered living materials (ELMs) are a new class of materials in which living organism incorporated into diffusive matrices uptake a fundamental role in material’s composition and function. Understanding how the spatial confinement in 3D affects the behavior of the embedded cells is crucial to design and predict ELM’s function, regulate and minimize their environmental impact and facilitate their translation into applied materials. This study investigates the growth and metabolic activity of bacteria within an associative hydrogel network (Pluronic-based) with mechanical properties that can be tuned by introducing a variable degree of acrylate crosslinks. Individual bacteria distributed in the hydrogel matrix at low density form functional colonies whose size is controlled by the extent of permanent crosslinks. With increasing stiffness and decreasing plasticity of the matrix, a decrease in colony volumes and an increase in their sphericity is observed. Protein production surprisingly follows a different pattern with higher production yields occurring in networks with intermediate permanent crosslinking degrees. These results demonstrate that, bacterial mechanosensitivity can be used to control and regulate the composition and function of ELMs by thoughtful design of the encapsulating matrix, and by following design criteria with interesting similarities to those developed for 3D culture of mammalian cells.
- ItemAmoeboid Cell Migration through Regular Arrays of Micropillars under Confinement(New York : Cold Spring Harbor Laboratory, 2022) Sadjadi, Zeinab; Vesperini, Doriane; Laurent, Annalena M.; Barnefske, Lena; Terriac, Emmanuel; Lautenschläger, Franziska; Rieger, HeikoMigrating cells often encounter a wide variety of topographic features—including the presence of obstacles—when navigating through crowded biological environments. Unravelling the impact of topography and crowding on the dynamics of cells is key to better understand many essential physiological processes such as the immune response. We study how migration and search efficiency of HL-60 cells differentiated into neutrophils in quasi two-dimensional environments are influenced by the lateral and vertical confinement and spatial arrangement of obstacles. A microfluidic device is designed to track the cells in confining geometries between two parallel plates with distance h, in which identical micropillars are arranged in regular pillar forests. We find that at each cell-pillar contact event, the cell spends a finite time near the pillar surface, which is independent of the height h and the interpillar spacing e. At low pillar density regime, the directional persistence of cells reduces with decreasing h or e, influencing their diffusivity and first-passage properties. The dynamics is strikingly different at high pillar density regime, where the cells are in simultaneous contact with more than one pillar; the cell velocity and persistence are distinctly higher compared to dilute pillar configurations with the same h. Our simulations reveal that the interplay between cell persistence and cell-pillar interactions can dramatically affect cell diffusivity and, thus, its first-passage properties.
- ItemAnalysis of Knowledge Tracing performance on synthesised student data(Hannover : Technische Informationsbibliothek, 2024) Pagonis, Panagiotis; Hartung, Kai; Wu, Di; Georges, Munir; Gröttrup, SörenKnowledge Tracing (KT) aims to predict the future performance of students by tracking the development of their knowledge states. Despite all the recent progress made in this field, the application of KT models in education systems is still restricted from the data perspectives: 1) limited access to real life data due to data protection concerns, 2) lack of diversity in public datasets, 3) noises in benchmark datasets such as duplicate records. To resolve these problems, we simulated student data with three statistical strategies based on public datasets and tested their performance on two KT baselines. While we observe only minor performance improvement with additional synthetic data, our work shows that using only synthetic data for training can lead to similar performance as real data.