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Start date: 2022 × WGL Institute: TIB ×

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Now showing 1 - 10 of 101
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    Handreichung Technik und Infastrukturen
    (Genève : CERN, 2023) Eichler, Frederik; Eppelin, Anita; Kampkaspar, Dario; Schrader, Antonia C.; Söllner, Konstanze; Vierkant, Paul; Withanage, Dulip; Wrzesinski, Marcel
    In der vorliegenden Handreichung stellen wir unterschiedliche technische Ressourcen vor, die redaktionelle Arbeiten unterstützen können. Dabei empfiehlt es sich, Software und Systeme zu nutzen, die den Wandel hin zu einer offenen, niederschwelligen und nachhaltigen Wissenschaftskultur fördern. Hierzu zählt in erster Linie die Verwendung von Open-Source-Software. Unsere Empfehlungen haben dabei eine begrenzte Reichweite: Serviceanbieter, Software und Projekte sind zu einem späteren Zeitpunkt ggf. nicht mehr verfügbar. Auch sind gerade die Infrastruktureinrichtungen in das föderale Wissenschaftssystem integriert, was sie bestimmten Unwägbarkeiten aussetzt.
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    Collaborative annotation and semantic enrichment of 3D media
    (New York,NY,United States : Association for Computing Machinery, 2022) Rossenova, Lozana; Schubert, Zoe; Vock, Richard; Sohmen, Lucia; Günther, Lukas; Duchesne, Paul; Blümel, Ina; Aizawa, Akiko
    A new FOSS (free and open source software) toolchain and associated workflow is being developed in the context of NFDI4Culture, a German consortium of research- and cultural heritage institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users across the broad spectrum of the digital libraries and archives field, and the digital humanities. This short paper and demo present how the integrated toolchain connects: 1) OpenRefine - for data reconciliation and batch upload; 2) Wikibase - for linked open data (LOD) storage; and 3) Kompakkt - for rendering and annotating 3D models. The presentation is aimed at librarians, digital curators and data managers interested in learning how to manage research datasets containing 3D media, and how to make them available within an open data environment with 3D-rendering and collaborative annotation features.
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    Open-Access-Finanzierung
    (Bonn : Bundesinstitut für Berufsbildung (BIBB), 2022) Kändler, Ulrike; Wohlgemuth, Michael; Ertl, Hubert; Rödel, Bodo
    [no abstract available]
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    Meetings and Mood-Related or Not? Insights from Student Software Projects
    (New York : Association for Computing Machinery, 2022) Klünder, Jil; Karras, Oliver; Madeiral, Fernanda; Lassenius, Casper
    [Background:] Teamwork, coordination, and communication are a prerequisite for the timely completion of a software project. Meetings as a facilitator for coordination and communication are an established medium for information exchange. Analyses of meetings in software projects have shown that certain interactions in these meetings, such as proactive statements followed by supportive ones, influence the mood and motivation of a team, which in turn affects its productivity. So far, however, research has focused only on certain interactions at a detailed level, requiring a complex and fine-grained analysis of a meeting itself. [Aim:] In this paper, we investigate meetings from a more abstract perspective, focusing on the polarity of the statements, i.e., whether they appear to be positive, negative, or neutral. [Method:] We analyze the relationship between the polarity of statements in meetings and different social aspects, including conflicts as well as the mood before and after a meeting. [Results:] Our results emerge from 21 student software project meetings and show some interesting insights: (1) Positive mood before a meeting is both related to the amount of positive statements in the beginning, as well as throughout the whole meeting, (2) negative mood before the meeting only influences the amount of negative statements in the first quarter of the meeting, but not the whole meeting, and (3) the amount of positive and negative statements during the meeting has no influence on the mood afterwards. [Conclusions:] We conclude that the behaviour in meetings might rather influence short-term emotional states (feelings) than long-term emotional states (mood), which are more important for the project.
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    TinyGenius: Intertwining natural language processing with microtask crowdsourcing for scholarly knowledge graph creation
    (New York,NY,United States : Association for Computing Machinery, 2022) Oelen, Allard; Stocker, Markus; Auer, Sören; Aizawa, Akiko
    As the number of published scholarly articles grows steadily each year, new methods are needed to organize scholarly knowledge so that it can be more efficiently discovered and used. Natural Language Processing (NLP) techniques are able to autonomously process scholarly articles at scale and to create machine readable representations of the article content. However, autonomous NLP methods are by far not sufficiently accurate to create a high-quality knowledge graph. Yet quality is crucial for the graph to be useful in practice. We present TinyGenius, a methodology to validate NLP-extracted scholarly knowledge statements using microtasks performed with crowdsourcing. The scholarly context in which the crowd workers operate has multiple challenges. The explainability of the employed NLP methods is crucial to provide context in order to support the decision process of crowd workers. We employed TinyGenius to populate a paper-centric knowledge graph, using five distinct NLP methods. In the end, the resulting knowledge graph serves as a digital library for scholarly articles.
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    Anne Baillot: From Handwriting to Footprinting: Text and Heritage in the Age of Climate Crisis. Cambridge: Open Book Publishers, 2023, 179 Seiten, ISBN 978-1-80511-089-7, https://doi.org/10.11647/OBP.0355
    (Berlin : Walter de Gruyter, 2024-05-04) Schmeja, Stefan
    Reviewed Publication: Baillot Anne From Handwriting to Footprinting: Text and Heritage in the Age of Climate Crisis Cambridge Open Book Publishers 2023 179 Seiten ISBN 978-1-80511-089-7, https://doi.org/10.11647/OBP.0355
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    An Approach to Evaluate User Interfaces in a Scholarly Knowledge Communication Domain
    (Cham : Springer, 2023) Obrezkov, Denis; Oelen, Allard; Auer, Sören; Abdelnour-Nocera, José L.; Marta Lárusdóttir; Petrie, Helen; Piccinno, Antonio; Winckler, Marco
    The amount of research articles produced every day is overwhelming: scholarly knowledge is getting harder to communicate and easier to get lost. A possible solution is to represent the information in knowledge graphs: structures representing knowledge in networks of entities, their semantic types, and relationships between them. But this solution has its own drawback: given its very specific task, it requires new methods for designing and evaluating user interfaces. In this paper, we propose an approach for user interface evaluation in the knowledge communication domain. We base our methodology on the well-established Cognitive Walkthough approach but employ a different set of questions, tailoring the method towards domain-specific needs. We demonstrate our approach on a scholarly knowledge graph implementation called Open Research Knowledge Graph (ORKG).
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    An AI-based open recommender system for personalized labor market driven education
    (Amsterdam [u.a.] : Elsevier Science, 2022) Tavakoli, Mohammadreza; Faraji, Abdolali; Vrolijk, Jarno; Molavi, Mohammadreza; Mol, Stefan T.; Kismihók, Gábor
    Attaining those skills that match labor market demand is getting increasingly complicated, not in the last place in engineering education, as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Anticipating and addressing such dynamism is a fundamental challenge to twenty-first century education. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. In this paper, we propose a novel, Artificial Intelligence (AI) driven approach to the development of an open, personalized, and labor market oriented learning recommender system, called eDoer. We discuss the complete system development cycle starting with a systematic user requirements gathering, and followed by system design, implementation, and validation. Our recommender prototype (1) derives the skill requirements for particular occupations through an analysis of online job vacancy announcements
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    NFDI4Chem - A Research Data Network for International Chemistry
    (Berlin : De Gruyter, 2023) Steinbeck, Christoph; Koepler, Oliver; Herres-Pawlis, Sonja; Bach, Felix; Jung, Nicole; Razum, Matthias; Liermann, Johannes C.; Neumann, Steffen
    Research data provide evidence for the validation of scientific hypotheses in most areas of science. Open access to them is the basis for true peer review of scientific results and publications. Hence, research data are at the heart of the scientific method as a whole. The value of openly sharing research data has by now been recognized by scientists, funders and politicians. Today, new research results are increasingly obtained by drawing on existing data. Many organisations such as the Research Data Alliance (RDA), the goFAIR initiative, and not least IUPAC are supporting and promoting the collection and curation of research data. One of the remaining challenges is to find matching data sets, to understand them and to reuse them for your own purpose. As a consequence, we urgently need better research data management.
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    Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets
    (Paris : CODATA, 2022) Peng, Ge; Lacagnina, Carlo; Downs, Robert R.; Ganske, Anette; Ramapriyan, Hampapuram K.; Ivánová, Ivana; Wyborn, Lesley; Jones, Dave; Bastin, Lucy; Shie, Chung-lin; Moroni, David F.
    Open-source science builds on open and free resources that include data, metadata, software, and workflows. Informed decisions on whether and how to (re)use digital datasets are dependent on an understanding about the quality of the underpinning data and relevant information. However, quality information, being difficult to curate and often context specific, is currently not readily available for sharing within and across disciplines. To help address this challenge and promote the creation and (re)use of freely and openly shared information about the quality of individual datasets, members of several groups around the world have undertaken an effort to develop international community guidelines with practical recommendations for the Earth science community, collaborating with international domain experts. The guidelines were inspired by the guiding principles of being findable, accessible, interoperable, and reusable (FAIR). Use of the FAIR dataset quality information guidelines is intended to help stakeholders, such as scientific data centers, digital data repositories, and producers, publishers, stewards and managers of data, to: i) capture, describe, and represent quality information of their datasets in a manner that is consistent with the FAIR Guiding Principles; ii) allow for the maximum discovery, trust, sharing, and reuse of their datasets; and iii) enable international access to and integration of dataset quality information. This article describes the processes that developed the guidelines that are aligned with the FAIR principles, presents a generic quality assessment workflow, describes the guidelines for preparing and disseminating dataset quality information, and outlines a path forward to improve their disciplinary diversity.