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End date: 2022 × Start date: 2020 × DDC: 020 × Has files: Yes × Version: publishedVersion ×

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Now showing 1 - 10 of 119
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    Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners
    (Setúbal, Portugal : Science and Technology Publications, Lda, 2020) Tavakoli, Mohammadreza; Mol, Stefan; Kismihók, Gábor; Lane, H. Chad; Zvacek, Susan; Uhomoibhi, James
    In this paper, we suggest a novel method to aid lifelong learners to access relevant OER based learning content to master skills demanded on the labour market. Our software prototype 1) applies Text Classification and Text Mining methods on vacancy announcements to decompose jobs into meaningful skills components, which lifelong learners should target; and 2) creates a hybrid OER Recommender System to suggest personalized learning content for learners to progress towards their skill targets. For the first evaluation of this prototype we focused on two job areas: Data Scientist, and Mechanical Engineer. We applied our skill extractor approach and provided OER recommendations for learners targeting these jobs. We conducted in-depth, semi-structured interviews with 12 subject matter experts to learn how our prototype performs in terms of its objectives, logic, and contribution to learning. More than 150 recommendations were generated, and 76.9% of these recommendations were treated as us eful by the interviewees. Interviews revealed that a personalized OER recommender system, based on skills demanded by labour market, has the potential to improve the learning experience of lifelong learners.
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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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    International Conferences of Bibliometrics
    (München : De Gruyter Saur, 2021) Fraumann, Grischa; Mugnaino, Rogério; Sanz-Casado, Elías; Ball, Rafael
    Conferences are deeply connected to research fields, in this case bibliometrics. As such, they are a venue to present and discuss current and innovative research, and play an important role for the scholarly community. In this article, we provide an overview on the history of conferences in bibliometrics. We conduct an analysis to list the most prominent conferences that were announced in the newsletter by ISSI, the International Society for Scientometrics and Informetrics. Furthermore, we describe how conferences are connected to learned societies and journals. Finally, we provide an outlook on how conferences might change in future.
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    Case Study: ENVRI Science Demonstrators with D4Science
    (Cham : Springer, 2020) Candela, Leonardo; Stocker, Markus; Häggström, Ingemar; Enell, Carl-Fredrik; Vitale, Domenico; Papale, Dario; Grenier, Baptiste; Chen, Yin; Obst, Matthias; Zhao, Zhiming; Hellström, Margareta
    Whenever a community of practice starts developing an IT solution for its use case(s) it has to face the issue of carefully selecting “the platform” to use. Such a platform should match the requirements and the overall settings resulting from the specific application context (including legacy technologies and solutions to be integrated and reused, costs of adoption and operation, easiness in acquiring skills and competencies). There is no one-size-fits-all solution that is suitable for all application context, and this is particularly true for scientific communities and their cases because of the wide heterogeneity characterising them. However, there is a large consensus that solutions from scratch are inefficient and services that facilitate the development and maintenance of scientific community-specific solutions do exist. This chapter describes how a set of diverse communities of practice efficiently developed their science demonstrators (on analysing and producing user-defined atmosphere data products, greenhouse gases fluxes, particle formation, mosquito diseases) by leveraging the services offered by the D4Science infrastructure. It shows that the D4Science design decisions aiming at streamlining implementations are effective. The chapter discusses the added value injected in the science demonstrators and resulting from the reuse of D4Science services, especially regarding Open Science practices and overall quality of service.
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    Modelling Archival Hierarchies in Practice: Key Aspects and Lessons Learned
    (Aachen, Germany : RWTH Aachen, 2021) Vafaie, Mahsa; Bruns, Oleksandra; Pilz, Nastasja; Dessì, Danilo; Sack, Harald; Sumikawa, Yasunobu; Ikejiri, Ryohei; Doucet, Antoine; Pfanzelter, Eva; Hasanuzzaman, Mohammed; Dias, Gaël; Milligan, Ian; Jatowt, Adam
    An increasing number of archival institutions aim to provide public access to historical documents. Ontologies have been designed, developed and utilised to model the archival description of historical documents and to enable interoperability between different information sources. However, due to the heterogeneous nature of archives and archival systems, current ontologies for the representation of archival content do not always cover all existing structural organisation forms equallywell. After briefly contextualising the heterogeneity in the hierarchical structure of German archives, this paper describes and evaluates differences between two archival ontologies, ArDO and RiC-O, and their approaches to modelling hierarchy levels and archive dynamics.
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    DDB-KG: The German Bibliographic Heritage in a Knowledge Graph
    (Aachen, Germany : RWTH Aachen, 2021) Tan, Mary Ann; Tietz, Tabea; Bruns, Oleksandra; Oppenlaender, Jonas; Dessì, Danilo; Harald, Sack; Sumikawa, Yasunobu; Ikejiri, Ryohei; Doucet, Antoine; Pfanzelter, Eva; Hasanuzzaman, Mohammed; Dias, Gaël; Milligan, Ian; Jatowt, Adam
    Under the German government’s initiative “NEUSTART Kultur”, the German Digital Library or Deutsche Digitale Bibliothek (DDB) is undergoing improvements to enhance user-experience. As an initial step, emphasis is placed on creating a knowledge graph from the bibliographic record collection of the DDB. This paper discusses the challenges facing the DDB in terms of retrieval and the solutions in addressing them. In particular, limitations of the current data model or ontology to represent bibliographic metadata is analyzed through concrete examples. This study presents the complete ontological mapping from DDB-Europeana Data Model (DDB-EDM) to FaBiO, and a prototype of the DDB-KG made available as a SPARQL endpoint. The suitabiliy of the target ontology is demonstrated with SPARQL queries formulated from competency questions.
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    Eigenfactor
    (München : De Gruyter Saur, 2021) Fraumann, Grischa; D'Souza, Jennifer; Holmberg, Kim
    The Eigenfactor™ is a journal metric, which was developed by Bergstrom and his colleagues at the University of Washington. They invented the Eigenfactor as a response to the criticism against the use of simple citation counts. The Eigenfactor makes use of the network structure of citations, i.e. citations between journals, and establishes the importance, influence or impact of a journal based on its location in a network of journals. The importance is defined based on the number of citations between journals. As such, the Eigenfactor algorithm is based on Eigenvector centrality. While journal based metrics have been criticized, the Eigenfactor has also been suggested as an alternative in the widely used San Francisco Declaration on ResearchAssessment (DORA).
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    Semantic and Knowledge Engineering Using ENVRI RM
    (Cham : Springer, 2020) Martin, Paul; Liao, Xiaofeng; Magagna, Barbara; Stocker, Markus; Zhao, Zhiming; Zhao, Zhiming; Hellström, Margareta
    The ENVRI Reference Model provides architects and engineers with the means to describe the architecture and operational behaviour of environmental and Earth science research infrastructures (RIs) in a standardised way using the standard terminology. This terminology and the relationships between specific classes of concept can be used as the basis for the machine-actionable specification of RIs or RI subsystems. Open Information Linking for Environmental RIs (OIL-E) is a framework for capturing architectural and design knowledge about environmental and Earth science RIs intended to help harmonise vocabulary, promote collaboration and identify common standards and technologies across different research infrastructure initiatives. At its heart is an ontology derived from the ENVRI Reference Model. Using this ontology, RI descriptions can be published as linked data, allowing discovery, querying and comparison using established Semantic Web technologies. It can also be used as an upper ontology by which to connect descriptions of RI entities (whether they be datasets, equipment, processes, etc.) that use other, more specific terminologies. The ENVRI Knowledge Base uses OIL-E to capture information about environmental and Earth science RIs in the ENVRI community for query and comparison. The Knowledge Base can be used to identify the technologies and standards used for particular activities and services and as a basis for evaluating research infrastructure subsystems and behaviours against certain criteria, such as compliance with the FAIR data principles.
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    Towards Operational Research Infrastructures with FAIR Data and Services
    (Cham : Springer, 2020) Zhao, Zhiming; Jeffery, Keith; Stocker, Markus; Atkinson, Malcolm; Petzold, Andreas; Zhao, Zhiming; Hellström, Margareta
    Environmental research infrastructures aim to provide scientists with facilities, resources and services to enable scientists to effectively perform advanced research. When addressing societal challenges such as climate change and pollution, scientists usually need data, models and methods from different domains to tackle the complexity of the complete environmental system. Research infrastructures are thus required to enable all data, including services, products, and virtual research environments is FAIR for research communities: Findable, Accessible, Interoperable and Reusable. In this last chapter, we conclude and identify future challenges in research infrastructure operation, user support, interoperability, and future evolution.
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    Wie FAIR sind unsere Metadaten? : Eine Analyse der Metadaten in den Repositorien des TIB-DOI-Services
    (Marburg : Philipps-Universität, 2021) Burger, Marleen; Cordts, Anette; Habermann, Ted
    Im vorliegenden Erfahrungsbericht stellen wir eine Metadatenanalyse vor, welche die Metadatenqualität von 144 Repositorien des TIB-DOI-Service im Hinblick auf die Erfüllung der FAIR Data Principles, Konsistenz und Vollständigkeit untersucht. Im Ergebnis zeigt sich, dass der Fokus der untersuchten Repositorien schwerpunktmäßig auf der Auffindbarkeit der mit Metadaten beschriebenen Ressourcen liegt und im Gesamtdurchschnitt über die Metadaten-Pflichtfelder hinaus nur wenige weitere Metadaten angegeben werden. Insbesondere mit Blick auf eine angestrebte bessere Nachnutzbarkeit sowie eine stärkere Verknüpfung mit anderen in Beziehung stehenden persistenten Identifikatoren wie ORCID, ROR ID oder DOI-zu-DOI-Beziehungen mit zitierten oder zitierenden Ressourcen, bestehen noch ungenutzte Potenziale, die im Sinne einer offenen, zukunftsweisenden Wissenschaft erschlossen werden sollten. Dahingegen zeigt unsere Analyse auch einzelne Repositorien mit umfangreichen Metadaten als Best-Practice-Beispiele auf, an denen sich andere Repositorien orientieren können. Insgesamt ermöglicht die durchgeführte Metadatenanalyse die Ableitung von Handlungsempfehlungen zur passgenauen Beratung von Repositorien, die ihre Metadatenqualität verbessern möchten.