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- ItemOER-Projekt twillo(Graz : Verein Forum Neue Medien in der Lehre Austria , 2022) Plank, Margret; Krause, Noreen; Beutnagel, Britta[No abstract available]
- ItemWie FAIR sind unsere Metadaten? : Eine Analyse der Metadaten in den Repositorien des TIB-DOI-Services(Marburg : Philipps-Universität, 2021) Burger, Marleen; Cordts, Anette; Habermann, TedIm 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.
- ItemBEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data(Sofia : Pensoft Publishers, 2021) Chamanara, Javad; Gaikwad, Jitendra; Gerlach, Roman; Algergawy, Alsayed; Ostrowski, Andreas; König-Ries, BirgittaObtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research.
- ItemAnne 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, StefanReviewed 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
- ItemZertifizierung von Forschungsdatenrepositorien: Wege, Praxiserfahrungen und Perspektiven : 10. Workshop der DINI/nestor-AG Forschungsdaten(Marburg : Philipps-Universität, 2020) Recker, Jonas; Helbig, Kerstin; Neumann, JannaDie DINI/nestor-AG Forschungsdaten führte am 5. März 2020 einen Workshop zum Thema Zertifizierung von Forschungsdatenrepositorien[1] an der Universitätsbibliothek Leipzig durch. Motiviert war die Veranstaltung durch den Wunsch, Teilnehmer*innen einen Überblick über relevante Zertifizierungsverfahren zu geben und Vorteile einer Zertifizierung herauszustellen. Gleichzeitig diente die Veranstaltung dem Austausch über Anforderungen und Unterstützungsbedarfe seitens der Repositorien. Trotz einer Reihe von Corona-bedingten Absagen und Vortragsausfällen verfolgten insgesamt 50 Teilnehmende die Vorträge und nahmen an der lebhaften Breakoutsession teil. Dieser Beitrag bereitet die Informationen und Anregungen aus den Diskussionen auf und skizziert erste Lösungsansätze zum Abbau identifizierter Hürden.
- ItemAn 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, GáborAttaining 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
- ItemCall to action for global access to and harmonization of quality information of individual earth science datasets(Paris : CODATA, 2021) Peng, Ge; Downs, Robert R.; Lacagnina, Carlo; Ramapriyan, Hampapuram; Ivánová, Ivana; Moroni, David; Wei, Yaxing; Larnicol, Gilles; Wyborn, Lesley; Goldberg, Mitch; Schulz, Jörg; Bastrakova, Irina; Ganske, Anette; Bastin, Lucy; Khalsa, Siri Jodha S.; Wu, Mingfang; Shie, Chung-Lin; Ritchey, Nancy; Jones, Dave; Habermann, Ted; Lief, Christina; Maggio, Iolanda; Albani, Mirko; Stall, Shelley; Zhou, Lihang; Drévillon, Marie; Champion, Sarah; Hou, C. Sophie; Doblas-Reyes, Francisco; Lehnert, Kerstin; Robinson, Erin; Bugbee, KaylinKnowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision- and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science.
- ItemNFDI4Chem - 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, SteffenResearch 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.
- ItemGlobal 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.
- ItemPersistent Identification for Conferences(Paris : CODATA, 2022) Franken, Julian; Birukou, Aliaksandr; Eckert, Kai; Fahl, Wolfgang; Hauschke, Christian; Lange, ChristophPersistent identification of entities plays a major role in the progress of digitization of many fields. In the scholarly publishing realm there are already persistent identifiers (PID) for papers (DOI), people (ORCID), organisation (GRID, ROR), books (ISBN) but there is no generally accepted PID system for scholarly events such as conferences or workshops yet. This article describes the relevant use cases that motivate the introduction of persistent identifiers for conferences. The use cases were mainly derived from interviews, discussions with experts and their previous work. As primary stakeholders who are involved in the typical conference event life cycle researchers, conference organizers, and data consumers were identified. The resulting list of use cases illustrates how PIDs for conference events will improve the current situation for these stakeholders and help with problems they are facing today.