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Start date: 2016 × DDC: 020 × Type: article ×

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Now showing 1 - 4 of 4
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    Towards Fair Principles for Research Information: Report on a Series of Workshops
    (Kyiv : Kyiv National University of Culture and Arts, 2021) Kaliuzhna, Nataliia; Altemeier, Franziska
    This is a summary report of the series of workshops on FAIR research information in open infrastructures that was jointly organised by the State Scientific and Technical Library of Ukraine (SSTL) and Leibniz Information Centre for Science and Technology (TIB) which have been collaborating under the framework of Joint German-Ukrainian project supported by the Federal Ministry of Education and Research of Germany and the Ministry of Science and Education of Ukraine. The workshops successfully harnessed the enthusiasm and experience of librarians, researchers, software providers, public funding body representatives, content providers, scientometricians and information specialists in an attempt to shed light and define criteria which assist discovery and reuse of research information by third-parties and make it FAIR. The series of workshops consisted of four separate workshops which addressed single aspects of FAIR– findability, accessibility, interoperability and reuse concerning research information. Due to Covid-19 travel restrictions workshops were held online between September 2020 and January 2021.
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    Editorial: Wie gestalten wir die Zukunft mit Open Access und Open Educational Resources?
    (Wien : ÖGHD, 2013) Ebner, Martin; Schön, Sandra; Heller, Lambert; Mumenthaler, Rudolf
    [no abstract available]
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    A memory institution for the digital age
    (Novosibirsk : Red.-Izdat. Otdel, 2020) Arndt, Susanne; Begoin, Mathias; Runnwerth, Mila
    The German National Library for Science and Technology (TIB) seizes the opportunity of an epochal change into the Digital Age, inter alia, by maintaining a prestigious research department covering the areas data science & digital libraries, visual analytics, scientific data management, knowledge infrastructures, learning & skill analytics, open science, and non-textual media. Without neglecting the original mission of collecting and curating literature for a widespread access to scientific information, TIB merges well-established processes with intelligent assistance tools. The Specialised Information Service for Mobility and Traffic Science (FID move) is one example of combining the mentioned research areas in order to build a user-centred subject-specific research infrastructure to support and shape tomorrow’s scientific work. We give a detailed introduction to the project’s action fields: web service platform, information supply with a focus on open access, strategy & structure for reusable research data, research community exchange & networking, communication strategies for the public & for scientists. Exemplary, we present the ongoing activities in building a comprehensive knowledge organisation system for e-mobility.
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    Analyzing social media for measuring public attitudes toward controversies and their driving factors: a case study of migration
    (Wien : Springer, 2022) Chen, Yiyi; Sack, Harald; Alam, Mehwish
    Among other ways of expressing opinions on media such as blogs, and forums, social media (such as Twitter) has become one of the most widely used channels by populations for expressing their opinions. With an increasing interest in the topic of migration in Europe, it is important to process and analyze these opinions. To this end, this study aims at measuring the public attitudes toward migration in terms of sentiments and hate speech from a large number of tweets crawled on the decisive topic of migration. This study introduces a knowledge base (KB) of anonymized migration-related annotated tweets termed as MigrationsKB (MGKB). The tweets from 2013 to July 2021 in the European countries that are hosts of immigrants are collected, pre-processed, and filtered using advanced topic modeling techniques. BERT-based entity linking and sentiment analysis, complemented by attention-based hate speech detection, are performed to annotate the curated tweets. Moreover, external databases are used to identify the potential social and economic factors causing negative public attitudes toward migration. The analysis aligns with the hypothesis that the countries with more migrants have fewer negative and hateful tweets. To further promote research in the interdisciplinary fields of social sciences and computer science, the outcomes are integrated into MGKB, which significantly extends the existing ontology to consider the public attitudes toward migrations and economic indicators. This study further discusses the use-cases and exploitation of MGKB. Finally, MGKB is made publicly available, fully supporting the FAIR principles.