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Abstract

In einem aktuellen Beitrag von Open Password (#664, 19. November ) zu einer Veranstaltung des Berliner Arbeitskreises Information unter dem Titel "Zukunft der Informationswissenschaft. Hat die Informationswissenschaft eine Zukunft?" nimmt der Herausgeber des gleichnamigen Buches, Dr. Willi Bredemeier, die Rolle eines Berichterstatters ein. Vorgestellt werden die Inhalte eines Vortrages des Hamburger HAW-Referenten, Prof. Dr. Dirk Lewandowski, zum Thema: "Warum die Frage nach der Zukunft der Informationswissenschaft falsch gestellt ist". Dem Bericht darüber in Open Password wurde der Titel "Die Informationswissenschaft hat ein strukturelles, kein inhaltliches Problem. Ein Sechs-Punkte-Programm, um aus dem Status eines kleinen Faches herauszukommen" gegeben.

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Footnote

Vortrag im Rahmen des Berliner Arbeitskreis Information (BAK) am 25.02.2021.

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Content

This study investigates the development of open access (OA) to journal articles from authors affiliated with German universities and non-university research institutions in the period 2010-2018. Beyond determining the overall share of openly available articles, a systematic classification of distinct categories of OA publishing allowed us to identify different patterns of adoption of OA. Taking into account the particularities of the German research landscape, variations in terms of productivity, OA uptake and approaches to OA are examined at the meso-level and possible explanations are discussed. The development of the OA uptake is analysed for the different research sectors in Germany (universities, non-university research institutes of the Helmholtz Association, Fraunhofer Society, Max Planck Society, Leibniz Association, and government research agencies). Combining several data sources (incl. Web of Science, Unpaywall, an authority file of standardised German affiliation information, the ISSN-Gold-OA 3.0 list, and OpenDOAR), the study confirms the growth of the OA share mirroring the international trend reported in related studies. We found that 45% of all considered articles during the observed period were openly available at the time of analysis. Our findings show that subject-specific repositories are the most prevalent type of OA. However, the percentages for publication in fully OA journals and OA via institutional repositories show similarly steep increases. Enabling data-driven decision-making regarding the implementation of OA in Germany at the institutional level, the results of this study furthermore can serve as a baseline to assess the impact recent transformative agreements with major publishers will likely have on scholarly communication.

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Abstract

Schon die Überschrift des Statements von Steve Patriarca belegt, dass die Anhänger der "Informationskompetenz" (Information Literacy) nach wie vor von der einfachen und naiven Annahme ausgehen, dass die reine Verfügbarkeit von "Informationskompetenz" ausreicht, um "uns die Werkzeuge" zu geben, "Quellen zu prüfen und Tatsachenbehauptungen zu verifizieren". Ohne nochmals gebetsmühlenartig die Argumente gegen eine "allgemeingültige Informationskompetenz" zu wiederholen, die es als eigenständige "Kompetenz" nicht geben kann (siehe die letzten Stellungnahmen zu diesem Unbegriff in Open Password Nr. 682, 691, 759, 960, 963, 965, 971, 979 usw.), und zudem auf die dort eingebundenen Sichten der Nachbarwissenschaften (Neurowissenschaften, Kommunikationswissenschaft usw.) zu diesem unguten Terminus der Bibliotheks- und Informationswissenschaft zu verweisen, sei hier lediglich kurz klargestellt:

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Content

Der MeSH ist ein polyhierarchisches, konzeptbasiertes Schlagwortregister für biomedizinische Fachbegriffe umfasst das Vokabular, welches in den NLM-Datenbanken, beispielsweise MEDLINE oder PubMed, erscheint. Er wird jährlich aktualisiert von der U. S. National Library of Medicine herausgegeben. Für die deutschsprachige Fassung übersetzt ZB MED dann die jeweils neu hinzugekommenen Terme und ergänzt sie um zusätzliche Synonyme. Erstmalig erstellte ZB MED den Deutschen MeSH im Jahr 2020. Vorher lag die Verantwortung beim Deutschen Institut für Medizinische Dokumentation und Information (DIMDI/BfArM)."

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Abstract

Literature review articles are essential to summarize the related work in the selected field. However, covering all related studies takes too much time and effort. This study questions how Artificial Intelligence can be used in this process. We used ChatGPT to create a literature review article to show the stage of the OpenAI ChatGPT artificial intelligence application. As the subject, the applications of Digital Twin in the health field were chosen. Abstracts of the last three years (2020, 2021 and 2022) papers were obtained from the keyword "Digital twin in healthcare" search results on Google Scholar and paraphrased by ChatGPT. Later on, we asked ChatGPT questions. The results are promising; however, the paraphrased parts had significant matches when checked with the Ithenticate tool. This article is the first attempt to show the compilation and expression of knowledge will be accelerated with the help of artificial intelligence. We are still at the beginning of such advances. The future academic publishing process will require less human effort, which in turn will allow academics to focus on their studies. In future studies, we will monitor citations to this study to evaluate the academic validity of the content produced by the ChatGPT. 1. Introduction OpenAI ChatGPT (ChatGPT, 2022) is a chatbot based on the OpenAI GPT-3 language model. It is designed to generate human-like text responses to user input in a conversational context. OpenAI ChatGPT is trained on a large dataset of human conversations and can be used to create responses to a wide range of topics and prompts. The chatbot can be used for customer service, content creation, and language translation tasks, creating replies in multiple languages. OpenAI ChatGPT is available through the OpenAI API, which allows developers to access and integrate the chatbot into their applications and systems. OpenAI ChatGPT is a variant of the GPT (Generative Pre-trained Transformer) language model developed by OpenAI. It is designed to generate human-like text, allowing it to engage in conversation with users naturally and intuitively. OpenAI ChatGPT is trained on a large dataset of human conversations, allowing it to understand and respond to a wide range of topics and contexts. It can be used in various applications, such as chatbots, customer service agents, and language translation systems. OpenAI ChatGPT is a state-of-the-art language model able to generate coherent and natural text that can be indistinguishable from text written by a human. As an artificial intelligence, ChatGPT may need help to change academic writing practices. However, it can provide information and guidance on ways to improve people's academic writing skills.

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Abstract

Human brain size nearly quadrupled in the six million years since Homo last shared a common ancestor with chimpanzees, but human brains are thought to have decreased in volume since the end of the last Ice Age. The timing and reason for this decrease is enigmatic. Here we use change-point analysis to estimate the timing of changes in the rate of hominin brain evolution. We find that hominin brains experienced positive rate changes at 2.1 and 1.5 million years ago, coincident with the early evolution of Homo and technological innovations evident in the archeological record. But we also find that human brain size reduction was surprisingly recent, occurring in the last 3,000 years. Our dating does not support hypotheses concerning brain size reduction as a by-product of body size reduction, a result of a shift to an agricultural diet, or a consequence of self-domestication. We suggest our analysis supports the hypothesis that the recent decrease in brain size may instead result from the externalization of knowledge and advantages of group-level decision-making due in part to the advent of social systems of distributed cognition and the storage and sharing of information. Humans live in social groups in which multiple brains contribute to the emergence of collective intelligence. Although difficult to study in the deep history of Homo, the impacts of group size, social organization, collective intelligence and other potential selective forces on brain evolution can be elucidated using ants as models. The remarkable ecological diversity of ants and their species richness encompasses forms convergent in aspects of human sociality, including large group size, agrarian life histories, division of labor, and collective cognition. Ants provide a wide range of social systems to generate and test hypotheses concerning brain size enlargement or reduction and aid in interpreting patterns of brain evolution identified in humans. Although humans and ants represent very different routes in social and cognitive evolution, the insights ants offer can broadly inform us of the selective forces that influence brain size.