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- ItemRADAR-Team stellt Testsystem auf zweitem Projekt-Workshop in Frankfurt vor(Karlsruhe : KIT, 2015) Potthoff, Jan; Razum, Matthias; Kraft, AngelinaIm Rahmen des Projekts "Research Data Repository" (RADAR) wurde am 23. Juni 2015 auf dem zweiten Projekt-Workshop der aktuelle Stand des Testsystems, das zur Archivierung und Publikation von Forschungsdaten genutzt werden kann, vorgestellt. Außerdem wurden weitere Anforderungen an das System und allgemeine Fragen des Forschungsdatenmanagements mit den Workshop-Teilnehmern diskutiert.
- ItemThe impact of the covid-19 pandemic on theworking conditions, employment, career development and well-being of refugee researchers(Basel : MDPI, 2021) Tzoraki, Ourania; Dimitrova, Svetlana; Barzakov, Marin; Yaseen, Saad; Gavalas, Vasilis; Harb, Hani; Haidari, Abas; Cahill, Brian P.; Ćulibrk, Alexandra; Nikolarea, Ekaterini; Andrianopulu, Eleni; Trajanovic, MiroslavThe ongoing ‘refugee crisis’ of the past years has led to the migration of refugee researchers (RRs) to European countries. Due to the COVID-19 pandemic, RRs often had to work from home and/or to continue their social, cultural and economic integration process under new conditions. An online survey carried out to explore the impact of the pandemic on the refugee researchers showed that RRs found it difficult to adapt their everyday working life to the ‘home’ setting. The majority have had neither a suitable work environment at home nor the appropriate technology. Although they stated that they are rather pleased with the measures taken by the public authorities, they expressed concern about their vulnerability due to their precarious contracts and the bureaucratic asylum procedures, as the pandemic has had a negative impact on these major issues. The majority of RRs working in academia seem not to have been affected at all as far as their income is concerned, while the majority of those employed in other sectors became unemployed during the pandemic (58%). Recommendations are provided to the public authorities and policy makers to assist RRs to mitigate the consequences of the pandemic on their life.
- ItemTowards Fair Principles for Research Information: Report on a Series of Workshops(Kyiv : Kyiv National University of Culture and Arts, 2021) Kaliuzhna, Nataliia; Altemeier, FranziskaThis 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.
- ItemBias in data-driven artificial intelligence systems - An introductory survey(Hoboken, NJ : Wiley-Blackwell, 2020) Ntoutsi, E.; Fafalios, P.; Gadiraju, U.; Iosifidis, V.; Nejdl, W.; Vidal, Maria-Esther; Ruggieri, S.; Turini, F.; Papadopoulos, S.; Krasanakis, E.; Kompatsiaris, I.; Kinder-Kurlanda, K.; Wagner, C.; Karimi, F.; Fernandez, M.; Alani, H.; Berendt, B.; Kruegel, T.; Heinze, C.; Broelemann, K.; Kasneci, G.; Tiropanis, T.; Staab, S.Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues.
- ItemScholarly event characteristics in four fields of science: a metrics-based analysis(Berlin : Springer Nature, 2020) Fathalla, S.; Vahdati, S.; Lange, C.; Auer, SörenOne of the key channels of scholarly knowledge exchange are scholarly events such as conferences, workshops, symposiums, etc.; such events are especially important and popular in Computer Science, Engineering, and Natural Sciences.However, scholars encounter problems in finding relevant information about upcoming events and statistics on their historic evolution.In order to obtain a better understanding of scholarly event characteristics in four fields of science, we analyzed the metadata of scholarly events of four major fields of science, namely Computer Science, Physics, Engineering, and Mathematics using Scholarly Events Quality Assessment suite, a suite of ten metrics.In particular, we analyzed renowned scholarly events belonging to five sub-fields within Computer Science, namely World Wide Web, Computer Vision, Software Engineering, Data Management, as well as Security and Privacy.This analysis is based on a systematic approach using descriptive statistics as well as exploratory data analysis. The findings are on the one hand interesting to observe the general evolution and success factors of scholarly events; on the other hand, they allow (prospective) event organizers, publishers, and committee members to assess the progress of their event over time and compare it to other events in the same field; and finally, they help researchers to make more informed decisions when selecting suitable venues for presenting their work.Based on these findings, a set of recommendations has been concluded to different stakeholders, involving event organizers, potential authors, proceedings publishers, and sponsors. Our comprehensive dataset of scholarly events of the aforementioned fields is openly available in a semantic format and maintained collaboratively at OpenResearch.org.
- Item3D@Technische Informationsbibliothek (TIB) : das Projekt PROBADO zeigt effiziente Möglichkeiten zur Suche in 3D-Daten. In: Web Science - die Zukunft des Internets(Hannover : Leibniz Universität Hannover, 2012) Blümel, Ina; Sens, Irinaimmer mehr digitale Wissensobjekte finden Eingang in Bibliotheken. innerhalb der Future Internet Initiative ist die TIB Mitglied der Arbeitsgruppe Internet of Contents, die Fragestellungen rund um die Erschließung und Nutzung von nichttextuellen, insbesondere audiovisuellen Daten in den Blick nimmt. Am Beispiel des Projekts PROBADO zeigen die Autorinnen, wie 3D-Modelle in die bibliothekarische Prozesskette integriert werden können.
- ItemAuthor Correction: Replication and Refinement of an Algorithm for Automated Drusen Segmentation on Optical Coherence Tomography (Scientific Reports, (2020), 10, 1, (7395), 10.1038/s41598-020-63924-6)([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Wintergerst, Maximilian W. M.; Gorgi Zadeh, Shekoufeh; Wiens, Vitalis; Thiele, Sarah; Schmitz-Valckenberg, Steffen; Holz, Frank G.; Finger, Robert P.; Schultz, ThomasCorrection to: Scientific Reports https://doi.org/10.1038/s41598-020-63924-6, published online 30 April 2020
- ItemEditorial: 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]
- ItemThe SciQA Scientific Question Answering Benchmark for Scholarly Knowledge(London : Nature Publishing Group, 2023) Auer, Sören; Barone, Dante A.C.; Bartz, Cassiano; Cortes, Eduardo G.; Jaradeh, Mohamad Yaser; Karras, Oliver; Koubarakis, Manolis; Mouromtsev, Dmitry; Pliukhin, Dmitrii; Radyush, Daniil; Shilin, Ivan; Stocker, Markus; Tsalapati, EleniKnowledge graphs have gained increasing popularity in the last decade in science and technology. However, knowledge graphs are currently relatively simple to moderate semantic structures that are mainly a collection of factual statements. Question answering (QA) benchmarks and systems were so far mainly geared towards encyclopedic knowledge graphs such as DBpedia and Wikidata. We present SciQA a scientific QA benchmark for scholarly knowledge. The benchmark leverages the Open Research Knowledge Graph (ORKG) which includes almost 170,000 resources describing research contributions of almost 15,000 scholarly articles from 709 research fields. Following a bottom-up methodology, we first manually developed a set of 100 complex questions that can be answered using this knowledge graph. Furthermore, we devised eight question templates with which we automatically generated further 2465 questions, that can also be answered with the ORKG. The questions cover a range of research fields and question types and are translated into corresponding SPARQL queries over the ORKG. Based on two preliminary evaluations, we show that the resulting SciQA benchmark represents a challenging task for next-generation QA systems. This task is part of the open competitions at the 22nd International Semantic Web Conference 2023 as the Scholarly Question Answering over Linked Data (QALD) Challenge.
- ItemA memory institution for the digital age(Novosibirsk : Red.-Izdat. Otdel, 2020) Arndt, Susanne; Begoin, Mathias; Runnwerth, MilaThe 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.