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- ItemDDB-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, AdamUnder 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.
- ItemOntology Design for Pharmaceutical Research Outcomes(Cham : Springer, 2020) Say, Zeynep; Fathalla, Said; Vahdati, Sahar; Lehmann, Jens; Auer, Sören; Hall, Mark; Merčun, Tanja; Risse, Thomas; Duchateau, FabienThe network of scholarly publishing involves generating and exchanging ideas, certifying research, publishing in order to disseminate findings, and preserving outputs. Despite enormous efforts in providing support for each of those steps in scholarly communication, identifying knowledge fragments is still a big challenge. This is due to the heterogeneous nature of the scholarly data and the current paradigm of distribution by publishing (mostly document-based) over journal articles, numerous repositories, and libraries. Therefore, transforming this paradigm to knowledge-based representation is expected to reform the knowledge sharing in the scholarly world. Although many movements have been initiated in recent years, non-technical scientific communities suffer from transforming document-based publishing to knowledge-based publishing. In this paper, we present a model (PharmSci) for scholarly publishing in the pharmaceutical research domain with the goal of facilitating knowledge discovery through effective ontology-based data integration. PharmSci provides machine-interpretable information to the knowledge discovery process. The principles and guidelines of the ontological engineering have been followed. Reasoning-based techniques are also presented in the design of the ontology to improve the quality of targeted tasks for data integration. The developed ontology is evaluated with a validation process and also a quality verification method.
- ItemSemantic Representation of Physics Research Data(Setúbal, Portugal : Science and Technology Publications, Lda, 2020) Say, Aysegul; Fathalla, Said; Vahdati, Sahar; Lehmann, Jens; Auer, Sören; Aveiro, David; Dietz, Jan; Filipe, JoaquimImprovements in web technologies and artificial intelligence enable novel, more data-driven research practices for scientists. However, scientific knowledge generated from data-intensive research practices is disseminated with unstructured formats, thus hindering the scholarly communication in various respects. The traditional document-based representation of scholarly information hampers the reusability of research contributions. To address this concern, we developed the Physics Ontology (PhySci) to represent physics-related scholarly data in a machine-interpretable format. PhySci facilitates knowledge exploration, comparison, and organization of such data by representing it as knowledge graphs. It establishes a unique conceptualization to increase the visibility and accessibility to the digital content of physics publications. We present the iterative design principles by outlining a methodology for its development and applying three different evaluation approaches: data-driven and criteria-based evaluation, as well as ontology testing.
- ItemOptimierte Erfassung und Veröffentlichung von Artikelmetadaten für eine nachhaltige Metadatenallmende im OA-Ökosystem zur Unterstützung von Auffindbarkeit und Evaluation(Zenodo, 2023) Nüst, Daniel; Hauschke, Christian; Coordts, Anette; Yücel, GaziDie Metadatenallmende ist ein wichtiger Baustein für den Wandel hin zu einem diversen Open-Access-Ökosystem. Nur mit offenen und hochwertigen Metadaten, die mindestens die gleiche oder sogar höhere Qualität und Abdeckung als die Metadaten-Silos etablierter kommerzieller Verlage erreichen, können unabhängige Zeitschriften auf Augenhöhe Themen wie Auffindbarkeit und faire Evaluation von Forschenden angehen. Wir stellen einen Arbeitsablauf und Werkzeuge vor, die eine Professionalisierung der Metadatenprozesse von unabhängigen, scholar-led OA-Journals unterstützen. Diese Journals können damit ihre Sichtbarkeit im Wissenschaftssystem und ihre Bedeutung als Publikationsort erhöhen. Dazu wird die global verbreitete Free and Open Source Software (FOSS) Open Journal Systems (OJS) um Funktionen erweitert, die a) Eingabe, Kuratierung und Anreicherung von artikelbezogenen Metadaten durch Autor:innen und Editor:innen und b) den Export dieser Metadaten an offene Datenquellen wie z. B. Wikidata ermöglichen. Diese Erweiterung wird durch OJS-Plugins und auch Anpassung der OJS-Kernsoftware in den folgenden Anwendungsfällen umgesetzt: Erstens ermöglicht die Integration von validierten persistenten Identifikatoren (PIDs) und geographischen Metadaten als Teil der Publikationsmetadaten eine bessere Auffindbarkeit und von Artikeln aus Open-Access-Zeitschriften. PIDs und Geometadaten stellen Verbindungen zu anderen Publikationen, akademischen Events, physischen Proben und wissenschaftlichen Instrumenten her und verknüpfen so verwandte Artikel über Zeitschriften und Wissenschaftsdisziplinen hinweg. Auf Basis dieser Metadaten werden zum Beispiel eine Suchplattform realisiert, die wissenschaftliche Artikel über Disziplingrenzen und Publikationsplatformen hinweg als offene Daten interaktiv auf einer Karte darstellt, und semantisch bedeutsame Links in Artikeln und ihren Landing Pages eingefügt. Zweitens werden Zitationsmetadaten während des Einreichungs- und Begutachtungsprozesses strukturiert erfasst und frei in standardisierten Formaten veröffentlicht. Durch die innovative und benutzerfreundliche Metadatenerfassung im Zuge des wissenschaftlichen Veröffentlichungsprozesses können Open-Access-Artikel in transparenten zitationsbasierten Evaluationsmetriken verwendet werden. Diese Neuerungen unterstützen eine offene Publikationskultur und -praxis. In diesem Beitrag berichten wir vom aktuellen Arbeitsstand zu den Anwendungsfällen und beschreiben eine Vision für eine neuartige verteilte Erfassung und Veröffentlichung offener Metadaten.
- ItemBaroque AI(Zenodo, 2023) Worthington, Simon; Blümel, InaPublication prototype: A computational publishing and AI assisted writing course unit with students of the Open Knowledge class – at Hochschule Hannover with the Open Science Lab, TIB. The prototype publication exercise involves creating a fictional ‘exhibition catalogue’ drawing on Wikidata based cataloguing of seventeenth century painting deposited by the Bavarian State Painting Collections. The prototype demostrates how computational publishing can be used to bring together different distributed linked open data (LOD) sources. Additionally AI tools are used for assisted essay writing. Then both are encapsulated in a multi-format computational publication — allowing for asynchronous collaborative working. Distributed LOD sources include: Wikidata/base, Nextcloud, Thoth, Semantic Kompakkt, and TIB AV Portal. AI tools used for essay writing are — OpenAI and Perplexity. Eleven students completed the class unit which was carried out over March to April 2023. An open access OER guide to running the class, a template publication for use in the class are online on GitHub and designed for OER reuse. Full class information and resources are on Wikiversity. The open source software used is brought together in the ADA Pipeline.
- ItemCausal Relationship over Knowledge Graphs(2022) Huang, Hao; Al Hasan, Mohammad; Xiong, LiCausality has been discussed for centuries, and the theory of causal inference over tabular data has been broadly studied and utilized in multiple disciplines. However, only a few works attempt to infer the causality while exploiting the meaning of the data represented in a data structure like knowledge graph. These works offer a glance at the possibilities of causal inference over knowledge graphs, but do not yet consider the metadata, e.g., cardinalities, class subsumption and overlap, and integrity constraints. We propose CareKG, a new formalism to express causal relationships among concepts, i.e., classes and relations, and enable causal queries over knowledge graphs using semantics of metadata. We empirically evaluate the expressiveness of CareKG in a synthetic knowledge graph concerning cardinalities, class subsumption and overlap, integrity constraints. Our initial results indicate that CareKG can represent and measure causal relations with some semantics which are uncovered by state-of-the-art approaches.
- ItemTowards Analyzing the Bias of News Recommender Systems Using Sentiment and Stance Detection(New York,NY,United States : Association for Computing Machinery, 2022) Alam, Mehwish; Iana, Andreea; Grote, Alexander; Ludwig, Katharina; Müller, Philipp; Paulheim, Heiko; Laforest, Frédérique; Troncy, Raphael; Médini, Lionel; Herman, IvanNews recommender systems are used by online news providers to alleviate information overload and to provide personalized content to users. However, algorithmic news curation has been hypothesized to create filter bubbles and to intensify users' selective exposure, potentially increasing their vulnerability to polarized opinions and fake news. In this paper, we show how information on news items' stance and sentiment can be utilized to analyze and quantify the extent to which recommender systems suffer from biases. To that end, we have annotated a German news corpus on the topic of migration using stance detection and sentiment analysis. In an experimental evaluation with four different recommender systems, our results show a slight tendency of all four models for recommending articles with negative sentiments and stances against the topic of refugees and migration. Moreover, we observed a positive correlation between the sentiment and stance bias of the text-based recommenders and the preexisting user bias, which indicates that these systems amplify users' opinions and decrease the diversity of recommended news. The knowledge-aware model appears to be the least prone to such biases, at the cost of predictive accuracy.
- ItemAn OER Recommender System Supporting Accessibility Requirements(New York : Association for Computing Machinery, 2020) Elias, Mirette; Tavakoli, Mohammadreza; Lohmann, Steffen; Kismihok, Gabor; Auer, Sören; Gurreiro, Tiago; Nicolau, Hugo; Moffatt, KarynOpen Educational Resources are becoming a significant source of learning that are widely used for various educational purposes and levels. Learners have diverse backgrounds and needs, especially when it comes to learners with accessibility requirements. Persons with disabilities have significantly lower employment rates partly due to the lack of access to education and vocational rehabilitation and training. It is not surprising therefore, that providing high quality OERs that facilitate the self-development towards specific jobs and skills on the labor market in the light of special preferences of learners with disabilities is difficult. In this paper, we introduce a personalized OER recommeder system that considers skills, occupations, and accessibility properties of learners to retrieve the most adequate and high-quality OERs. This is done by: 1) describing the profile of learners with disabilities, 2) collecting and analysing more than 1,500 OERs, 3) filtering OERs based on their accessibility features and predicted quality, and 4) providing personalised OER recommendations for learners according to their accessibility needs. As a result, the OERs retrieved by our method proved to satisfy more accessibility checks than other OERs. Moreover, we evaluated our results with five experts in educating people with visual and cognitive impairments. The evaluation showed that our recommendations are potentially helpful for learners with accessibility needs.
- ItemORCID Germany Consortium - Numbers and Figures(Meyrin : CERN , 2018) Vierkant, Paul; Pampel, Heinz; Bertelmann, Roland; Dreyer, BrittaThis poster shows the development and status of the ORCID Germany Consortium.
- Itemopen-access.network. Wie gestalten wir die Zukunft?(Zenodo, 2023) Benz, Martina; Kirchner, Andreas; Mikautsch, Emilia; Strauß, HeleneDas Poster "open-access.network. Wie gestalten wir die Zukunft?" wurde im Rahmen des BMBF-geförderten Projekts open.access-network erstellt und für die Open-Access-Tage 2023 angenommen. Das Poster skizziert den Weg zur Verstetigung des Kompetenz- und Vernetzungsportals open-access.network. Mit Blick auf das Ziel eines Community-basierten Organisations- und Finanzierungsmodells, wird aktiv zur Interaktion mit dem Poster sowie zur Ideen- und Meinungsäußerung zur Verstetigung eingeladen.