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Now showing 1 - 10 of 322
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    Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners
    (Setúbal, Portugal : Science and Technology Publications, Lda, 2020) Tavakoli, Mohammadreza; Mol, Stefan; Kismihók, Gábor; Lane, H. Chad; Zvacek, Susan; Uhomoibhi, James
    In this paper, we suggest a novel method to aid lifelong learners to access relevant OER based learning content to master skills demanded on the labour market. Our software prototype 1) applies Text Classification and Text Mining methods on vacancy announcements to decompose jobs into meaningful skills components, which lifelong learners should target; and 2) creates a hybrid OER Recommender System to suggest personalized learning content for learners to progress towards their skill targets. For the first evaluation of this prototype we focused on two job areas: Data Scientist, and Mechanical Engineer. We applied our skill extractor approach and provided OER recommendations for learners targeting these jobs. We conducted in-depth, semi-structured interviews with 12 subject matter experts to learn how our prototype performs in terms of its objectives, logic, and contribution to learning. More than 150 recommendations were generated, and 76.9% of these recommendations were treated as us eful by the interviewees. Interviews revealed that a personalized OER recommender system, based on skills demanded by labour market, has the potential to improve the learning experience of lifelong learners.
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    Translating the Concept of Goal Setting into Practice: What ‘else’ Does It Require than a Goal Setting Tool?
    (Setúbal, Portugal : Science and Technology Publications, Lda, 2020) Kismihók, Gábor; Zhao, Catherine; Schippers, Michaéla; Mol, Stefan; Harrison, Scott; Shehata, Shady; Lane, H. Chad; Zvacek, Susan; Uhomoibhi, James
    This conceptual paper reviews the current status of goal setting in the area of technology enhanced learning and education. Besides a brief literature review, three current projects on goal setting are discussed. The paper shows that the main barriers for goal setting applications in education are not related to the technology, the available data or analytical methods, but rather the human factor. The most important bottlenecks are the lack of students’ goal setting skills and abilities, and the current curriculum design, which, especially in the observed higher education institutions, provides little support for goal setting interventions.
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    Unveiling Relations in the Industry 4.0 Standards Landscape Based on Knowledge Graph Embeddings
    (Cham : Springer, 2020) Rivas, Ariam; Grangel-González, Irlán; Collarana, Diego; Lehmann, Jens; Vidal, Maria-Esther; Hartmann, Sven; Küng, Josef; Kotsis, Gabriele; Tjoa, A Min; Khalil, Ismail
    Industry 4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of empowering interoperability in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans∗ family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.
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    Renegotiating Open-Access-Licences for Scientific Films
    (Amsterdam : IOS Press, 2016) Brehm, Elke
    Scientific publishing is not limited to text any more, but more and more extends also to digital audio-visual media. Thus services for publishing these media in portals designed for scientific content, oriented towards the demands of scientists and which comply with the requirements of Open Access Licenses must be provided. Among others, it is the goal of the Competence Centre for Non-textual-materials of TIB to collect, archive and provide access to scientific audio-visual media in the TIB AV-Portal under the best possible (open) conditions. This applies to older films, as for example the film collection of the former IWF Knowledge and Media gGmbH i. L. (IWF) and to new films. However, even if the acquisition of the necessary rights for audio-visual media is complex, the renegotiation of Open-Access- Licenses for older films is very successful. This paper focuses on the role of Open Access in the licensing strategy of TIB regarding scientific films, the respective experience of TIB and the presentation in the AV-Portal, but also touches upon prerequisites and procedures for the use of Orphan Works.
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    Context-Based Entity Matching for Big Data
    (Cham : Springer, 2020) Tasnim, Mayesha; Collarana, Diego; Graux, Damien; Vidal, Maria-Esther; Janev, Valentina; Graux, Damien; Jabeen, Hajira; Sallinger, Emanuel
    In the Big Data era, where variety is the most dominant dimension, the RDF data model enables the creation and integration of actionable knowledge from heterogeneous data sources. However, the RDF data model allows for describing entities under various contexts, e.g., people can be described from its demographic context, but as well from their professional contexts. Context-aware description poses challenges during entity matching of RDF datasets—the match might not be valid in every context. To perform a contextually relevant entity matching, the specific context under which a data-driven task, e.g., data integration is performed, must be taken into account. However, existing approaches only consider inter-schema and properties mapping of different data sources and prevent users from selecting contexts and conditions during a data integration process. We devise COMET, an entity matching technique that relies on both the knowledge stated in RDF vocabularies and a context-based similarity metric to map contextually equivalent RDF graphs. COMET follows a two-fold approach to solve the problem of entity matching in RDF graphs in a context-aware manner. In the first step, COMET computes the similarity measures across RDF entities and resorts to the Formal Concept Analysis algorithm to map contextually equivalent RDF entities. Finally, COMET combines the results of the first step and executes a 1-1 perfect matching algorithm for matching RDF entities based on the combined scores. We empirically evaluate the performance of COMET on testbed from DBpedia. The experimental results suggest that COMET accurately matches equivalent RDF graphs in a context-dependent manner.
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    Building Scholarly Knowledge Bases with Crowdsourcing and Text Mining
    (Aachen : RWTH, 2020) Stocker, Markus; Zhang, Chengzhi; Mayr, Philipp; Lu, Wei; Zhang, Yi
    For centuries, scholarly knowledge has been buried in documents. While articles are great to convey the story of scientific work to peers, they make it hard for machines to process scholarly knowledge. The recent proliferation of the scholarly literature and the increasing inability of researchers to digest, reproduce, reuse its content are constant reminders that we urgently need a transformative digitalization of the scholarly literature. Building on the Open Research Knowledge Graph (http://orkg.org) as a concrete research infrastructure, in this talk we present how using crowdsourcing and text mining humans and machines can collaboratively build scholarly knowledge bases, i.e. systems that acquire, curate and publish data, information and knowledge published in the scholarly literature in structured and semantic form. We discuss some key challenges that human and technical infrastructures face as well as the possibilities scholarly knowledge bases enable.
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    International Conferences of Bibliometrics
    (München : De Gruyter Saur, 2021) Fraumann, Grischa; Mugnaino, Rogério; Sanz-Casado, Elías; Ball, Rafael
    Conferences are deeply connected to research fields, in this case bibliometrics. As such, they are a venue to present and discuss current and innovative research, and play an important role for the scholarly community. In this article, we provide an overview on the history of conferences in bibliometrics. We conduct an analysis to list the most prominent conferences that were announced in the newsletter by ISSI, the International Society for Scientometrics and Informetrics. Furthermore, we describe how conferences are connected to learned societies and journals. Finally, we provide an outlook on how conferences might change in future.
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    The ties that bind - On the impact of losing a consortium member in a cooperatively operated digital preservation system
    (2016) Lindlar, Michelle
    Cooperatively operated digital preservation systems offer institutions of varying size the chance to actively participate in digital preservation. In current times of budget cuts they are also a valuable asset to larger memory institutions. While the benefits of cooperatively operated systems have been discussed before, the risks associated with a consortial solution have not been analyzed in detail. TIB hosts the Goportis Digital Archive which is used by two large national subject libraries as well as by TIB itself. As the host of this comparatively small preservation network, TIB has started to analyze the particular risk which losing a consortium member poses to the overall system operation. This paper presents the current status of this work-in-progress and highlights two areas: risk factors associated with cost and risk factors associated with the content. While the paper is strictly written from the viewpoint of the consortial leader/ host of this specific network, the underlying processes shall be beneficial to other cooperatively operated digital preservation systems.
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    Overview of Chinese specialist literature in the field of Science and Technology in Germany
    (2015) Koch, Sarah
    The main target audience of the libraries special collections of East Asian literature is the scholars of humanities and social sciences, just like the sinological libraries are normally considered for the scholars of Chinese Studies. But in recent years one can notice a growing interest in East Asia, especially in China, in the field of science and technology. The increasing international economic relations between China and Germany are raising the demand for engineers who have a broad knowledge of China and the technical developments of both countries. In order to achieve an overview of the rapid technical and scientific developments in China, it is assumed that specialized language skills are required to be able to access important information. As the National Library for all areas of engineering and natural sciences, the German National Library of Science and Technology (TIB) takes the responsibility to provide research and industry with specialist literature and information – nationally and internationally. Therefore the TIB also built up the most comprehensive collection of modern Chinese literature in science and technology in Germany. As to understand how the library can provide a good support for the much more heterogeneous user group of Chinese literature in this field as well, it is necessary to learn more about their requirements. The purpose of this paper is to get an overview of the Chinese research output in science and technology by analyzing international databases, and to examine the target audience of this kind of literature. It is expected that it will not only show the growing awareness and use of Chinese technical and scientific publications by engineers in Germany, but also demonstrate the importance of access to these publications in terms of scholarly exchange for both German and Chinese scholars in Germany.
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    Estimating the information gap between textual and visual representations
    (New York City : Association for Computing Machinery, 2017) Henning, Christian; Ewerth, Ralph
    Photos, drawings, figures, etc. supplement textual information in various kinds of media, for example, in web news or scientific pub- lications. In this respect, the intended effect of an image can be quite different, e.g., providing additional information, focusing on certain details of surrounding text, or simply being a general il- lustration of a topic. As a consequence, the semantic correlation between information of different modalities can vary noticeably, too. Moreover, cross-modal interrelations are often hard to describe in a precise way. The variety of possible interrelations of textual and graphical information and the question, how they can be de- scribed and automatically estimated have not been addressed yet by previous work. In this paper, we present several contributions to close this gap. First, we introduce two measures to describe cross- modal interrelations: cross-modal mutual information (CMI) and semantic correlation (SC). Second, a novel approach relying on deep learning is suggested to estimate CMI and SC of textual and visual information. Third, three diverse datasets are leveraged to learn an appropriate deep neural network model for the demanding task. The system has been evaluated on a challenging test set and the experimental results demonstrate the feasibility of the approach.