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Author: Vidal, Maria-Esther × End date: 2024 × Start date: 2020 × End date: 2024 × Start date: 2020 × Version: publishedVersion × Subject: Konferenzschrift ×

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Now showing 1 - 4 of 4
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    Optimizing Federated Queries Based on the Physical Design of a Data Lake
    (Aachen : RWTH, 2020) Rohde, Philipp D.; Vidal, Maria-Esther
    The optimization of query execution plans is known to be crucial for reducing the query execution time. In particular, query optimization has been studied thoroughly for relational databases over the past decades. Recently, the Resource Description Framework (RDF) became popular for publishing data on the Web. As a consequence, federations composed of different data models like RDF and relational databases evolved. One type of these federations are Semantic Data Lakes where every data source is kept in its original data model and semantically annotated with ontologies or controlled vocabularies. However, state-of-the-art query engines for federated query processing over Semantic Data Lakes often rely on optimization techniques tailored for RDF. In this paper, we present query optimization techniques guided by heuristics that take the physical design of a Data Lake into account. The heuristics are implemented on top of Ontario, a SPARQL query engine for Semantic Data Lakes. Using sourcespecific heuristics, the query engine is able to generate more efficient query execution plans by exploiting the knowledge about indexes and normalization in relational databases. We show that heuristics which take the physical design of the Data Lake into account are able to speed up query processing.
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    Digital Transformation of Education Credential Processes and Life Cycles – A Structured Overview on Main Challenges and Research Questions
    ([Wilmington, DE, USA] : IARIA, [2020], 2020) Keck, Ingo R.; Vidal, Maria-Esther; Heller, Lambert; Mikroyannidis, Alexander; Chang, Maiga; White, Stephen
    In this article, we look at the challenges that arise in the use and management of education credentials, and from the switch from analogue, paper-based education credentials to digital education credentials. We propose a general methodology to capture qualitative descriptions and measurable quantitative results that allow to estimate the effectiveness of a digital credential management system in solving these challenges. This methodology is applied to the EU H2020 project QualiChain use case, where five pilots have been selected to study a broad field of digital credential workflows and credential management. Copyright (c) IARIA, 2020
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    Falcon 2.0: An Entity and Relation Linking Tool over Wikidata
    (New York City, NY : Association for Computing Machinery, 2020) Sakor, Ahmad; Singh, Kuldeep; Patel, Anery; Vidal, Maria-Esther
    The Natural Language Processing (NLP) community has significantly contributed to the solutions for entity and relation recognition from a natural language text, and possibly linking them to proper matches in Knowledge Graphs (KGs). Considering Wikidata as the background KG, there are still limited tools to link knowledge within the text to Wikidata. In this paper, we present Falcon 2.0, the first joint entity and relation linking tool over Wikidata. It receives a short natural language text in the English language and outputs a ranked list of entities and relations annotated with the proper candidates in Wikidata. The candidates are represented by their Internationalized Resource Identifier (IRI) in Wikidata. Falcon 2.0 resorts to the English language model for the recognition task (e.g., N-Gram tiling and N-Gram splitting), and then an optimization approach for the linking task. We have empirically studied the performance of Falcon 2.0 on Wikidata and concluded that it outperforms all the existing baselines. Falcon 2.0 is open source and can be reused by the community; all the required instructions of Falcon 2.0 are well-documented at our GitHub repository (https://github.com/SDM-TIB/falcon2.0). We also demonstrate an online API, which can be run without any technical expertise. Falcon 2.0 and its background knowledge bases are available as resources at https://labs.tib.eu/falcon/falcon2/.
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    Preface of MEPDaW 2020: Managing the evolution and preservation of the data web
    (Aachen, Germany : RWTH Aachen, 2020) Orlandi, Fabrizio; Graux, Damien; Vidal, Maria-Esther; Fernández, Javier D.; Debattista, Jeremy; Orlandi, Fabrizio; Graux, Damien; Vidal, Maria-Esther; Fernández, Javier D.; Debattista, Jeremy
    The MEPDaW workshop series targets one of the emerging and fundamental problems of the Web, specifically the management and preservation of evolving knowledge graphs. During the past six years, the workshop series has been gathering a community of researchers and practitioners around these challenges. To date, the series has successfully published more than 30 articles allowing more than 50 individual authors to present and share their ideas. This 6th edition, virtually co-located with the International Semantic Web Conference (ISWC 2020), gathered the community around nine research publications and one invited keynote presentation. The event took place online on the 1st of November, 2020.