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End date: 2022 × Start date: 2020 × End date: 2019 × Start date: 2010 × Has files: Yes × WGL Institute: TIB ×

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Now showing 1 - 10 of 14
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    EVENTSKG: A 5-Star Dataset of Top-Ranked Events in Eight Computer Science Communities
    (Berlin ; Heidelberg : Springer, 2019) Fathalla, Said; Lange, Christoph; Auer, Sören; Hitzler, Pascal; Fernández, Miriam; Janowicz, Krzysztof; Zaveri, Amrapali; Gray, Alasdair J.G.; Lopez, Vanessa; Haller, Armin; Hammar, Karl
    Metadata of scientific events has become increasingly available on the Web, albeit often as raw data in various formats, disregarding its semantics and interlinking relations. This leads to restricting the usability of this data for, e.g., subsequent analyses and reasoning. Therefore, there is a pressing need to represent this data in a semantic representation, i.e., Linked Data. We present the new release of the EVENTSKG dataset, comprising comprehensive semantic descriptions of scientific events of eight computer science communities. Currently, EVENTSKG is a 5-star dataset containing metadata of 73 top-ranked event series (almost 2,000 events) established over the last five decades. The new release is a Linked Open Dataset adhering to an updated version of the Scientific Events Ontology, a reference ontology for event metadata representation, leading to richer and cleaner data. To facilitate the maintenance of EVENTSKG and to ensure its sustainability, EVENTSKG is coupled with a Java API that enables users to add/update events metadata without going into the details of the representation of the dataset. We shed light on events characteristics by analyzing EVENTSKG data, which provides a flexible means for customization in order to better understand the characteristics of renowned CS events.
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    The Research Core Dataset (KDSF) in the Linked Data context
    (Amsterdam [u.a.] : Elsevier, 2019) Walther, Tatiana; Hauschke, Christian; Kasprzik, Anna; Sicilia, Miguel-Angel; Simons, Ed; Clements, Anna; de Castro, Pablo; Bergström, Johan
    This paper describes our efforts to implement the Research Core Dataset (“Kerndatensatz Forschung”; KDSF) as an ontology in VIVO. KDSF is used in VIVO to record the required metadata on incoming data and to produce reports as an output. While both processes need an elaborate adaptation of the KDSF specification, this paper focusses on the adaptation of the KDSF basic data model for recording data in VIVO. In this context, the VIVO and KDSF ontologies were compared with respect to domain, syntax, structure, and granularity in order to identify correspondences and mismatches. To produce an alignment, different matching approaches have been applied. Furthermore, we made necessary modifications and extensions on KDSF classes and properties.
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    Interaction Network Analysis Using Semantic Similarity Based on Translation Embeddings
    (Berlin ; Heidelberg : Springer, 2019) Manzoor Bajwa, Awais; Collarana, Diego; Vidal, Maria-Esther; Acosta, Maribel; Cudré-Mauroux, Philippe; Maleshkova, Maria; Pellegrini, Tassilo; Sack, Harald; Sure-Vetter, York
    Biomedical knowledge graphs such as STITCH, SIDER, and Drugbank provide the basis for the discovery of associations between biomedical entities, e.g., interactions between drugs and targets. Link prediction is a paramount task and represents a building block for supporting knowledge discovery. Although several approaches have been proposed for effectively predicting links, the role of semantics has not been studied in depth. In this work, we tackle the problem of discovering interactions between drugs and targets, and propose SimTransE, a machine learning-based approach that solves this problem effectively. SimTransE relies on translating embeddings to model drug-target interactions and values of similarity across them. Grounded on the vectorial representation of drug-target interactions, SimTransE is able to discover novel drug-target interactions. We empirically study SimTransE using state-of-the-art benchmarks and approaches. Experimental results suggest that SimTransE is competitive with the state of the art, representing, thus, an effective alternative for knowledge discovery in the biomedical domain.
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    Preface
    (Aachen, Germany : RWTH Aachen, 2019) Kaffee, Lucie-Aimee; Endris, Kemele M.; Vidal, Maria-Esther; Comerio, Marco; Sadeghi, Mersedeh; Chaves-Fraga; David, Colpaert Pieter; Kaffee, Lucie Aimée; Endris, Kemele M.; Vidal, María-Esther; Comerio, Marco; Sadeghi, Mersedeh; Chaves-Fraga, David; Colpaert, Pieter
    This volumne presents the proceedings of the 1st International Workshop on Approaches for Making Data Interoperable (AMAR 2019) and 1st International Workshop on Semantics for Transport (Sem4Tra) held in Karlsruhe, Germany, September 9, 2019, co-located with SEMANTiCS 2019. Interoperability of data is an important factor to make transportation data accessible, therefore we present the topics alongside each other in this proceedings.
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    Open Science und die Bibliothek – Aktionsfelder und Berufsbild
    (Graz : Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare, 2019) Blümel, Ina; Drees, Bastian; Hauschke, Christian; Heller, Lambert; Tullney, Marco
    Eine durch die Digitalisierung veränderte und auf Open Science ausgerichtete Wissenschaftspraxis benötigt angepasste Infrastrukturen und Services. Daraus ergeben sich verschiedene neue oder veränderte Aktionsfelder für wissenschaftliche Bibliotheken und Infrastruktureinrichtungen. Zu nennen sind zum Beispiel die nicht-textuellen Materialien wie Forschungsdaten, AV-Medien oder Software und die Umsetzung der FAIR-Prinzipien. Hinzu kommen neue Aufgaben im Bereich der Forschungsinformationen, zum Beispiel in der Unterstützung institutioneller Forschungsinformationssysteme, die Gestaltung von Open Access, die Unterstützung kollaborativen wissenschaftlichen Arbeitens sowie die Schaffung von offenen Infrastrukturen. In diesem Artikel werden diese Felder kurz vorgestellt und sich daraus abzeichnende Anforderungen an das bibliothekarische Berufsbild skizziert.
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    “When was this picture taken?” – Image date estimation in the wild
    (Berlin : Springer Verlag, 2017) Müller, E.; Springstein, M.; Ewerth, R.
    The problem of automatically estimating the creation date of photos has been addressed rarely in the past. In this paper, we introduce a novel dataset Date Estimation in the Wild for the task of predicting the acquisition year of images captured in the period from 1930 to 1999. In contrast to previous work, the dataset is neither restricted to color photography nor to specific visual concepts. The dataset consists of more than one million images crawled from Flickr and contains a large number of different motives. In addition, we propose two baseline approaches for regression and classification, respectively, relying on state-of-the-art deep convolutional neural networks. Experimental results demonstrate that these baselines are already superior to annotations of untrained humans.
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    Open is not enough
    (Basingstoke : Nature Publishing Group, 2018) Chen, Xiaoli; Dallmeier-Tiessen, Sünje; Dasler, Robin; Feger, Sebastian; Fokianos, Pamfilos; Gonzalez, Jose Benito; Hirvonsalo, Harri; Kousidis, Dinos; Lavasa, Artemis; Mele, Salvatore; Rodriguez, Diego Rodriguez; Šimko, Tibor; Smith, Tim; Trisovic, Ana; Trzcinska, Anna; Tsanaktsidis, Ioannis; Zimmermann, Markus; Cranmer, Kyle; Heinrich, Lukas; Watts, Gordon; Hildreth, Michael; Lloret Iglesias, Lara; Lassila-Perini, Kati; Neubert, Sebastian
    The solutions adopted by the high-energy physics community to foster reproducible research are examples of best practices that could be embraced more widely. This first experience suggests that reproducibility requires going beyond openness.
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    Survey vs Scraped Data: Comparing Time Series Properties of Web and Survey Vacancy Data
    (Berlin : Springer Nature, 2019) De Pedraza, P.; Visintin, S.; Tijdens, K.; Kismihók, G.
    This paper studies the relationship between a vacancy population obtained from web crawling and vacancies in the economy inferred by a National Statistics Office (NSO) using a traditional method. We compare the time series properties of samples obtained between 2007 and 2014 by Statistics Netherlands and by a web scraping company. We find that the web and NSO vacancy data present similar time series properties, suggesting that both time series are generated by the same underlying phenomenon: the real number of new vacancies in the economy. We conclude that, in our case study, web-sourced data are able to capture aggregate economic activity in the labor market.
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    Formalizing Gremlin pattern matching traversals in an integrated graph Algebra
    (Aachen, Germany : RWTH Aachen, 2019) Thakkar, Harsh; Auer, Sören; Vidal, Maria-Esther; Samavi, Reza; Consens, Mariano P.; Khatchadourian, Shahan; Nguyen, Vinh; Sheth, Amit; Giménez-García, José M.; Thakkar, Harsh
    Graph data management (also called NoSQL) has revealed beneficial characteristics in terms of flexibility and scalability by differ-ently balancing between query expressivity and schema flexibility. This peculiar advantage has resulted into an unforeseen race of developing new task-specific graph systems, query languages and data models, such as property graphs, key-value, wide column, resource description framework (RDF), etc. Present-day graph query languages are focused towards flex-ible graph pattern matching (aka sub-graph matching), whereas graph computing frameworks aim towards providing fast parallel (distributed) execution of instructions. The consequence of this rapid growth in the variety of graph-based data management systems has resulted in a lack of standardization. Gremlin, a graph traversal language, and machine provide a common platform for supporting any graph computing sys-tem (such as an OLTP graph database or OLAP graph processors). In this extended report, we present a formalization of graph pattern match-ing for Gremlin queries. We also study, discuss and consolidate various existing graph algebra operators into an integrated graph algebra.
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    Natural variability or anthropogenically-induced variation? Insights from 15 years of multidisciplinary observations at the arctic marine LTER site HAUSGARTEN
    (Amsterdam : Elsevier B.V., 2016) Soltwedel, T.; Bauerfeind, E.; Bergmann, M.; Bracher, A.; Budaeva, N.; Busch, K.; Cherkasheva, A.; Fahl, K.; Grzelak, K.; Hasemann, C.; Jacob, M.; Kraft, A.; Lalande, C.; Metfies, K.; Nöthig, E.-M.; Meyer, K.; Quéric, N.-V.; Schewe, I.; Włodarska-Kowalczuk, M.; Klages, M.
    Time-series studies of arctic marine ecosystems are rare. This is not surprising since polar regions are largely only accessible by means of expensive modern infrastructure and instrumentation. In 1999, the Alfred Wegener Institute, Helmholtz-Centre for Polar and Marine Research (AWI) established the LTER (Long-Term Ecological Research) observatory HAUSGARTEN crossing the Fram Strait at about 79°N. Multidisciplinary investigations covering all parts of the open-ocean ecosystem are carried out at a total of 21 permanent sampling sites in water depths ranging between 250 and 5500 m. From the outset, repeated sampling in the water column and at the deep seafloor during regular expeditions in summer months was complemented by continuous year-round sampling and sensing using autonomous instruments in anchored devices (i.e., moorings and free-falling systems). The central HAUSGARTEN station at 2500 m water depth in the eastern Fram Strait serves as an experimental area for unique biological in situ experiments at the seafloor, simulating various scenarios in changing environmental settings. Long-term ecological research at the HAUSGARTEN observatory revealed a number of interesting temporal trends in numerous biological variables from the pelagic system to the deep seafloor. Contrary to common intuition, the entire ecosystem responded exceptionally fast to environmental changes in the upper water column. Major variations were associated with a Warm-Water-Anomaly evident in surface waters in eastern parts of the Fram Strait between 2005 and 2008. However, even after 15 years of intense time-series work at HAUSGARTEN, we cannot yet predict with complete certainty whether these trends indicate lasting alterations due to anthropologically-induced global environmental changes of the system, or whether they reflect natural variability on multiyear time-scales, for example, in relation to decadal oscillatory atmospheric processes.