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- ZeitschriftenartikelMachine Learning Meets Databases(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Günnemann, StephanMachine Learning has become highly popular due to several success stories in data-driven applications. Prominent examples include object detection in images, speech recognition, and text translation. According to Gartner’s 2016 Hype Cycle for Emerging Technologies, Machine Learning is currently at its peak of inflated expectations, with several other application domains trying to exploit the use of Machine Learning technology. Since data-driven applications are a fundamental cornerstone of the database community as well, it becomes natural to ask how these fields relate to each other. In this article, we will therefore provide a brief introduction to the field of Machine Learning, we will discuss its interplay with other fields such as Data Mining and Databases, and we provide an overview of recent data management systems integrating Machine Learning functionality.
- ZeitschriftenartikelDissertationen(Datenbank-Spektrum: Vol. 17, No. 1, 2017)
- ZeitschriftenartikelSABIO-RK, von Daten in der Publikation zur Suchlösung für Spezialisten(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Müller, Wolfgang; Bittkowski, Meik; Golebiewski, Martin; Kania, Renate; Rey, Maja; Weidemann, Andreas; Wittig, UlrikeSABIO-RK ist eine Datenbank, in der Spezialisten aus der Systembiologie Daten aus biochemischen Publikationen suchen, finden, und in geeigneten Formaten extrahieren können. Der Artikel beschreibt, wie Kuratierung durch Experten, standardisierte Struktur, flexible Suche und einfacher Datenexport ineinandergreifen, um den Informationsbedarf der Nutzer zu befriedigen.
- ZeitschriftenartikelLIVIVO – the Vertical Search Engine for Life Sciences(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Müller, Bernd; Poley, Christoph; Pössel, Jana; Hagelstein, Alexandra; Gübitz, ThomasThe explosive growth of literature and data in the life sciences challenges researchers to keep track of current advancements in their disciplines. Novel approaches in the life science like the One Health paradigm require integrated methodologies in order to link and connect heterogeneous information from databases and literature resources. Current publications in the life sciences are increasingly characterized by the employment of trans-disciplinary methodologies comprising molecular and cell biology, genetics, genomic, epigenomic, transcriptional and proteomic high throughput technologies with data from humans, plants, and animals. The literature search engine LIVIVO empowers retrieval functionality by incorporating various literature resources from medicine, health, environment, agriculture and nutrition. LIVIVO is developed in-house by ZB MED – Information Centre for Life Sciences. It provides a user-friendly and usability-tested search interface with a corpus of 55 Million citations derived from 50 databases. Standardized application programming interfaces are available for data export and high throughput retrieval. The search functions allow for semantic retrieval with filtering options based on life science entities. The service oriented architecture of LIVIVO uses four different implementation layers to deliver search services. A Knowledge Environment is developed by ZB MED to deal with the heterogeneity of data as an integrative approach to model, store, and link semantic concepts within literature resources and databases. Future work will focus on the exploitation of life science ontologies and on the employment of NLP technologies in order to improve query expansion, filters in faceted search, and concept based relevancy rankings in LIVIVO.
- ZeitschriftenartikelEuropeana – a Search Engine for Digitised Cultural Heritage Material(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Petras, Vivien; Hill, Timothy; Stiller, Juliane; Gäde, MariaEuropeana is a large-scale search engine for digitised cultural heritage material. It aggregates metadata from various European institutions such as libraries, archives, museums and galleries. The heterogeneous data and the enormous scale (53 million objects in over 50 languages) pose specific challenges for search and exploration. In this paper, we address the different challenges and solutions for information access within Europeana including information needs, data enrichment, ranking and other search aspects for digital cultural heritage.
- ZeitschriftenartikelPerforming Entity Facts(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Beck, Julia; Büchner, Michael; Bartholmei, Stephan; Knepper, MarkoIn a theatre play, persons appear as playwright, director, actors, etc. The play may have several performances with changing casts while actors may contribute to other plays and the role of a contributor may vary. Persons and the character of their contribution are a major focus in the performing arts domain. In order to create a domain specific and comprehensive research portal, current indexing techniques are combined with linked data methods giving access to person related information. The Specialised Information Service Performing Arts aggregates numerous metadata sources documenting the holdings of German-speaking cultural heritage institutions. This information source is extended by links to the recently established service Entity Facts by the German National Library that provides details to the persons related to the metadata records. The portal is based on the VuFind framework with index files that cover the metadata of all data providers and the cached data of all related authority records from Entity Facts. In order to achieve this, the standard model of VuFind MARC21 has been replaced by the Europeana model EDM. This allows for modeling all data – metadata and authority data – following linked data principles. While the respective mappings could be re-used new record drivers and indexing rules had to be defined.
- ZeitschriftenartikelDas Fachgebiet „Informationssysteme“ am Hasso-Plattner-Institut(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Naumann, Felix; Krestel, RalfDas Hasso-Plattner-Institut (HPI) ist ein privat finanziertes Institut an der Universität Potsdam. Stifter ist Professor Hasso Plattner, Mitgründer und Aufsichtsratsvorsitzender des Software-Konzerns SAP. Das Fachgebiet Informationssysteme, das von Prof. Dr. Felix Naumann geleitet wird, beschäftigt sich mit dem effizienten und effektiven Umgang mit heterogenen Daten und Texten. Gegründet wurde das Fachgebiet 2006 und bietet derzeit 12 Doktoranden und circa 15 Masterstudenten eine Forschungsumgebung.
- ZeitschriftenartikelPubPsych: A Powerful Research Tool Providing Access to a Broad Supranational Body of Psychological Knowledge(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Weichselgartner, Erich; Baier, Christiane; Ramthun, RolandIn the scientific domain, millions of research papers in many different languages are published throughout the globe every year. This causes not only information overload, but because of the language barrier, researchers might not understand or even find articles that could be relevant for their work. Therefore, in the field of psychology, the Leibniz Institute for Psychology Information (ZPID) and its partners have created PubPsych (https://www.pubpsych.eu/), an open access vertical search engine for psychological literature, tests, treatment programs and research data (metadata, not the content itself). We discuss the motivation for creating the system, design decisions, connected problems and our solutions, especially concerning multilingual information.
- ZeitschriftenartikelNews(Datenbank-Spektrum: Vol. 17, No. 1, 2017)
- ZeitschriftenartikelBASE (Bielefeld Academic Search Engine)(Datenbank-Spektrum: Vol. 17, No. 1, 2017) Bäcker, Amelie; Pietsch, Christian; Summann, Friedrich; Wolf, SebastianWissenschaftliche Publikationen und ihre beschreibenden Metadaten stehen in stetig zunehmender Anzahl über Plattformen für elektronische Zeitschriften oder digitale Repositorien frei über das Internet zur Verfügung und lassen sich nachnutzen. Die Metadaten können über OAI-PMH (Open Archives Initiative Protocol for Metadata Harvesting) abgerufen werden (Harvesting). Durch Weiterverarbeitung und Indexierung der Metadaten lassen sich Services wie die „Bielefeld Academic Search Engine“ (BASE) entwickeln.Dieser Artikel beschreibt die praktischen Erfahrungen, die seit über 10 Jahren im Rahmen des Betriebs von BASE an der Universitätsbibliothek Bielefeld gewonnen wurden. BASE sammelt Millionen von Metadatensätzen aus Tausenden von Quellen weltweit. Die Metadaten werden während des Indexierungsprozesses teilweise korrigiert, normalisiert und um weitere Informationen angereichert. BASE sammelt zudem Metadaten zu den indexierten Quellen, die ebenfalls für Retrieval und Anzeige verwendet werden.Eine Übersicht der Services vergleichbarer Suchdienste zeigt auf, welche Unterschiede und Gemeinsamkeiten es zwischen BASE und anderen wissenschaftlichen Suchdiensten gibt.BASE wird auf vielfältige Weise verwendet, und die enthaltenen Daten werden über Schnittstellen nachgenutzt. Neue Herausforderungen ergeben sich insbesondere aus der Erweiterung des Umfangs der Metadaten und ihrer Bereitstellung mithilfe detaillierterer Datenformate jenseits von Dublin Core. Durch die Anreicherung der Metadaten um Informationen wie Personenattribute (IDs, Affiliationen), Förderorganisationen und verknüpfte Forschungsdaten entsteht die Notwendigkeit, das Datenschema für die Indexierung in geeigneter Weise zu erweitern.