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Author: Strömert, Philip ×

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    AEON - Die Academic Event Ontology
    (Zenodo, 2021) Strömert, Philip
    Die Academic Event Ontology (AEON) ist eines der ersten Module einer zukünftigen erneuerten und modularisierten VIVO-Ontologie 2.0. Mit Hilfe von AEON sollen die relevanten Metadaten von wissenschaftlichen Veranstaltungen und Veranstaltungsreihen, inklusive der verschiedenen Rollen aller Beteiligten, maschinenlesbarer und besser teilbar werden. Die Entwicklung von AEON ist einerseits eine Antwort auf die Anforderung an moderne FIS-Systeme. Ebenso ist sie ein erster Schritt in die richtige Richtung, um bessere Aussagen über die Qualität wissenschaftlichen Veranstaltungen und Veranstaltungsreihen machen zu können. In diesem Vortrag wird ein Überblick über die Ontologie gegeben und es werden die noch bevorstehenden Herausforderungen aufgezeigt. Dabei werden sowohl die Wahl der BFO als "Upper Ontology" als auch die benötigten Anknüpfungspunkte zu anderen bestehenden OBO und sich noch in der Entwicklung befindenenden VIVO-Ontologie-Modulen kurz thematisiert.
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    ConfIDent: Enter the Feedback Loop
    (Meyrin : CERN, 2020-01-29) Strömert, Philip
    Slides from session at PIDapalooza2020, January 29th 2020, Lisbon, Portugal.
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    Conference Identifiers : the story so far and how to proceed
    (Meyrin : CERN, 2020-02-07) Franken, Julian; Strömert, Philip; Eckert, Kai; Benchekroun, Sami
    The Conference ID working group has a simple goal: identify conferences in a landscape of many similarly named organizations and constantly changing elements like organizers, names, publishers and so on. The idea is simple, the implementation not so much. In this session, we would like to introduce briefly the current state of the working group, as well as some current issues for the audience to be discussed. Issues include for example: Are use cases for conference identifiers missing? What identifiers to use? Who should manage the issuing of the identifiers? How do we promote the new identifiers?
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    Ontologies4Chem: The landscape of ontologies in chemistry
    (Berlin : de Gruyter, 2022) Strömert, Philip; Hunold, Johannes; Castro, André; Neumann, Steffen; Koepler, Oliver
    For a long time, databases such as CAS, Reaxys, PubChem or ChemSpider mostly rely on unique numerical identifiers or chemical structure identifiers like InChI, SMILES or others to link data across heterogeneous data sources. The retrospective processing of information and fragmented data from text publications to maintain these databases is a cumbersome process. Ontologies are a holistic approach to semantically describe data, information and knowledge of a domain. They provide terms, relations and logic to semantically annotate and link data building knowledge graphs. The application of standard taxonomies and vocabularies from the very beginning of data generation and along research workflows in electronic lab notebooks (ELNs), software tools, and their final publication in data repositories create FAIR data straightforwardly. Thus a proper semantic description of an investigation and the why, how, where, when, and by whom data was produced in conjunction with the description and representation of research data is a natural outcome in contrast to the retrospective processing of research publications as we know it. In this work we provide an overview of ontologies in chemistry suitable to represent concepts of research and research data. These ontologies are evaluated against several criteria derived from the FAIR data principles and their possible application in the digitisation of research data management workflows.