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<rdf:RDF xmlns:community="http://www.bibsonomy.org/ontologies/2008/05/community#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:admin="http://webns.net/mvcb/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:swrc="http://swrc.ontoware.org/ontology#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xml:base="https://puma.ub.uni-stuttgart.de/group/researchcode/simulation%20metadata%20data"><owl:Ontology rdf:about=""><rdfs:comment>PUMA publications for /group/researchcode/simulation%20metadata%20data</rdfs:comment><owl:imports rdf:resource="http://swrc.ontoware.org/ontology/portal"/></owl:Ontology><rdf:Description rdf:about="https://puma.ub.uni-stuttgart.de/bibtex/224312a954079a07a4488cc88392ef995/diglezakis"><owl:sameAs rdf:resource="/uri/bibtex/224312a954079a07a4488cc88392ef995/diglezakis"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><owl:sameAs rdf:resource="https://link.springer.com/chapter/10.1007/978-3-319-67008-9_12"/><swrc:date>Fri Feb 16 09:39:19 CET 2018</swrc:date><swrc:booktitle>International Conference on Theory and Practice of Digital Libraries</swrc:booktitle><swrc:organization><swrc:Organization swrc:name="Springer"/></swrc:organization><swrc:pages>140--151</swrc:pages><swrc:title>Challenges of Research Data Management for High Performance Computing</swrc:title><swrc:year>2017</swrc:year><swrc:keywords>forschungsdaten metadata management data simulation obib hpc </swrc:keywords><swrc:abstract>This paper targets the challenges of research data management with a focus on High Performance Computing (HPC) and simulation data. Main challenges are discussed: The Big Data qualities of HPC research data, technical data management, organizational and administrative challenges. Emerging from these challenges, requirements for a feasible HPC research data management are derived and an alternative data life cycle is proposed. The requirement analysis includes recommendations which are based on a modified OAIS architecture: To meet the HPC requirements of a scalable system, metadata and data must not be stored together. Metadata keys are defined and organizational actions are recommended. Moreover, this paper contributes by introducing the role of a Scientific Data Manager, who is responsible for the institution’s data management and taking stewardship of the data.</swrc:abstract><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Bj{\&#034;o}rn Schembera"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Thomas B{\&#034;o}nisch"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description></rdf:RDF>