PUMA publications for /group/researchcode/dataMon Feb 18 10:25:06 CET 2019LIBREAS. Library Ideas # 23: Forschungsdaten. Metadaten. Noch mehr Daten. Forschungsdatenmanagement106--130Forschungsdatenmanagement in DFG-SFBs2013forschungsdaten data policy sfb Mon Nov 19 08:40:13 CET 2018HT (Doctoral Consortium / Late-breaking Results / Workshops)conf/ht/2014dcCEUR Workshop ProceedingsStatistical Modeling by Gesture: A graphical, Browser-based Statistical Interface for Data Repositories.12102014forschungsdaten visualization data tools dataverse statistics Tue Jun 05 11:14:16 CEST 2018bioRxivA Data Citation Roadmap for Scholarly Data Repositories2017forschungsdaten citation data This article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles, a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Expert Group, as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE (https://biocaddie.org) program. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories.Fri Feb 16 09:39:19 CET 2018International Conference on Theory and Practice of Digital Libraries140--151Challenges of Research Data Management for High Performance Computing2017forschungsdaten metadata management data simulation obib hpc 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.