Dr. Tobias Weigel

Dr. Tobias Weigel


Application Support




Fuhlentwiete 10, 20355 Hamburg, Germany

Work area

Helmholtz AI (AIM)


Computer science, geoinformatics

Collaborative activities

  • Editorial Board member of CODATA Data Science Journal (2015-)
  • EOSC-pillar (2019-2020)
  • EOSC-hub (2018-2020)
  • EUDAT, EUDAT2020 (2012-2018)
  • Co-chair of multple RDA Working Groups on PIDs, data and metadata management (2013-2020)
  • Member of the Architecture WG of the European Open Science Coud, co-chair of the PID Task Force (2019-2020)
  • Member of the Technical Advisory Board of the Research Data Alliance (RDA) (2016-2019)

Selected publications

Also see my ORCID record (not necessarily complete).

Refereed journal articles:

  • Weigel, Schwardmann, Klump, Bendoukha, Quick: Making Data and Workflows Findable for Machines. Data Intelligence (2020). doi:10.1162/dint_a_00026
  • Jacobsen, et al.: FAIR Principles: Interpretations and Implementation Considerations. Data
    Intelligence (2019). doi:10.1162/dint_r_00024
  • Balaji, Taylor, Juckes, Lawrence, Durack, Lautenschlager, Blanton, Cinquini, Denvil, Elkington, Guglielmo, Guilyardi, Hassell, Kharin, Kindermann, Nikonov, Radhakrishnan, Stockhause, Weigel, Williams: Requirements for a global data infrastructure in support of CMIP6. Geoscientific Model Development (2018). doi:10.5194/gmd-11-3659-2018
  • Klump, Murphy, Weigel, Parsons: Editorial: 20 Years of Persistent Identifiers - Applications
    and Future Directions. Data Science Journal Special Collection (2017). doi:10.5334/dsj-
  • Data Science Journal, Special Collection on Persistent Identifiers; Klump, Murphy, Weigel, Parsons (eds). 2017.
  • Weigel, Kindermann, Lautenschlager: Actionable Persistent Identifier Collections. Data Science
    Journal, 2014. doi:10.2481/dsj.12-058
  • Weigel, Lautenschlager, Toussaint, Kindermann: A framework for extended persistent identification
    of scientific assets. Data Science Journal, 2013.


Technical reports and community standards:

  • Weigel, Plale, Parsons, Zhou, Luo, Schwardmann, Quick, Hellström, Kurakawa: RDA Recommendation on PID Kernel Information (Version 1). Research Data Alliance, 2018. doi:10.15497/RDA00031
  • Weigel, Almas, Baumgardt, Zastrow, Schwardmann, Hellström, Quinteros, Fleischer: Recommendation on Research Data Collections. Research Data Alliance, 2017. doi:10.15497/RDA00022
  • Weigel, DiLauro, Zastrow: PID Information Types WG final deliverable. Research Data Alliance, 2015. doi:1015497/FDAA09D5-5ED0-403D-B97A-2675E1EBE786