paper.bib

@article{dswPaper,
  author    = {Robert Pergl and
               Rob W. W. Hooft and
               Marek Such{\'{a}}nek and
               Vojtech Knaisl and
               Jan Slifka},
  title     = {"Data Stewardship Wizard": {A} Tool Bringing Together Researchers,
               Data Stewards, and Data Experts around Data Management Planning},
  journal   = {Data Science Journal},
  volume    = {18},
  pages     = {59},
  year      = {2019},
  doi       = {10.5334/dsj-2019-059}
}
@article{daisyPaper,
    author = {Becker, Regina and Alper, Pinar and Grouès, Valentin and Munoz, Sandrine and Jarosz, Yohan and Lebioda, Jacek and Rege, Kavita and Trefois, Christophe and Satagopam, Venkata and Schneider, Reinhard},
    title = {{DAISY: A Data Information System for accountability under the General Data Protection Regulation}},
    journal = {GigaScience},
    volume = {8},
    number = {12},
    year = {2019},
    month = {12},
    abstract = "{The new European legislation on data protection, namely, the General Data Protection Regulation (GDPR), has introduced comprehensive requirements for the documentation about the processing of personal data as well as informing the data subjects of its use. GDPR’s accountability principle requires institutions, projects, and data hubs to document their data processings and demonstrate compliance with the GDPR. In response to this requirement, we see the emergence of commercial data-mapping tools, and institutions creating GDPR data register with such tools. One shortcoming of this approach is the genericity of tools, and their process-based model not capturing the project-based, collaborative nature of data processing in biomedical research.We have developed a software tool to allow research institutions to comply with the GDPR accountability requirement and map the sometimes very complex data flows in biomedical research. By analysing the transparency and record-keeping obligations of each GDPR principle, we observe that our tool effectively meets the accountability requirement.The GDPR is bringing data protection to center stage in research data management, necessitating dedicated tools, personnel, and processes. Our tool, DAISY, is tailored specifically for biomedical research and can help institutions in tackling the documentation challenge brought about by the GDPR. DAISY is made available as a free and open source tool on Github. DAISY is actively being used at the Luxembourg Centre for Systems Biomedicine and the ELIXIR-Luxembourg data hub.}",
    issn = {2047-217X},
    doi = {10.1093/gigascience/giz140},
    url = {https://doi.org/10.1093/gigascience/giz140},
    eprint = {https://academic.oup.com/gigascience/article-pdf/8/12/giz140/31731268/giz140.pdf},
}