Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

Data preservation 101

773 visualizaciones

Publicado el

10 simple steps towards effective preservation of research data

Publicado en: Ciencias
  • Sé el primero en comentar

  • Sé el primero en recomendar esto

Data preservation 101

  1. 1. Stephen Abrams University of California Curation Center Data Preservation 101
  2. 2. preservation is the means to an end … widespread data availability, sharing, and (re)use
  3. 3. good for science  reproducibility integrity  enables collaboration and synergy  minimizes needless duplication of effort © Universal Pictures
  4. 4. “Papers with publicly available microarray data received more citations than similar papers that did not make their data available, even after controlling for many variables known to influence citation rate” good for scientists  get credit for your work  higher impact factor
  5. 5. … and you have to (and should want to)  funders require it  journals require it  disciplinary best practice (increasingly) expects it “To do otherwise should come to be regarded as scientific malpractice” – Royal Society, 2014
  6. 6. what can I do? adopt the growing body of good practices 10 aspirational goals ►
  7. 7. plan ahead 10 implicit (non-)decisions can have significant consequences
  8. 8. plan ahead 10 a data management plan describes your intentions during and after your research project
  9. 9. prefer formats that are … standard customized open source proprietary commonly-used obscure self-describing opaque text binary 9 be preservation- friendly from the start
  10. 10. assign an identifier to your data 8 DOIs provide unambiguous reference, persistent access, and citation metrics [digital object identifier]
  11. 11. get an identifier for yourself 7 ORCIDs provide unambiguous reference and citation metrics [open researcher and contributor identifier]
  12. 12. describe and document what would you want to know about someone else’s data? who? what? when? where? how? why? …? 6
  13. 13. upload to a repository 5 professional, pro-active management replication fixity monitoring media refresh technology watch disaster recovery/ business continuity … replication fixity monitoring media refresh technology watch disaster recovery/ business continuity …
  14. 14. use a license with the most permissive terms 4 is best is okay custom data use agreement should be avoided
  15. 15. publish 3 so your data is available to collaborators, colleagues, and community
  16. 16. cite yourself and others 2 add data citations to your CV and publications track usage of your data products through alt-metrics
  17. 17. preserve your code 1 everything just said about data applies equally well to code
  18. 18. plan format identify (your data) identify (yourself) describe upload license publish cite code data preservation 101
  19. 19. for more information …
  20. 20. for more information … … also, a good paper to review: Goodman, Pepe, Blocker, Borgman, Cranmer et al. (2014) “Ten simple rules for the care and feeding of scientific data” PLOS Computational Biology 10(4):e1003452, doi:10.1371/journal.pcbi.1003542 … and ask your local librarian