NelsonMemoPersistentidentifiers(PIDs)DataethicsResearchsoftwareLong-termdatapreservationDatasecurityFAIR“Understaffed”ResearchdatalifecycleDMSPConsultationsCross-institutionworkinggroup“Itdepends”Publicaccess toresearchdata“Goodenough”BudgetreductionInstitutionalrepositoryDataservicesworkflowSensitivedataBigDataComplianceReproducibilityResearchcycleDMSbudgeting“Datascience”BurdenPublicaccessplansWho is goingto look at thedataanyway?HPCDatareuseInstitutionaldataretentionpolicyDatastoragecostsIRBNIHPolicyDirect vs.indirectcosts“Unfundedmandate”CAREInstitutionaldatamanagementpolicyFunderrequirementsDatacurationAIDatasharingAsked to“do morewith less”DatarepositoryNelsonMemoPersistentidentifiers(PIDs)DataethicsResearchsoftwareLong-termdatapreservationDatasecurityFAIR“Understaffed”ResearchdatalifecycleDMSPConsultationsCross-institutionworkinggroup“Itdepends”Publicaccess toresearchdata“Goodenough”BudgetreductionInstitutionalrepositoryDataservicesworkflowSensitivedataBigDataComplianceReproducibilityResearchcycleDMSbudgeting“Datascience”BurdenPublicaccessplansWho is goingto look at thedataanyway?HPCDatareuseInstitutionaldataretentionpolicyDatastoragecostsIRBNIHPolicyDirect vs.indirectcosts“Unfundedmandate”CAREInstitutionaldatamanagementpolicyFunderrequirementsDatacurationAIDatasharingAsked to“do morewith less”Datarepository

RADS 2 Kick Off Bingo! - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Nelson Memo
  2. Persistent identifiers (PIDs)
  3. Data ethics
  4. Research software
  5. Long-term data preservation
  6. Data security
  7. FAIR
  8. “Understaffed”
  9. Research data lifecycle
  10. DMSP Consultations
  11. Cross-institution working group
  12. “It depends”
  13. Public access to research data
  14. “Good enough”
  15. Budget reduction
  16. Institutional repository
  17. Data services workflow
  18. Sensitive data
  19. Big Data
  20. Compliance
  21. Reproducibility
  22. Research cycle
  23. DMS budgeting
  24. “Data science”
  25. Burden
  26. Public access plans
  27. Who is going to look at the data anyway?
  28. HPC
  29. Data reuse
  30. Institutional data retention policy
  31. Data storage costs
  32. IRB
  33. NIH Policy
  34. Direct vs. indirect costs
  35. “Unfunded mandate”
  36. CARE
  37. Institutional data management policy
  38. Funder requirements
  39. Data curation
  40. AI
  41. Data sharing
  42. Asked to “do more with less”
  43. Data repository