FunderrequirementsDatarepositoryComplianceIRBDatastoragecostsAsked to“do morewith less”NelsonMemoNIHPolicyBigDataDatasharingDatasecurityCross-institutionworkinggroup“Goodenough”ResearchcycleCAREBudgetreduction“Understaffed”SensitivedataDMSPConsultationsHPCInstitutionalrepositoryFAIRBurdenResearchsoftwareDatacurationDirect vs.indirectcostsPublicaccess toresearchdataReproducibilityDataservicesworkflowWho is goingto look at thedataanyway?ResearchdatalifecycleLong-termdatapreservationPublicaccessplansPersistentidentifiers(PIDs)DatareuseDMSbudgetingAIInstitutionaldataretentionpolicy“Unfundedmandate”Dataethics“Datascience”Institutionaldatamanagementpolicy“Itdepends”FunderrequirementsDatarepositoryComplianceIRBDatastoragecostsAsked to“do morewith less”NelsonMemoNIHPolicyBigDataDatasharingDatasecurityCross-institutionworkinggroup“Goodenough”ResearchcycleCAREBudgetreduction“Understaffed”SensitivedataDMSPConsultationsHPCInstitutionalrepositoryFAIRBurdenResearchsoftwareDatacurationDirect vs.indirectcostsPublicaccess toresearchdataReproducibilityDataservicesworkflowWho is goingto look at thedataanyway?ResearchdatalifecycleLong-termdatapreservationPublicaccessplansPersistentidentifiers(PIDs)DatareuseDMSbudgetingAIInstitutionaldataretentionpolicy“Unfundedmandate”Dataethics“Datascience”Institutionaldatamanagementpolicy“Itdepends”

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