SensitivedataDatastoragecostsLong-termdatapreservationDMSPConsultations“Understaffed”Cross-institutionworkinggroupDatarepositoryInstitutionaldataretentionpolicyComplianceNelsonMemo“Unfundedmandate”IRBDatareuseInstitutionaldatamanagementpolicyFunderrequirementsBurdenInstitutionalrepositoryDatasecurityDataservicesworkflowHPCNIHPolicyDatasharing“Datascience”FAIR“Goodenough”Direct vs.indirectcostsPersistentidentifiers(PIDs)Asked to“do morewith less”ResearchdatalifecycleDataethicsBudgetreductionDMSbudgetingResearchsoftwareDatacurationCAREPublicaccessplansResearchcycleWho is goingto look at thedataanyway?“Itdepends”BigDataAIReproducibilityPublicaccess toresearchdataSensitivedataDatastoragecostsLong-termdatapreservationDMSPConsultations“Understaffed”Cross-institutionworkinggroupDatarepositoryInstitutionaldataretentionpolicyComplianceNelsonMemo“Unfundedmandate”IRBDatareuseInstitutionaldatamanagementpolicyFunderrequirementsBurdenInstitutionalrepositoryDatasecurityDataservicesworkflowHPCNIHPolicyDatasharing“Datascience”FAIR“Goodenough”Direct vs.indirectcostsPersistentidentifiers(PIDs)Asked to“do morewith less”ResearchdatalifecycleDataethicsBudgetreductionDMSbudgetingResearchsoftwareDatacurationCAREPublicaccessplansResearchcycleWho is goingto look at thedataanyway?“Itdepends”BigDataAIReproducibilityPublicaccess toresearchdata

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