“Goodenough”NelsonMemoBudgetreductionBigDataAsked to“do morewith less”CAREDatarepositoryCross-institutionworkinggroupDirect vs.indirectcostsHPCLong-termdatapreservation“Datascience”DataservicesworkflowReproducibility“Understaffed”DMSbudgetingInstitutionalrepositoryDatacurationPersistentidentifiers(PIDs)“Unfundedmandate”DatareuseDatasharingInstitutionaldataretentionpolicyFAIRDataethicsResearchcycle“Itdepends”SensitivedataComplianceDatasecurityWho is goingto look at thedataanyway?FunderrequirementsResearchsoftwareDMSPConsultationsInstitutionaldatamanagementpolicyResearchdatalifecycleNIHPolicyDatastoragecostsIRBBurdenPublicaccessplansPublicaccess toresearchdataAI“Goodenough”NelsonMemoBudgetreductionBigDataAsked to“do morewith less”CAREDatarepositoryCross-institutionworkinggroupDirect vs.indirectcostsHPCLong-termdatapreservation“Datascience”DataservicesworkflowReproducibility“Understaffed”DMSbudgetingInstitutionalrepositoryDatacurationPersistentidentifiers(PIDs)“Unfundedmandate”DatareuseDatasharingInstitutionaldataretentionpolicyFAIRDataethicsResearchcycle“Itdepends”SensitivedataComplianceDatasecurityWho is goingto look at thedataanyway?FunderrequirementsResearchsoftwareDMSPConsultationsInstitutionaldatamanagementpolicyResearchdatalifecycleNIHPolicyDatastoragecostsIRBBurdenPublicaccessplansPublicaccess toresearchdataAI

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