DatastoragecostsResearchdatalifecycleDatareuseFAIRReproducibilityDMSbudgetingSensitivedataAIHPC“Understaffed”Persistentidentifiers(PIDs)“Datascience”FunderrequirementsResearchsoftwareInstitutionaldataretentionpolicyBudgetreductionIRBNelsonMemoResearchcycleBurdenWho is goingto look at thedataanyway?“Unfundedmandate”“Goodenough”ComplianceDirect vs.indirectcostsLong-termdatapreservationCAREPublicaccess toresearchdataCross-institutionworkinggroupBigDataDatacurationPublicaccessplansDMSPConsultationsInstitutionalrepositoryDatasecurityDatasharingNIHPolicyDataservicesworkflowDataethicsAsked to“do morewith less”Datarepository“Itdepends”InstitutionaldatamanagementpolicyDatastoragecostsResearchdatalifecycleDatareuseFAIRReproducibilityDMSbudgetingSensitivedataAIHPC“Understaffed”Persistentidentifiers(PIDs)“Datascience”FunderrequirementsResearchsoftwareInstitutionaldataretentionpolicyBudgetreductionIRBNelsonMemoResearchcycleBurdenWho is goingto look at thedataanyway?“Unfundedmandate”“Goodenough”ComplianceDirect vs.indirectcostsLong-termdatapreservationCAREPublicaccess toresearchdataCross-institutionworkinggroupBigDataDatacurationPublicaccessplansDMSPConsultationsInstitutionalrepositoryDatasecurityDatasharingNIHPolicyDataservicesworkflowDataethicsAsked to“do morewith less”Datarepository“Itdepends”Institutionaldatamanagementpolicy

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