DatarepositoryResearchsoftwareBigData“Datascience”Long-termdatapreservationDataservicesworkflowBudgetreductionDatareusePersistentidentifiers(PIDs)IRBSensitivedataInstitutionalrepositoryAsked to“do morewith less”DMSbudgetingCross-institutionworkinggroup“Itdepends”DMSPConsultations“Understaffed”CAREReproducibilityDatasharingHPCDirect vs.indirectcostsResearchdatalifecycleNelsonMemo“Unfundedmandate”NIHPolicyDatacurationPublicaccessplansResearchcycleComplianceInstitutionaldatamanagementpolicyWho is goingto look at thedataanyway?FAIRDatasecurityInstitutionaldataretentionpolicyPublicaccess toresearchdataAIDatastoragecostsFunderrequirements“Goodenough”BurdenDataethicsDatarepositoryResearchsoftwareBigData“Datascience”Long-termdatapreservationDataservicesworkflowBudgetreductionDatareusePersistentidentifiers(PIDs)IRBSensitivedataInstitutionalrepositoryAsked to“do morewith less”DMSbudgetingCross-institutionworkinggroup“Itdepends”DMSPConsultations“Understaffed”CAREReproducibilityDatasharingHPCDirect vs.indirectcostsResearchdatalifecycleNelsonMemo“Unfundedmandate”NIHPolicyDatacurationPublicaccessplansResearchcycleComplianceInstitutionaldatamanagementpolicyWho is goingto look at thedataanyway?FAIRDatasecurityInstitutionaldataretentionpolicyPublicaccess toresearchdataAIDatastoragecostsFunderrequirements“Goodenough”BurdenDataethics

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