InstitutionaldatamanagementpolicyPersistentidentifiers(PIDs)Dataservicesworkflow“Unfundedmandate”ComplianceBurdenCAREDirect vs.indirectcostsDataethicsLong-termdatapreservationPublicaccess toresearchdataDatastoragecostsDMSbudgetingNIHPolicyDatasharingIRBSensitivedataBigDataAsked to“do morewith less”Reproducibility“Understaffed”NelsonMemoDatasecurityPublicaccessplansAIDMSPConsultationsResearchsoftwareHPCBudgetreduction“Datascience”Institutionalrepository“Itdepends”DatareuseWho is goingto look at thedataanyway?FAIRCross-institutionworkinggroupInstitutionaldataretentionpolicyResearchcycle“Goodenough”FunderrequirementsResearchdatalifecycleDatarepositoryDatacurationInstitutionaldatamanagementpolicyPersistentidentifiers(PIDs)Dataservicesworkflow“Unfundedmandate”ComplianceBurdenCAREDirect vs.indirectcostsDataethicsLong-termdatapreservationPublicaccess toresearchdataDatastoragecostsDMSbudgetingNIHPolicyDatasharingIRBSensitivedataBigDataAsked to“do morewith less”Reproducibility“Understaffed”NelsonMemoDatasecurityPublicaccessplansAIDMSPConsultationsResearchsoftwareHPCBudgetreduction“Datascience”Institutionalrepository“Itdepends”DatareuseWho is goingto look at thedataanyway?FAIRCross-institutionworkinggroupInstitutionaldataretentionpolicyResearchcycle“Goodenough”FunderrequirementsResearchdatalifecycleDatarepositoryDatacuration

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