InstitutionalrepositoryPublicaccess toresearchdataComplianceDatasecurityPersistentidentifiers(PIDs)BigDataWho is goingto look at thedataanyway?DMSbudgetingNIHPolicyDatasharingInstitutionaldatamanagementpolicy“Datascience”NelsonMemoDatastoragecostsAI“Unfundedmandate”Long-termdatapreservationPublicaccessplansInstitutionaldataretentionpolicyReproducibilityFunderrequirementsSensitivedataDirect vs.indirectcostsHPCIRBCross-institutionworkinggroupResearchcycle“Itdepends”ResearchdatalifecycleAsked to“do morewith less”DataservicesworkflowDMSPConsultationsFAIR“Goodenough”“Understaffed”ResearchsoftwareDatarepositoryDataethicsBudgetreductionDatacurationBurdenCAREDatareuseInstitutionalrepositoryPublicaccess toresearchdataComplianceDatasecurityPersistentidentifiers(PIDs)BigDataWho is goingto look at thedataanyway?DMSbudgetingNIHPolicyDatasharingInstitutionaldatamanagementpolicy“Datascience”NelsonMemoDatastoragecostsAI“Unfundedmandate”Long-termdatapreservationPublicaccessplansInstitutionaldataretentionpolicyReproducibilityFunderrequirementsSensitivedataDirect vs.indirectcostsHPCIRBCross-institutionworkinggroupResearchcycle“Itdepends”ResearchdatalifecycleAsked to“do morewith less”DataservicesworkflowDMSPConsultationsFAIR“Goodenough”“Understaffed”ResearchsoftwareDatarepositoryDataethicsBudgetreductionDatacurationBurdenCAREDatareuse

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