NelsonMemoWho is goingto look at thedataanyway?ResearchcycleNIHPolicyDatasecurityDatareuse“Goodenough”IRBDatastoragecostsFAIR“Unfundedmandate”PublicaccessplansInstitutionaldatamanagementpolicyHPCBigData“Understaffed”ReproducibilityDatacurationDatarepositoryCARECompliance“Itdepends”DataservicesworkflowPublicaccess toresearchdataInstitutionalrepositoryResearchdatalifecycleDatasharingLong-termdatapreservationSensitivedataBudgetreductionAIBurdenDMSPConsultationsPersistentidentifiers(PIDs)ResearchsoftwareDataethicsCross-institutionworkinggroupAsked to“do morewith less”DMSbudgetingInstitutionaldataretentionpolicyDirect vs.indirectcosts“Datascience”FunderrequirementsNelsonMemoWho is goingto look at thedataanyway?ResearchcycleNIHPolicyDatasecurityDatareuse“Goodenough”IRBDatastoragecostsFAIR“Unfundedmandate”PublicaccessplansInstitutionaldatamanagementpolicyHPCBigData“Understaffed”ReproducibilityDatacurationDatarepositoryCARECompliance“Itdepends”DataservicesworkflowPublicaccess toresearchdataInstitutionalrepositoryResearchdatalifecycleDatasharingLong-termdatapreservationSensitivedataBudgetreductionAIBurdenDMSPConsultationsPersistentidentifiers(PIDs)ResearchsoftwareDataethicsCross-institutionworkinggroupAsked to“do morewith less”DMSbudgetingInstitutionaldataretentionpolicyDirect vs.indirectcosts“Datascience”Funderrequirements

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