DatastoragecostsDMSPConsultationsDMSbudgetingDatasharingDatacuration“Goodenough”InstitutionalrepositoryNelsonMemoBudgetreductionInstitutionaldataretentionpolicy“Unfundedmandate”PublicaccessplansResearchsoftwareWho is goingto look at thedataanyway?“Understaffed”InstitutionaldatamanagementpolicyResearchcycleFAIRComplianceDatarepositoryAIBurdenSensitivedataReproducibilityDataethicsFunderrequirementsDatasecurityIRBPersistentidentifiers(PIDs)Asked to“do morewith less”Direct vs.indirectcostsCross-institutionworkinggroupHPCCAREDataservicesworkflowBigDataDatareuse“Itdepends”Long-termdatapreservationResearchdatalifecycle“Datascience”NIHPolicyPublicaccess toresearchdataDatastoragecostsDMSPConsultationsDMSbudgetingDatasharingDatacuration“Goodenough”InstitutionalrepositoryNelsonMemoBudgetreductionInstitutionaldataretentionpolicy“Unfundedmandate”PublicaccessplansResearchsoftwareWho is goingto look at thedataanyway?“Understaffed”InstitutionaldatamanagementpolicyResearchcycleFAIRComplianceDatarepositoryAIBurdenSensitivedataReproducibilityDataethicsFunderrequirementsDatasecurityIRBPersistentidentifiers(PIDs)Asked to“do morewith less”Direct vs.indirectcostsCross-institutionworkinggroupHPCCAREDataservicesworkflowBigDataDatareuse“Itdepends”Long-termdatapreservationResearchdatalifecycle“Datascience”NIHPolicyPublicaccess toresearchdata

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.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
  1. Data storage costs
  2. DMSP Consultations
  3. DMS budgeting
  4. Data sharing
  5. Data curation
  6. “Good enough”
  7. Institutional repository
  8. Nelson Memo
  9. Budget reduction
  10. Institutional data retention policy
  11. “Unfunded mandate”
  12. Public access plans
  13. Research software
  14. Who is going to look at the data anyway?
  15. “Understaffed”
  16. Institutional data management policy
  17. Research cycle
  18. FAIR
  19. Compliance
  20. Data repository
  21. AI
  22. Burden
  23. Sensitive data
  24. Reproducibility
  25. Data ethics
  26. Funder requirements
  27. Data security
  28. IRB
  29. Persistent identifiers (PIDs)
  30. Asked to “do more with less”
  31. Direct vs. indirect costs
  32. Cross-institution working group
  33. HPC
  34. CARE
  35. Data services workflow
  36. Big Data
  37. Data reuse
  38. “It depends”
  39. Long-term data preservation
  40. Research data lifecycle
  41. “Data science”
  42. NIH Policy
  43. Public access to research data