CAREResearchdatalifecycleNIHPolicyDataethicsBigDataWho is goingto look at thedataanyway?Asked to“do morewith less”SensitivedataFAIR“Datascience”ComplianceDMSbudgetingDatasharingReproducibilityHPCFunderrequirements“Goodenough”DMSPConsultationsDatareuseDatarepositoryInstitutionaldataretentionpolicyDataservicesworkflowDatasecurityDirect vs.indirectcostsPublicaccessplansResearchsoftwareLong-termdatapreservationPublicaccess toresearchdataBudgetreductionNelsonMemoDatacuration“Understaffed”DatastoragecostsBurdenAIIRB“Itdepends”InstitutionalrepositoryCross-institutionworkinggroupPersistentidentifiers(PIDs)InstitutionaldatamanagementpolicyResearchcycle“Unfundedmandate”CAREResearchdatalifecycleNIHPolicyDataethicsBigDataWho is goingto look at thedataanyway?Asked to“do morewith less”SensitivedataFAIR“Datascience”ComplianceDMSbudgetingDatasharingReproducibilityHPCFunderrequirements“Goodenough”DMSPConsultationsDatareuseDatarepositoryInstitutionaldataretentionpolicyDataservicesworkflowDatasecurityDirect vs.indirectcostsPublicaccessplansResearchsoftwareLong-termdatapreservationPublicaccess toresearchdataBudgetreductionNelsonMemoDatacuration“Understaffed”DatastoragecostsBurdenAIIRB“Itdepends”InstitutionalrepositoryCross-institutionworkinggroupPersistentidentifiers(PIDs)InstitutionaldatamanagementpolicyResearchcycle“Unfundedmandate”

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