1. Meta/Data As If Research Depends On It
Roy Tennant
#usetda2016
#usetda2016
Meta/Data As If Research Depends On It

2. Why Share Data?

3. Mandates

4. Facilitates data re-use

6. Brings more attention to the research it is based upon

8. Because it’s the right thing to do

9. Why Metadata?

10. The chained library of Hereford Cathedral 

12.
Photo by CC BY-NC-ND 2.0

13. Photo by U Mich Library https://www. flickr
Photo by U Mich Library CC BY 2.0

14. Photo by Karin Dalziel https://www. flickr
Photo by Karin Dalziel CC BY-NC 2.0

18. Data doesn’t describe itself
Guess what?
Data doesn’t describe itself
Not Even Close

20. Umm…what am I looking at?

21. Data Dictionary

22. Codebook

23. Survey Instrument

24. User Guide

25. HOW Metadata?

26. A Few Questions… What is it? Who collected it? How was it captured?
When?
What can I legally do with it?

27. …That Lead to Many More What are all of the data elements?
What do they mean? That is, how exactly were they collected?
Were the requirements of working with human subjects met?
Etc.

28. At Least Three Types
Descriptive — what is needed for discovery and selection
Technical and Structural — what is needed to describe technical aspects of the data, such as file format, and how the data is structured
Administrative — what is needed to manage or use the object (e.g., rights)

29. Using Which Standard?

30. How hard can this be?
Photo by CC BY-ND 2.0

31. 380 million records

33. Discovery Evaluation Identifiers 245 Title Statement
100 Personal Name
650 Subject
700 Personal Name
260 Publication Statement
300 Physical Description
Evaluation
500 Notes

35. This is incredibly difficult to get right

36. Standards alone don’t solve your problem

37. Basic Metadata Workflow
Authentication & Authorization
Capture
Validation
Reporting and Remediation
Protection & Backup

38. Basic Principles

39. Capture everything that you can

40. Whenever possible, validate it upon entry

41. Granularity is key for machine processing

42. Granularity Example
Gabriel Garcia Márquez <IndividualName> <FirstGiven>Gabriel</FirstGiven> <LastFamily>Garcia Márquez</LastFamily> </IndividualName> “Gabriel Garcia Márquez” or “Garcia Márquez, Gabriel”

43. Strive for consistency

45. Employ constant vigilance & use remediation techniques

47. UNT Metadata Quality Assurance Mechanisms & Tools…
2. Metadata Analysis Tools
NULL Values
List/Browse All Values (by each qualifiers and elements)
List Authorities Values
Graphical reports and other fun stuff
Clickable Maps by Institution and Collection
Word Clouds by elements
Records added overtime and other graphical reports
“Enhancing the Quality of Metadata: Modular Approach to Digital Resource Lifecycle Management“
University of North Texas

48. Recent research

49. …both disciplines wanted context about the data producer’s research methods and were able to get enough detail to be able to reuse the data…Archaeologists relied on bibliographies to facilitate data discovery, whereas quantitative social scientists used bibliographies to facilitate reuse decisions. Data reusers in both disciplines also relied on intermediaries. Quantitative social scientists, particularly novices, relied on faculty advisors…whereas archaeologists relied on colleagues and museum curators to locate data and associated context.

50. It’s unlikely that novice social science researchers (NSSRs) will require more metadata for data sets, but given that NSSRs relied on advice from faculty advisors, we should consider about how to enable this type of “human scaffolding”.

51. Curation of research data as part of the evolving scholarly record requires new skill sets, including deeper domain knowledge, data modeling, and ontology development. Libraries are investing more effort in becoming part of their faculty’s research process and offering services that help ensure that their research data will be accessible if not also preserved. Good metadata will help guide other researchers to the research data they need for their own projects—and the data creators will have the satisfaction of knowing that their data has benefitted others.
Karen
Smith-Yoshimura,
April 18, 2016

52. Concluding thoughts

53. Libraries are increasingly providing end-to-end research data services

55. The culture of sharing data is more advanced in some disciplines than others

58. It’s an employment growth sector

60. It remains unclear just how much, and in which disciplines, these data resources will be re-used

61. it’s the right thing to do
But…
it’s the right thing to do

62. Roy Tennant Senior Program Officer OCLC Research tennantr@oclc.org
@rtennant
facebook.com/roytennant