This document discusses analyzing data about research data and datasets to better understand their impact. It notes that impact goes beyond just citations and includes many types of engagement like views, saves, discussions, recommendations by different groups. More metrics from different sources need to be exposed about datasets to analyze diverse impacts. The data and metrics also need to be more open through text mining and aggregators. This will help drive more awareness of different types of research products and changes in how they are valued.

1. Analyzing
Data about our Data
Heather
Piwowar
@researchremix
cofounder,
ImpactStory.
Postdoc
at
NESCent.
some photos NC, SA
#RDS2013

2. We want to understand
the impact of our datasets

3. Something that we
data-people often forget:

4. IMPACT ISN’T JUST CITATIONS

5. Many types of engagement:
• views
• saves
• discussions
• formal references
• recommendations

6. Many engagement groups:
• researchers
• teachers
• students
• policy makers
• practitioners

7. journal article citation
formal reference
from a scholar

8. journal article in-text link
formal reference
from a scholar

9. blog in-text link
informal discussion
from a scholar

10. tweet in-text link
informal discussion
from a scholar
... or a teacher, student,
policy maker, ...

11. Mendeley,
delicious bookmark
save
by someone
for some reason :)

12. GitHub star
recommendation
by someone

13. http://www.flickr.com/photos/pixscapes/4331070047

14. Analyze
Data about our Data

15. Impact flavour
CC-BY-NC by maniacyak on flickr
http://www.flickr.com/photos/maniacyak/3432589472

16. How can we do this?
What is possible now?
What data exists, and how
can we analyze it?

17. Open metrics, with context, for diverse products.!
Board:
Cameron Neylon
John Wilbanks

21. Also:
Altmetric.com
Plum Analytics
Data Citation Index

22. 1. More data about our data

23. a) More metrics exposed

24. http://dx.doi.org/10.5061/dryad.18

25. http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/3131/utilization

26. http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/3131/utilization

27. http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/3131/utilization

28. b) More support for all
types of engagement

29. Today: full pallet for articles

30. Tools to support all stages
of web-native engagement
still lacking for datasets.
#callToAction

31. c) more derived metrics,
more context

35. 2) More open

36. http://www.flickr.com/photos/quinnanya/2055471833

37. OPEN text mining of articles
OPEN data from repos
OPEN metrics
from aggregators

38. 1. More data about our data
2. More open

39. 3. More awareness

42. http://datapub.cdlib.org/nsf-now-allows-data-in-biosketch-
accomplishments/
Piwowar H. (2013).Value all research products, Nature,
493 (7431) 159-159. DOI: 10.1038/493159a

43. Drive demand
Drive change

44. 1. More data about our data
2. More open
3. More awareness

45. http://www.flickr.com/photos/blmurch/722900022/

46. thank you!
Jason Priem: cofounder of ImpactStory
Also: Todd Vision, Mike Whitlock, the open science community, and
those who release their articles, datasets and photos openly.
blog.ImpactStory.org
team@ImpactStory.org
@ImpactStory
ImpactStory.org