1. Scientific and technical foundation for altmetrics in the US
William Gunn, Ph.D.
Head of Academic Outreach
Mendeley
@mrgunn
https://orcid.org/0000-0002-3555-2054

2. Why altmetrics?
http://www.stm-assoc.org/2009_10_13_MWC_STM_Report.pdf
•978 data repositories
•19 funder policies
•16 data journals New forms of scholarship need new metrics.

3. Problems with Impact Factor

4. Country
Documents
Citable documents
Citations
Self- Citations
Citations per Document
H index
United States
7,063,329
6,672,307
129,540,193
62,480,425
20.45
1,380
China
2,680,395
2,655,272
11,253,119
6,127,507
6.17
385
United Kingdom
1,918,650
1,763,766
31,393,290
7,513,112
18.29
851
Germany
1,782,920
1,704,566
25,848,738
6,852,785
16.16
740
Japan
1,776,473
1,734,289
20,347,377
6,073,934
12.11
635
France
1,283,370
1,229,376
17,870,597
4,151,730
15.6
681
Canada
993,461
946,493
15,696,168
3,050,504
18.5
658
Italy
959,688
909,701
12,719,572
2,976,533
15.26
588
Spain
759,811
715,452
8,688,942
2,212,008
13.89
476
India
750,777
716,232
4,528,302
1,585,248
7.99
301
Problems with Impact Factor

5. http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0030291
Problems with Impact Factor
During discussions with Thomson Scientific over which article types in PLoS Medicine the company deems as “citable,” it became clear that the process of determining a journal's impact factor is unscientific and arbitrary.”

6. The higher the impact factor, the more likely the research is to be retracted, partly due to intense competition.
http://bjoern.brembs.net/news766.html.11
What matters is who is reading your work!
There is no correlation between the number a citations an article receives and the impact factor of the journal. http://www.bmj.com/content/314/7079/497.1.full

7. Adams, Jonathan. "Collaborations: the fourth age of research." Nature 497.7451 (2013): 557-560.

8. King, Christopher (2012) Thomson Reuters Annual Report
http://ar.thomsonreuters.com/_files/pdf/MultiauthorPapers_ChrisKing.pdf

9. What are altmetrics?
Research impacts more than authors

10. http://dx.doi.org/10.3789/isqv25no2.2013.04

11. Citations are slow

12. Mendeley is fast

13. Professors on Mendeley tend to be in applied math, stats, and physics.
Graduate students on Mendeley tend to be in engineering disciplines.
http://dx.doi.org/10.6084/m9.figshare.1041819

14. Cell Biology and Neuroscience are highly active disciplines, relative to their output.
Social sciences are highly active relative to their citations/paper
http://dx.doi.org/10.6084/m9.figshare.1041819

16. Readership vs. citations
•it comes with a payload of metadata
•it accrues faster
•it illuminates previously hidden impact

17. http://arxiv.org/html/1203.4745v1
altmetrics show broader impact

18. http://www.asis.org/Bulletin/Apr-13/AprMay13_Lin_Fenner.html
altmetrics show broader impact

19. Consistency is key
http://www.niso.org/publications/isq/2013/v25no2/chamberlain/

20. Issues To Be Addressed
•Identity
•Privacy
•Attribution
•Gaming
•Filtration
standards/ best practice

21. NISO Altmetrics Standards
Alfred P. Sloan Foundation
American Library Association
California Institute of Technology
Center for Research Libraries
EBSCO
Elsevier
Harvard
Internet Archive
Wiley
Library and Information Technology Association
Library of Congress
Los Alamos National Laboratory
National Institutes of Health
National Library of Medicine
OCLC
Princeton
Columbia
Smithsonian
Stanford
…

22. NISO Altmetrics Standards
•Types of sources: Mendeley, Twitter, Views, Downloads, Facebook
•Quality of sources: collection, reporting, aggregation methods; provenance; availability
•Use cases: discovery and assessment (of people and objects)

23. Types of sources
Most altmetrics providers use the following:
•Page views or downloads
•Mendeley readers (articles only for now)
•Tweets
•FB events
•Comments
•Github

24. Quality of sources
Collection methods vary & counts are inconsistent. Further study is needed.
For reporting, transparency is key. Show raw data, not just a derived number.
Aggregation of raw data is generally done by the recipient (institution, funder, publisher, author, etc) according to their need, instead of using one central source.

25. Quality of sources
Understanding and open reporting of provenance is important for community buy-in and long term stability.
Raw data should be available under open license, via API, with identifiers.
Identifiers include DOI:object, ORCID:person, ISNI/Ringgold: institution
Ex. This person(ORCID), at this institution (ISNI), released this object (DOI).

26. Use cases
Two main use cases exist: Discovery and Evaluation
Because the data sources remain variable, discovery can be done now. Accuracy of numbers matters less in recommendation than in assessment. Precision important for both.

27. Next Steps
•NISO white paper will be in public comment period soon.
•Working Groups will be established to develop best practices and standards.
•Pending approval, NISO will issue recommended practice or published standard.
•NISO to develop training to implement and adopt any recommended standards.

28. Amgen: 47 of 53 “landmark” oncology publications could not be reproduced
Bayer: 43 of 67 oncology & cardiovascular projects were based on contradictory results
Dr. John Ioannidis: 432 publications purporting sex differences in hypertension, multiple sclerosis, or lung cancer. Only one data set was reproducible http://reproducibilityinitiative.org
There is no gold standard

29. www.mendeley.com
william.gunn@mendeley.com
@mrgunn
https://orcid.org/0000-0002-3555-2054

30. ...and aggregates research data in the cloud
Mendeley extracts research data…
Install Mendeley Desktop
Collecting rich signals from domain experts.

31. Home
Work
Mobile
Cloud Library

32. Shared Folder

33. Mendeley Research Catalog

34. Mendeley Research Catalog

35. Read papers + keep track of notes
470M documents

36. Taking some misery out of writing

37. Information Extraction

38. We are publishing this data to the LOD cloud
http://code-research.eu/

39. Defining readership
•Each document addition is a “read”
•stamped with metadata describing the context of the read event
•a read is like a citation, but faster and captures more