1. CHALLENGES 1

2. SPECIAL CASE: ARTS & HUMANITIES
Productivity

3. SPECIAL CASE: ARTS & HUMANITIES
Citations per paper

4. SPECIAL CASE: ARTS & HUMANITIES
Authors Per Paper,

5. SPECIAL CASE: “NEGATIVE” CITATIONS
Negative citations are a tiny proportion of the citation activities

6. SPECIAL CASE: “NEGATIVE” CITATIONS

7. SPECIAL CASE: SELF-CITATIONS
Should Self-citations be counted or removed?
Journals whose rank in category is significantly distorted by self-citation are removed from JCR for 2 years, then re-evaluated

8. SPECIAL CASE: MUTUAL CITATIONS

9. SPECIAL CASE: MUTUAL CITATIONS
Journal self-citations are concentrated in Journal Impact Factor years
High-value citation partners show extreme concentration

10. SPECIAL CASE: MUTUAL CITATIONS
490 Cited References

11. SPECIAL CASE: MULTI-AUTHORED PAPERS
ATLAS COLLABORATION is a group consisting of almost 3,000 authors

12. SPECIAL CASE: MULTI-AUTHORED PAPERS
Author A
Author B

13. AFILIATIONS DISAMBIGUATION VARIANTS
There are 80+ different institutional name variants unified under London School Economics & Political Science
6,000+ Unified organizations in WoS

14. AUTHOR DISAMBIGUATION
Common names can attract documents of multiple authors with the same name
2. Even if a name is unique enough, it might suffer from inaccuracies (e.g. typographical errors)
Disambiguation Problems

15. AUTHOR DISAMBIGUATION AUTHOR-AFFILIATION LINK

16. AUTHOR DISAMBIGUATION ORCID

17. AUTHOR DISAMBIGUATION WEB OF SCIENCE DISTINCT AUTHOR SETS
Records grouped together are likely written by the same person

18. AUTHOR DISAMBIGUATION AUTHOR PROFILES
Clean, disambiguated profiles at the Author/Department/Faculty level
Disambiguated profiles can be used to run accurate research performance reports at all organizational levels

19. Informed Use of Bibliometrics
Ten Rules in Using Publication and Citation Analysis 1.
Consider whether available data can address the question 2.
Choose publication types, field definitions, and years of data 3.
Decide on whole or fractional counting 4.
Judge whether data require editing to remove “artifacts” 5.
Compare like with like 6.
Use relative measures, not just absolute counts 7.
Obtain multiple measures 8.
Recognize the skewed nature of citation data 9.
Confirm that the data collected are relevant to the question
10.
Ask whether the results are reasonable
And, above all, present the results openly and honestly
David Pendlebury (2008): “Using Bibliometrics in Evaluating Research”