Bibliometrics as Big Data Science: Combination of Large Datasets and Research assessment Methodologies

Professors:Henk F. Moed

Full description

Course outline:  The course provides for a broad scientific-scholarly audience an introduction to the use of metrics in research assessment. It focuses on base notions and features rather than on technical details. It consists of three parts, each comprising three lectures of 45 minutes. Part 1 discusses the main trends in research assessment, and the challenges of current metrics development. It highlights the multi-dimensionality of research performance, the computerization of the research process, and the intricate relationship between metrics and peer review. Part 2 presents an overview of the field of metrics-based research assessment studies: its historical development, from scientometric studies based on Eugene Garfield’s Science Citation Index up until the notion of informetrics as a big data science; its main data sources, including so called altmetric sources obtained from the usage of publication archives and social media; its key analytical methodologies; and, last but not least, a series of illustrative applications. Two subjects are discussed in more detail in Part 3 of the course. The first is the use of metrics in the assessment of social sciences and humanities, revealing differences in communication and publication practices between its various subfields, comparing the degree to which their research output is covered by major databases, and highlighting the distinction between scholarly and cultural impact and merit. The second Caput Selectum analyzes the relationships between metrics and research funding. The Course ends with a discussion of the grand challenges of the development of metrics and their application in various types of research assessment processes.  The table below gives more detailed information on the topics covered in the lectures.


Tentative program

Part 1: Introduction; background; base notions.

1. Metrics in Research Assessment: An overview

2. Why research assessment; why metrics?

3. Research assessment methodologies

4. Types of metrics

Part 2: The classical approach

5. Citation indexes and citation-based indicators; data accuracy;

6. Assessment of journals and subject fields

7. Assessment of individual researchers, departments, institutions.

8. Assessment of national research systems

Part 3: New developments and conclusions

9. Electronic publishing; Access models; Social Media; Big data science

10. Altmetrics

11. Econometric models; research efficiency

12. The technological and societal impact of research

13. Metrics and peer review

14. Intended and unintended effects of research assessment processes

15. The multi-dimensional assessment of research



23 February 2015  AULA A2 (hour: 9-13) DIAG, via Ariosto, 25 Rome

24 February 2015 AULA A3 (hour: 14-17.30) DIAG, via Ariosto, 25 Rome

25 February 2015 AULA A4 (hour: 9-13) DIAG, via Ariosto, 25 Rome


4 May 2015 AULA A2 (hour: 9-13) DIAG, via Ariosto, 25 Rome

5 May 2015 AULA A3 (hour: 14-17.30) DIAG, via Ariosto, 25 Rome

6 May 2015 AULA A4 (hour: 9-13) DIAG, via Ariosto, 25 Rome