Presentation at Drexel MRC Assessing Researchers’ Collaborative Quality Kedma Duarte Federal...

Presentation at Drexel MRC

Assessing Researchers’ Collaborative Quality

Kedma DuarteFederal University of Santa Catarina, Brazil

Doctoral Degree

December 2, 2015


Contents

1. Motivation

2. Research questions

3. Methodology

4. Intended contribution


Introducing myself Goiania, Goiás- Education

• Undergraduate in Computer Science • Master in Computer Engineering

- Professional background• University of Goiás State - Information System Program

• Goiás Research Foundation (Fapeg) - Information Technology Manager ** My fist experience with research collaborations

Florianopolis, Santa Catarina• Doctoral degree in Knowledge Engineering, at Federal University of Santa Catarina (UFSC)

Brasilia, DF

Goiás

Santa Catarina


1. Motivation

Goias Research Foundation – www.fapeg.go.gov.br

• I was the funding director of a program for collaboration between

researchers.

• The main question that my boss always asked me:

• “How can we assess the quality of research collaborators?”

http://www.fapeg.go.gov.br/


1. Motivation

When I was selected for the doctoral degree, my proposal

was to study research collaborators.

Literature review

• There is a vast literature on research collaboration

• However, there is not scientific basis to compute quality

of research collaborators.


2. Research question

• How to assess the collaborative quality of research

collaborators?

• RQ1: What are the attributes that distinguish quality in

research collaborators?

• …..


RQ1 – What are the attributes that distinguish quality in research collaborators?

CONTEXT OF RESEARCH

COLLABORATORS

CAREER

RESEARCH COLLABORATORS ARE RESEARCHERS

RESEARCH COLLABORATORS AREAFFILIATED TO INSTITUTIONS RESEARCH COLLABORATORS

ACHIEVE ACCOMPLISHMENTS

ACCOMPLISHMENTSINSTITUTIONS

RESEARCHER


3. Methodology

1. Literature review

• The attributes of research collaborators

2. Machine Learning

• The predictive attributes of research collaborators

3. Database

• Brazilian Lattes database


http://lattes.cnpq.br/

CNPq - National council for the development of science and technology, is part of the Brazilian Ministry of Science, Technology and Innovation (MCTI).

Lattes database has about 3.5 million curricula, individually registered by students, professors, researchers, and practitioners from all research areas and institutions in Brazil.

Pacheco, 2015

http://lattes.cnpq.br/


“The Brazilian experience with the Lattes Database is a powerful example of good practice. This provides high-quality data on about 1.6 million researchers and about 4,000 institutions. (…) - The result is one of the cleanest researcher databases in existence.“

Nature 25/03/2010

http://www.nature.com/nature/journal/v464/n7288/full/464488a.html

Pacheco, 2015

http://www.nature.com/nature/journal/v464/n7288/full/464488a.html


http://lattes.cnpq.br/2693759912446687

CV Lattes - Example

Dr. Roberto Pacheco has led the conception, development, and deployment of, among others, the Lattes Platform

Pacheco, 2015




4. Intended contribution

• For funding agencies measure collaborative quality

• Rankings and metrics could be used for purposes such as:

• Selection of collaborators with better chances of success by funding agencies;

• Identification of guidance to mentor junior researchers to become better collaborators.


Next steps

We are writing another article, whose goal is to identify what

attributes are predictive of quality, applying machine

learning to the Lattes database.


Bibliography Adams, J. (2013). Collaborations: the fourth age of research. Nature, 497(7451), 557–560. doi:10.1038/497557a

Atkins, D. E., Droegemeier, K. K., Feldman, S. I., Garcia-molina, H., Klein, M. L., Messerschmitt, D. G., et al. (2003). Revolutionizing Science and Engineering Through Cyberinfrastructure: Report of the National Science Foundation Blue-Ribbon Advisory Panel on Cyberinfrastructure (Vol. 81).

Beaver, D. deB., & Rosen, R. (1978). Studies in scientific collaboration: Part I. The Professional Origins of Scientific Co-Authorship. Scientometrics, 1(1), 65–84. doi:10.1007/BF02016840

Bozeman, B., Fay, D., & Slade, C. P. (2013). Research collaboration in universities and academic entrepreneurship: The-state-of-the-art. Journal of Technology Transfer, 38(1), 1–67. doi:10.1007/s10961-012-9281-8

Cañibano, C., & Bozeman, B. (2009). Curriculum vitae method in science policy and research evaluation: the state-of-the-art. Research Evaluation, 18(2), 86–94. doi:10.3152/095820209X441754

Dietz, J. S., Chompalov, I., Bozeman, B., Lane, E. O., & Park, J. (2000). Using the CV to study the career path of scientists and engineers. Scientometrics, 49, 419–442.

Klein, J. T. (2008). Evaluation of Interdisciplinary and Transdisciplinary Research, 35, 116–123. doi:10.1016/j.amepre.2008.05.010

Lane, J. (2010). Let’s make science metrics more scientific. Nature, 464(7288), 488–9. doi:10.1038/464488a

Pacheco, R.C.S. (2015). 4Cs Interdisciplinares: Conhecimento, Casos, Coprodução, Commons. IV Workshop interdisciplinar de investigacion e indicadores de sustentabilidad (WIPIS 2015). Universidade de Concepcion, Chile. Apr, 2015.

Yagi, E., Badash, L., & De Beaver, D. B. (1996). Derek J. de S. Price (1922-83): Historian of science and herald of scientometrics. Interdisciplinary Science Reviews, 21(1), 64–76.


Kedma Batista [email protected]

Thank you!

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