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Neurotree: A Collaborative, Graphical Database of the Academic Genealogy of Neuroscience

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  • Stephen V David
  • Benjamin Y Hayden

Abstract

Neurotree is an online database that documents the lineage of academic mentorship in neuroscience. Modeled on the tree format typically used to describe biological genealogies, the Neurotree web site provides a concise summary of the intellectual history of neuroscience and relationships between individuals in the current neuroscience community. The contents of the database are entirely crowd-sourced: any internet user can add information about researchers and the connections between them. As of July 2012, Neurotree has collected information from 10,000 users about 35,000 researchers and 50,000 mentor relationships, and continues to grow. The present report serves to highlight the utility of Neurotree as a resource for academic research and to summarize some basic analysis of its data. The tree structure of the database permits a variety of graphical analyses. We find that the connectivity and graphical distance between researchers entered into Neurotree early has stabilized and thus appears to be mostly complete. The connectivity of more recent entries continues to mature. A ranking of researcher fecundity based on their mentorship reveals a sustained period of influential researchers from 1850–1950, with the most influential individuals active at the later end of that period. Finally, a clustering analysis reveals that some subfields of neuroscience are reflected in tightly interconnected mentor-trainee groups.

Suggested Citation

  • Stephen V David & Benjamin Y Hayden, 2012. "Neurotree: A Collaborative, Graphical Database of the Academic Genealogy of Neuroscience," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-12, October.
  • Handle: RePEc:plo:pone00:0046608
    DOI: 10.1371/journal.pone.0046608
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    Cited by:

    1. Dhananjay Kumar & Plaban Kumar Bhowmick & Sumana Dey & Debarshi Kumar Sanyal, 2023. "On the banks of Shodhganga: analysis of the academic genealogy graph of an Indian ETD repository," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 3879-3914, July.
    2. Carlos Eduardo M. Viegas Silva & Rubens Nunes & Elisabete Maria Macedo Viegas, 2018. "A genealogy of the Brazilian scientific research on freshwater fish farming by means of the academic supervision linkage," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1535-1553, December.
    3. Debarshi Kumar Sanyal & Sumana Dey & Partha Pratim Das, 2020. "gm-index: a new mentorship index for researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 71-102, April.
    4. Rossi, Luciano & Freire, Igor L. & Mena-Chalco, Jesús P., 2017. "Genealogical index: A metric to analyze advisor–advisee relationships," Journal of Informetrics, Elsevier, vol. 11(2), pages 564-582.
    5. Rossi, Luciano & Damaceno, Rafael J.P. & Freire, Igor L. & Bechara, Etelvino J.H. & Mena-Chalco, Jesús P., 2018. "Topological metrics in academic genealogy graphs," Journal of Informetrics, Elsevier, vol. 12(4), pages 1042-1058.
    6. Rafael J. P. Damaceno & Luciano Rossi & Rogério Mugnaini & Jesús P. Mena-Chalco, 2019. "The Brazilian academic genealogy: evidence of advisor–advisee relationships through quantitative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 303-333, April.
    7. Wuestman, Mignon & Wanzenböck, Iris & Frenken, Koen, 2023. "Local peer communities and future academic success of Ph.D. candidates," Research Policy, Elsevier, vol. 52(8).
    8. Julia H. Chariker & Yihang Zhang & John R. Pani & Eric C. Rouchka, 2017. "Identification of successful mentoring communities using network-based analysis of mentor–mentee relationships across Nobel laureates," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1733-1749, June.
    9. Dominik P. Heinisch & Guido Buenstorf, 2018. "The next generation (plus one): an analysis of doctoral students’ academic fecundity based on a novel approach to advisor identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 351-380, October.
    10. Lisa D. Wijsen & Denny Borsboom & Tiago Cabaço & Willem J. Heiser, 2019. "An Academic Genealogy of Psychometric Society Presidents," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 562-588, June.
    11. Kumar, Dhananjay & Bhowmick, Plaban Kumar & Paik, Jiaul H, 2023. "Researcher influence prediction (ResIP) using academic genealogy network," Journal of Informetrics, Elsevier, vol. 17(2).

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