Science of Scientific Team Science: A survey

Yu, Shuo; Bedru, Hayat Dino; Lee, Ivan; Xia, Feng

doi:10.1016/j.cosrev.2018.12.001

Cited by 33 publications

(20 citation statements)

References 81 publications

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“…Tables 6a and 6b present the intra-and inter-program relationships of the graduate programs with two database updates. Considering the 2019 update and the inter-program relationships greater than ten, we note that there are 408 relationships between UFMG-UFAM, followed by UFMG-UnB (59), UFMG-UFRN (28), and UnB-UFRN (26). Thus, UFMG (level 7 by CAPES) presents a greater total of collaborations among the five Computer Science graduate programs indicating research leadership and good inter-program cooperation patterns.…”

Section: Rq3 What Are the Intra-and Inter-program Collaboration Patterns?mentioning

confidence: 92%

“…In previous works ( [22,23]), we present a collaboration network analysis as a management tool using publication data available in Lattes Platform from one Computer Science graduate program in Brazil, including a recommendation module for scientific partnerships. Besides, many international works are leading to interesting findings as in [24] that explores how collaboration in Computer Science evolved since 1960, measuring influences of scientist groups based on multiple types of collaboration [25], and a cross-disciplinary research work presenting a survey of scientific teamwork collaboration [26]. Nevertheless, there is a research gap concerning the Brazilian Computer Science graduate programs with intra-and inter-scientific collaboration analysis.…”

Section: Introductionmentioning

confidence: 99%

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Scientific Collaboration Network Analysis: A Brazilian Computer Science Graduate Programs Case

Costa¹,

Nunes²,

Ralha³

2021

Preprint

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Scientific collaboration networks can present different views of researchers’ interaction. The analysis of these networks allows research transparency focusing on the understanding of how science evolves in different contexts. In this article, we present a scientific collaboration network analysis using social network metrics as average degree, connected components, betweenness and closeness centralities applied to five Brazilian Computer Science graduate programs. An online artifact built upon the design science research paradigm, namely SCI-synergy, was developed to ease the analysis involving publication data available on the Digital Bibliography & Library Project (DBLP) from the graduate program members allied to the Federal University of Minas Gerais (UFMG), the State University of São Paulo (USP), the Federal University of Rio Grande do Norte (UFRN), the Federal University of Amazonas (UFAM), and the University of Brasília (UnB). The objective is to analyze the scientific collaboration network of each program focusing on the researchers’ collaboration to understand patterns considering intra- and inter-program relationships. The analysis covers two database updates of 2019 and 2021. Results show that intra-program relationships are not always bigger among the highest-ranked programs in CAPES. Nevertheless, UFMG presents a greater total of cooperation among the five programs indicating research leadership and good inter-program collaboration patterns. We advocate that the collaboration network analysis using an online artifact can be useful to understand patterns of all the Brazilian Computer Science graduate programs to discover new research perspectives to be improved, avoided or even applied to other contexts.

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Section: Rq3 What Are the Intra-and Inter-program Collaboration Patterns?mentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Scientific Collaboration Network Analysis: A Brazilian Computer Science Graduate Programs Case

Costa¹,

Nunes²,

Ralha³

2021

Preprint

View full text Add to dashboard Cite

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“…Second, as part of the same project, new approaches such as genomics are beginning to be used for a robust characterization of collections [53]. Currently, two critical crop collections, potato [62] and cacao [63], have been characterized and are available for the public. Soon, we expect to publish similar results for other native and underutilized crops such as avocado, Passiflora, and peach palm.…”

Section: Research Experience and Skills In The Disciplinementioning

confidence: 99%

Opportunities and Challenges to Improve a Public Research Program in Plant Breeding and Enhance Underutilized Plant Genetic Resources in the Tropics

Cerón‐Souza

Galeano

Tehelen³

et al. 2021

Genes

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The American tropics are hotspots of wild and domesticated plant biodiversity, which is still underutilized by breeding programs despite being conserved at regional gene banks. The improvement of those programs depends on long-term public funds and the maintenance of specialized staff. Unfortunately, financial ups and downs complicate staff connectivity and their research impact. Between 2000 and 2010, Agrosavia (Corporación Colombiana de Investigación Agropecuaria) dramatically decreased its public financial support. In 2017, we surveyed all 52 researchers from Agrosavia involved in plant breeding and plant genetic resource programs to examine the effect of decimating funds in the last ten years. We hypothesized that the staff dedicated to plant breeding still suffer a strong fragmentation and low connectivity. As we expected, the social network among researchers is weak. The top ten central leaders are predominantly males with an M.Sc. degree but have significant experience in the area. The staff has experience in 31 tropical crops, and 17 are on the list of underutilized species. Moreover, although 26 of these crops are in the national germplasm bank, this has not been the primary source for their breeding programs. We proposed five principles to improve connectivity among teams and research impact: (1) The promotion of internal discussion about gender gaps and generation shifts to design indicators to monitor and decrease this disparity over time. (2) The construction of long-term initiatives and synergies with the Colombian government to support the local production of food security crops independent of market trends. (3) Better collaboration between the National Plant Germplasm Bank and plant breeding researchers. (4) A concerted priority list of species (especially those neglected or underutilized) and external institutions to better focus the collaborative efforts in research using public funds. (5) Better spaces for the design of projects among researchers and training programs in new technologies. These principles could also apply in other tropical countries with public plant breeding research programs facing similar challenges.

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“…Research collaborations are one of primary features that affect performances of the research [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Interinstitutional Research Team Formation Based on Bibliographic Network Embedding

Lee

Hong

Kim

2021

Mobile Information Systems

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This study aims at forming research teams for interinstitutional collaborations. Research institutes have their own purposes and topics of interest. Thus, supporting joint research between multiple institutes, we have to consider not only synergies between scholars but also purposes of the institutes. To solve this problem, we propose a bibliographic network embedding method that can learn characteristics of institutes, not only of each scholar. First, we compose a bibliographic network that consists of scholars, publications, venues, research projects, and institutes. Collaboration styles and research topics of institutes and scholars are extracted by mining subgraphs from the bibliographic network. Then, vector representations of network nodes are learned based on occurrences of subgraphs on the nodes and neighborhoods of the nodes. Based on the vector representations, we train multilayer perceptrons (MLP) to assess collaboration probability between scholars affiliated in different institutes. For training the MLP, we suggest three strategies: (i) considering every collaboration, (ii) focusing on interinstitutional collaborations, and (iii) focusing on collaboration outcomes. To evaluate the proposed methods, we have analyzed research collaborations of POSTECH (Pohang University of Science and Technology) and RIST (Research Institute of Industrial Science and Technology) from 2011 to 2020. Then, we conducted the research team formation for joint research of the two institutes according to two purposes: pure research and commercialization research.

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Science of Scientific Team Science: A survey

Cited by 33 publications

References 81 publications

Scientific Collaboration Network Analysis: A Brazilian Computer Science Graduate Programs Case

Scientific Collaboration Network Analysis: A Brazilian Computer Science Graduate Programs Case

Opportunities and Challenges to Improve a Public Research Program in Plant Breeding and Enhance Underutilized Plant Genetic Resources in the Tropics

Interinstitutional Research Team Formation Based on Bibliographic Network Embedding

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