Design and Development of a Virtual Laboratory in Python for the Teaching of Data Analysis and Mathematics in Geology: Geopy

González-Nieto, Pilar López; Flechoso, M. Gomez; Mocoroa, M.A. Arribas; Martin, Alexander; Lorenzo, Mari Luz García; Gómez, Gabriel; Gómez, José Antonio Álvarez; Fraile, Andrea Caso; Dagan, J.M. Orosco; Palomares, Raúl Merinero; Lahoz-Beltrá, Rafael

doi:10.21125/inted.2020.0687

Cited by 5 publications

(2 citation statements)

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“…Data on global resurrection plant distribution was obtained via personal communication with Luiz Bondi. Coordinates for resurrection plant distributions were reverse mapped to identify their country of origin using the GeoPy package (Lopez Gonzalez-Nieto et al, 2020). After reverse mapping, we plotted the number of unique species in each country divided by the surface area (from the Natural Earth low resolution and tiny countries datasets) of that country to account for the species-area law.…”

Section: Methodsmentioning

confidence: 99%

Unifying the Research Landscape of Desiccation Tolerance to Identify Trends, Gaps, and Opportunities

Lotreck,

Ghassemi,

VanBuren

2024

Preprint

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Desiccation tolerance, or the ability to survive extreme dehydration, has evolved recurrently across the tree of life. While our understanding of the mechanisms underlying desiccation tolerance continues to expand, the compartmentalization of findings by study system impedes progress. Here, we analyzed 5,963 papers related to desiccation and examined model systems, research topics, citation networks, and disciplinary siloing over time. Our results show significant siloing, with plant science dominating the field, and relatively isolated clustering of plants, animal, microbial, and fungal literature. Topic modeling identified 46 distinct research topics, highlighting both commonalities and divergences across the knowledge of desiccation tolerance in different systems. We observed a rich diversity of model desiccation tolerant species within the community, contrasting the single species model for most biology research areas. To address citation gaps, we developed a rule-based algorithm to recommend new invitees to a niche conference, DesWorks, enhancing the integration of diverse research areas. The algorithm, which considers co-citation, co-authorship, research topics, and geographic data, successfully identified candidates with novel expertise that was unrepresented in previous conferences. Our findings underscore the importance of interdisciplinary collaboration in advancing desiccation tolerance research and provide a framework for using bibliometric tools to foster scientific integration.

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Section: Methodsmentioning

confidence: 99%

Unifying the Research Landscape of Desiccation Tolerance to Identify Trends, Gaps, and Opportunities

Lotreck,

Ghassemi,

VanBuren

2024

Preprint

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“…3 . 0 (Lopez Gonzalez-Nieto et al 2020). ABCal further uses the plotting functionality implemented in folium 0 .…”

Section: Methodsmentioning

confidence: 99%

ABCal: a Python package for Author Bias Computation and Scientometric Plotting for Reviews and Meta-Analyses

Le Clercq

2023

Preprint

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Systematic reviews are critical summaries of the exiting literature on a given subject and, when combined with meta-analysis, provides a quantitative synthesis of evidence to direct and inform future research. Such reviews must, however, account for complex sources of between study heterogeneity and possible sources of bias, such as publication bias. This paper presents the methods and results of a research study using a newly developed software tool called ABCal (version 1.0.2) to compute and assess author bias in the literature, providing a quantitative measure for the possible effect of overrepresented authors introducing bias to the overall interpretation of the literature. ABCal includes a new metric referred to as author bias, which is a measure of potential biases per paper when the frequency or proportions of contributions from specific authors are considered. The metric is able to account for a significant portion of the observed heterogeneity between studies included in meta-analyses. A meta-regression between observed effect measures and author bias values revealed that higher levels of author bias were associated with higher effect measures while lower author bias was evident for studies with lower effect measures. Furthermore, the software’s capabilities to analyse authorship contributions and produce scientometric plots was able to reveal distinct patterns in both the temporal and geographic distributions of publications, which may relate to any evident publication bias. Thus, ABCal can aid researchers in gaining a deeper understanding of the research landscape and assist in identifying both key contributors and holistic research trends.

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ABCal: a Python package for author bias computation and scientometric plotting for reviews and meta-analyses

Le Clercq

2023

Scientometrics

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Systematic reviews are critical summaries of the exiting literature on a given subject and, when combined with meta-analysis, provides a quantitative synthesis of evidence to direct and inform future research. Such reviews must, however, account for complex sources of between study heterogeneity and possible sources of bias, such as publication bias. This paper presents the methods and results of a research study using a newly developed software tool called ABCal (version 1.0.2) to compute and assess author bias in the literature, providing a quantitative measure for the possible effect of overrepresented authors introducing bias to the overall interpretation of the literature. ABCal includes a new metric referred to as author bias, which is a measure of potential biases per paper when the frequency or proportions of contributions from specific authors are considered. The metric is able to account for a significant portion of the observed heterogeneity between studies included in meta-analyses. A meta-regression between observed effect measures and author bias values revealed that higher levels of author bias were associated with higher effect measures while lower author bias was evident for studies with lower effect measures. Furthermore, the software's capabilities to analyse authorship contributions and produce scientometric plots was able to reveal distinct patterns in both the temporal and geographic distributions of publications, which may relate to any evident publication bias. Thus, ABCal can aid researchers in gaining a deeper understanding of the research landscape and assist in identifying both key contributors and holistic research trends.

show abstract

Design and Development of a Virtual Laboratory in Python for the Teaching of Data Analysis and Mathematics in Geology: Geopy

Cited by 5 publications

References 0 publications

Unifying the Research Landscape of Desiccation Tolerance to Identify Trends, Gaps, and Opportunities

Unifying the Research Landscape of Desiccation Tolerance to Identify Trends, Gaps, and Opportunities

ABCal: a Python package for Author Bias Computation and Scientometric Plotting for Reviews and Meta-Analyses

ABCal: a Python package for author bias computation and scientometric plotting for reviews and meta-analyses

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