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Methodology capture: discriminating between the "best" and the rest of community practice

BACKGROUND: The methodologies we use both enable and help define our research. However, as experimental complexity has increased the choice of appropriate methodologies has become an increasingly difficult task. This makes it difficult to keep track of available bioinformatics software, let alone th...

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Autores principales: Eales, James M, Pinney, John W, Stevens, Robert D, Robertson, David L
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2553348/
https://www.ncbi.nlm.nih.gov/pubmed/18761740
http://dx.doi.org/10.1186/1471-2105-9-359
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author Eales, James M
Pinney, John W
Stevens, Robert D
Robertson, David L
author_facet Eales, James M
Pinney, John W
Stevens, Robert D
Robertson, David L
author_sort Eales, James M
collection PubMed
description BACKGROUND: The methodologies we use both enable and help define our research. However, as experimental complexity has increased the choice of appropriate methodologies has become an increasingly difficult task. This makes it difficult to keep track of available bioinformatics software, let alone the most suitable protocols in a specific research area. To remedy this we present an approach for capturing methodology from literature in order to identify and, thus, define best practice within a field. RESULTS: Our approach is to implement data extraction techniques on the full-text of scientific articles to obtain the set of experimental protocols used by an entire scientific discipline, molecular phylogenetics. Our methodology for identifying methodologies could in principle be applied to any scientific discipline, whether or not computer-based. We find a number of issues related to the nature of best practice, as opposed to community practice. We find that there is much heterogeneity in the use of molecular phylogenetic methods and software, some of which is related to poor specification of protocols. We also find that phylogenetic practice exhibits field-specific tendencies that have increased through time, despite the generic nature of the available software. We used the practice of highly published and widely collaborative researchers ("expert" researchers) to analyse the influence of authority on community practice. We find expert authors exhibit patterns of practice common to their field and therefore act as useful field-specific practice indicators. CONCLUSION: We have identified a structured community of phylogenetic researchers performing analyses that are customary in their own local community and significantly different from those in other areas. Best practice information can help to bridge such subtle differences by increasing communication of protocols to a wider audience. We propose that the practice of expert authors from the field of evolutionary biology is the closest to contemporary best practice in phylogenetic experimental design. Capturing best practice is, however, a complex task and should also acknowledge the differences between fields such as the specific context of the analysis.
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spelling pubmed-25533482008-09-26 Methodology capture: discriminating between the "best" and the rest of community practice Eales, James M Pinney, John W Stevens, Robert D Robertson, David L BMC Bioinformatics Research Article BACKGROUND: The methodologies we use both enable and help define our research. However, as experimental complexity has increased the choice of appropriate methodologies has become an increasingly difficult task. This makes it difficult to keep track of available bioinformatics software, let alone the most suitable protocols in a specific research area. To remedy this we present an approach for capturing methodology from literature in order to identify and, thus, define best practice within a field. RESULTS: Our approach is to implement data extraction techniques on the full-text of scientific articles to obtain the set of experimental protocols used by an entire scientific discipline, molecular phylogenetics. Our methodology for identifying methodologies could in principle be applied to any scientific discipline, whether or not computer-based. We find a number of issues related to the nature of best practice, as opposed to community practice. We find that there is much heterogeneity in the use of molecular phylogenetic methods and software, some of which is related to poor specification of protocols. We also find that phylogenetic practice exhibits field-specific tendencies that have increased through time, despite the generic nature of the available software. We used the practice of highly published and widely collaborative researchers ("expert" researchers) to analyse the influence of authority on community practice. We find expert authors exhibit patterns of practice common to their field and therefore act as useful field-specific practice indicators. CONCLUSION: We have identified a structured community of phylogenetic researchers performing analyses that are customary in their own local community and significantly different from those in other areas. Best practice information can help to bridge such subtle differences by increasing communication of protocols to a wider audience. We propose that the practice of expert authors from the field of evolutionary biology is the closest to contemporary best practice in phylogenetic experimental design. Capturing best practice is, however, a complex task and should also acknowledge the differences between fields such as the specific context of the analysis. BioMed Central 2008-09-01 /pmc/articles/PMC2553348/ /pubmed/18761740 http://dx.doi.org/10.1186/1471-2105-9-359 Text en Copyright © 2008 Eales et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Eales, James M
Pinney, John W
Stevens, Robert D
Robertson, David L
Methodology capture: discriminating between the "best" and the rest of community practice
title Methodology capture: discriminating between the "best" and the rest of community practice
title_full Methodology capture: discriminating between the "best" and the rest of community practice
title_fullStr Methodology capture: discriminating between the "best" and the rest of community practice
title_full_unstemmed Methodology capture: discriminating between the "best" and the rest of community practice
title_short Methodology capture: discriminating between the "best" and the rest of community practice
title_sort methodology capture: discriminating between the "best" and the rest of community practice
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2553348/
https://www.ncbi.nlm.nih.gov/pubmed/18761740
http://dx.doi.org/10.1186/1471-2105-9-359
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