Academic Journal
AgTC and AgETL: open-source tools to enhance data collection and management for plant science research.
| Τίτλος: | AgTC and AgETL: open-source tools to enhance data collection and management for plant science research. |
|---|---|
| Συγγραφείς: | Vargas-Rojas, Luis, To-Chia Ting, Rainey, Katherine M., Reynolds, Matthew, Wang, Diane R. |
| Πηγή: | Frontiers in Plant Science; 2024, p1-12, 12p |
| Θεματικοί όροι: | Botany, Data management, Collection & preservation of plant specimens, Acquisition of data, Management science, Data integration |
| Περίληψη: | Advancements in phenotyping technology have enabled plant science researchers to gather large volumes of information from their experiments, especially those that evaluate multiple genotypes. To fully leverage these complex and often heterogeneous data sets (i.e. those that differ in format and structure), scientists must invest considerable time in data processing, and data management has emerged as a considerable barrier for downstream application. Here, we propose a pipeline to enhance data collection, processing, and management from plant science studies comprising of two newly developed open-source programs. The first, called AgTC, is a series of programming functions that generates comma-separated values file templates to collect data in a standard format using either a lab-based computer or a mobile device. The second series of functions, AgETL, executes steps for an Extract-Transform-Load (ETL) data integration process where data are extracted from heterogeneously formatted files, transformed to meet standard criteria, and loaded into a database. There, data are stored and can be accessed for data analysis-related processes, including dynamic data visualization through webbased tools. Both AgTC and AgETL are flexible for application across plant science experiments without programming knowledge on the part of the domain scientist, and their functions are executed on Jupyter Notebook, a browser-based interactive development environment. Additionally, all parameters are easily customized from central configuration files written in the human-readable YAML format. Using three experiments from research laboratories in university and non-government organization (NGO) settings as test cases, we demonstrate the utility of AgTC and AgETL to streamline critical steps from data collection to analysis in the plant sciences. [ABSTRACT FROM AUTHOR] |
| Copyright of Frontiers in Plant Science is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: AgTC and AgETL: open-source tools to enhance data collection and management for plant science research. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Vargas-Rojas%2C+Luis%22">Vargas-Rojas, Luis</searchLink><br /><searchLink fieldCode="AR" term="%22To-Chia+Ting%22">To-Chia Ting</searchLink><br /><searchLink fieldCode="AR" term="%22Rainey%2C+Katherine+M%2E%22">Rainey, Katherine M.</searchLink><br /><searchLink fieldCode="AR" term="%22Reynolds%2C+Matthew%22">Reynolds, Matthew</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Diane+R%2E%22">Wang, Diane R.</searchLink> – Name: TitleSource Label: Source Group: Src Data: Frontiers in Plant Science; 2024, p1-12, 12p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Botany%22">Botany</searchLink><br /><searchLink fieldCode="DE" term="%22Data+management%22">Data management</searchLink><br /><searchLink fieldCode="DE" term="%22Collection+%26+preservation+of+plant+specimens%22">Collection & preservation of plant specimens</searchLink><br /><searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink><br /><searchLink fieldCode="DE" term="%22Management+science%22">Management science</searchLink><br /><searchLink fieldCode="DE" term="%22Data+integration%22">Data integration</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Advancements in phenotyping technology have enabled plant science researchers to gather large volumes of information from their experiments, especially those that evaluate multiple genotypes. To fully leverage these complex and often heterogeneous data sets (i.e. those that differ in format and structure), scientists must invest considerable time in data processing, and data management has emerged as a considerable barrier for downstream application. Here, we propose a pipeline to enhance data collection, processing, and management from plant science studies comprising of two newly developed open-source programs. The first, called AgTC, is a series of programming functions that generates comma-separated values file templates to collect data in a standard format using either a lab-based computer or a mobile device. The second series of functions, AgETL, executes steps for an Extract-Transform-Load (ETL) data integration process where data are extracted from heterogeneously formatted files, transformed to meet standard criteria, and loaded into a database. There, data are stored and can be accessed for data analysis-related processes, including dynamic data visualization through webbased tools. Both AgTC and AgETL are flexible for application across plant science experiments without programming knowledge on the part of the domain scientist, and their functions are executed on Jupyter Notebook, a browser-based interactive development environment. Additionally, all parameters are easily customized from central configuration files written in the human-readable YAML format. Using three experiments from research laboratories in university and non-government organization (NGO) settings as test cases, we demonstrate the utility of AgTC and AgETL to streamline critical steps from data collection to analysis in the plant sciences. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Frontiers in Plant Science is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3389/fpls.2024.1265073 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1 Subjects: – SubjectFull: Botany Type: general – SubjectFull: Data management Type: general – SubjectFull: Collection & preservation of plant specimens Type: general – SubjectFull: Acquisition of data Type: general – SubjectFull: Management science Type: general – SubjectFull: Data integration Type: general Titles: – TitleFull: AgTC and AgETL: open-source tools to enhance data collection and management for plant science research. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Vargas-Rojas, Luis – PersonEntity: Name: NameFull: To-Chia Ting – PersonEntity: Name: NameFull: Rainey, Katherine M. – PersonEntity: Name: NameFull: Reynolds, Matthew – PersonEntity: Name: NameFull: Wang, Diane R. IsPartOfRelationships: – BibEntity: Dates: – D: 05 M: 03 Text: 2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 1664462X Titles: – TitleFull: Frontiers in Plant Science Type: main |
| ResultId | 1 |