Corrigendum: Towards recommendations for metadata and data handling in plant phenotyping

Krajewski, Paweł; Chen, Dijun; Ćwiek, Hanna; Dijk, Aalt D. J. van; Fiorani, Fabio; Kersey, Paul J.; Klukas, Christian; Lange, Matthias; Markiewicz, Augustyn; Nap, Jan Peter; Oeveren, Jan van; Pommier, Cyril; Scholz, Uwe; Schriek, Marco van; Usadel, Björn; Weise, Stéphan

doi:10.1093/jxb/ery006

Cited by 2 publications

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“…The observation scores used for phenotyping are described in an embedded "Trait Definition File." Thus, the provided metadata complies with the version 1.1 of the MIAPPE standard (Krajewski et al, 2015;Ćwiek-Kupczyńska et al, 2016;Papoutsoglou et al, 2020). Due to the strong diversity of phenotypic research data, the standard was initially developed to explain the minimal information that is necessary to describe plant phenotypic experiments.…”

Section: Miappe-compliant Isa-tab Exportmentioning

confidence: 99%

“…Rather, there are a large number of repositories with different specific focuses and data formats (Coppens et al, 2017). To supersede many different and incompatible text based formats for data storage and data exchange an international committee has agreed upon recommendations for a set of minimal information about plant phenotyping experiments (MIAPPE) (Krajewski et al, 2015;Ćwiek-Kupczyńska et al, 2016). An established way to digitize the results of biological and life science experiments for storage is the ISA framework (Sansone et al, 2012) and in particular the "ISA-Tab" file format (Rocca-Serra et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…An established way to digitize the results of biological and life science experiments for storage is the ISA framework (Sansone et al, 2012) and in particular the "ISA-Tab" file format (Rocca-Serra et al, 2010). In the plant science community, there is a common effort to establish the usage of MIAPPE-compliant ISA-Tab files for the export and transfer of data for plant phenotyping experiments (Krajewski et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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BRIDGE – A Visual Analytics Web Tool for Barley Genebank Genomics

et al. 2020

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Genebanks harbor a large treasure trove of untapped plant genetic diversity. A growing world population and a changing climate require an increase in the production and development of stress resistant plant cultivars while decreasing the acreage. These requirements for improved plant cultivars can be supported by the broader exploitation of plant genetic resources (PGR) as inputs for genomics-assisted breeding. To support this process we have developed BRIDGE, a data warehouse and exploratory data analysis tool for genebank genomics of barley (Hordeum vulgare L.). Using efficient technologies for data storage, data transfer and web development, we facilitate access to digital genebank resources of barley by prioritizing the interactive and visual analysis of integrated genotypic and phenotypic data. The underlying data resulted from a barley genebank genomics study cataloging sequence and morphological data of 22,626 barley accessions, mainly from the German Federal ex situ genebank. BRIDGE consists of interactively coupled modules to visualize integrated, curated and quality checked data, such as variation data, results of dimensionality reduction and genome wide association studies (GWAS), phenotyping results, passport data as well as the geographic distribution of germplasm samples. The core component is a manager for custom collections of germplasm. A search module to find and select germplasm by passport and phenotypic attributes is included as well as modules to export genotypic data in gzip-compressed variant call format (VCF) files and phenotypic data in MIAPPEcompliant ISA-Tab files. BRIDGE is accessible at the following URL: https://bridge.ipkgatersleben.de.

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Section: Miappe-compliant Isa-tab Exportmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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BRIDGE – A Visual Analytics Web Tool for Barley Genebank Genomics

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“…Among other objectives, transPLANT aims to develop and share standards for the description of data and metadata, which are critical to allow sharing of information between different resources. One example of this effort is the recommendations for plant phenotyping metadata and data handling put forth in a recent publication ( 50 , 51 ).…”

Section: Metadata and Persistencementioning

confidence: 99%

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

et al. 2018

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The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.

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Corrigendum: Towards recommendations for metadata and data handling in plant phenotyping

Cited by 2 publications

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BRIDGE – A Visual Analytics Web Tool for Barley Genebank Genomics

BRIDGE – A Visual Analytics Web Tool for Barley Genebank Genomics

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

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