Papoutsoglou Evangelia A, Faria Daniel, Arend Daniel, Arnaud Elizabeth, Athanasiadis Ioannis N, Chaves Inês, Coppens Frederik, Cornut Guillaume, Costa Bruno V, Ćwiek-Kupczyńska Hanna, Droesbeke Bert, Finkers Richard, Gruden Kristina, Junker Astrid, King Graham J, Krajewski Paweł, Lange Matthias, Laporte Marie-Angélique, Michotey Célia, Oppermann Markus, Ostler Richard, Poorter Hendrik, Ramı Rez-Gonzalez Ricardo, Ramšak Živa, Reif Jochen C, Rocca-Serra Philippe, Sansone Susanna-Assunta, Scholz Uwe, Tardieu François, Uauy Cristobal, Usadel Björn, Visser Richard G F, Weise Stephan, Kersey Paul J, Miguel Célia M, Adam-Blondon Anne-Françoise, Pommier Cyril
Plant Breeding, Wageningen University & Research, PO Box 386, Wageningen, 6700AJ, the Netherlands.
BioData.pt, Instituto Gulbenkian de Ciência, 2780-156, Oeiras, Portugal.
New Phytol. 2020 Jul;227(1):260-273. doi: 10.1111/nph.16544. Epub 2020 Apr 25.
Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.
在现代科学中，实现数据重用和知识发现变得越来越重要，这需要努力使数据发布实践标准化。由于植物表型领域的复杂性和异质性，这一任务尤其具有挑战性。我们发布了MIAPPE 1.1版本，该版本在覆盖范围上增强了现有的MIAPPE标准，通过明确的数据模型在结构上支持多年生植物，并通过定义和示例在清晰度上提供支持。我们通过使用MIAPPE 1.1以多种不同格式表达多个异构表型实验来评估它，以证明其适用性以及各种实现之间的互操作性。此外，由于其中一个数据集在MIAPPE 1.0下无法描述，这证明了其扩展的覆盖范围。MIAPPE 1.1由于其扩展的覆盖范围，尤其是其数据模型的形式化，这有助于以不同格式实现，标志着在实现植物表型数据可重用性方面迈出了重要一步。社区反馈对这一发展至关重要，并且将是确保该标准被采用的关键部分。
