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Plant Methods. 2016 Nov 9;12:44. eCollection 2016.

Measures for interoperability of phenotypic data: minimum information requirements and formatting.

Author information

1
Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, 60-479 Poznań, Poland.
2
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstraße 3, 06466 Stadt Seeland, Germany.
3
Bioversity International, parc Scientifique Agropolis II, 34397 Montpellier Cedex 5, France.
4
Institute for Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany.
5
INRA, UR1164 URGI - Research Unit in Genomics-Info, INRA de Versailles-Grignon, Route de Saint-Cyr, 78026 Versailles, France.
6
Forschungszentrum Jülich GmbH, IBG-2 Plant Sciences, 52425 Jülich, Germany.
7
Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, 60-479 Poznań, Poland ; Institute of Computing Science, Poznań University of Technology, ul. Piotrowo 3a, 60-479 Poznań, Poland.
8
LemnaTec GmbH, Pascalstraße 59, 52076 Aachen, Germany.
9
Poznań Supercomputing and Networking Center Affiliated to the Institute of Bioorganic Chemistry, Polish Academy of Sciences, ul. Jana Pawła II 10, 61-139 Poznań, Poland.
10
UMR MISTEA, INRA SupAgro, Place Pierre Viala 2, 34060 Montpellier, France.
11
Keygene N.V., Agro Business Park 90, 6708 PW Wageningen, The Netherlands.
12
Oxford e-Research Centre, University of Oxford, 7 Keble Road, Oxford, OX1 3QG UK.
13
Gregor Mendel Institute, Austrian Academy of Sciences, 1030 Vienna, Austria.
14
Forschungszentrum Jülich GmbH, IBG-2 Plant Sciences, 52425 Jülich, Germany ; Institute of Biology I, BioSC, RWTH Aachen, Worringer Weg 3, Aachen, Germany.
15
The European Molecular Biology Laboratory-The European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD UK.

Abstract

BACKGROUND:

Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse.

RESULTS:

In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented.

CONCLUSIONS:

Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.

KEYWORDS:

Data standardisation and formatting; Experiment description; Experimental metadata; Minimum information recommendations; Plant phenotyping

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