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Scientific topics: Data quality management 


Helis Academy course FAIR data stewardship 2021, Day 2, Finding and capturing data part 1

This presentation is part of the 3rd edition of the Helis Academy FAIR data stewardship (for life sciences) course Day 2, March 18, 2021

Scientific topics: FAIR data, Data quality management

Operations: Analysis

Keywords: Data collection

Resource type: Slidedeck

Helis Academy course FAIR data stewardship 2021, Day 2, Finding and capturing data part 1 http://tess.elixir-uk.org/materials/helis-academy-course-fair-data-stewardship-2021-day-2-finding-and-capturing-data This presentation is part of the 3rd edition of the Helis Academy FAIR data stewardship (for life sciences) course Day 2, March 18, 2021 FAIR data Data quality management Data collection PhD candidate
Plant Phenotyping Data managment Webinar (MIAPPE)

The Minimal Information About Plant Phenotyping Experiment, MIAPPE (www.miappe.org), has been designed by ELIXIR, EMPHASIS and Bioversity international, to guide plant scientist in the management of experimental data. Furthermore, since genetic studies relies on the integration and the linking...

Scientific topics: Data submission, annotation, and curation, Data quality management, Phenomics, Plant biology

Operations: Standardisation and normalisation

Resource type: Video, Slides

Plant Phenotyping Data managment Webinar (MIAPPE) http://tess.elixir-uk.org/materials/plant-phenotyping-data-managment-webinar-miappe The Minimal Information About Plant Phenotyping Experiment, MIAPPE (www.miappe.org), has been designed by ELIXIR, EMPHASIS and Bioversity international, to guide plant scientist in the management of experimental data. Furthermore, since genetic studies relies on the integration and the linking between phenotype and genotype datasets, relevant section of MIAPPE are beginning to be used for genotyping standards. This Webinar will give an overview of the current practices and methods for plant phenotyping data standardization, and how to deal with the variability and heterogeneity inherent to research and breeding data sets. Data management approaches at some of the major research organizations will be given as examples. The recording is available [here](https://youtu.be/4FOQPAWl6_M) and the slides are [here](https://drive.google.com/file/d/1FORlCX662T9dxiG4uzQwVXDXnq-sP0FP/view?usp=sharing) Cyril Pommier Anne-Françoise Adam-Blondon Célia Michotey Data submission, annotation, and curation Data quality management Phenomics Plant biology Researchers Biologists, Genomicists, Computer Scientists Biologists software developers, bioinformaticians
Custom training: OpenRefine

The aim of this training is to help you use OpenRefine on your own data. This can contain subjects like: load data files, import and parse data files from a URL clean data files: rename columns, transform and edit cells, split multivalue cells... transform data from one format to another:...

Scientific topics: Data quality management

Custom training: OpenRefine http://tess.elixir-uk.org/materials/custom-training-openrefine The aim of this training is to help you use OpenRefine on your own data. This can contain subjects like: load data files, import and parse data files from a URL clean data files: rename columns, transform and edit cells, split multivalue cells... transform data from one format to another: e.g. merge data from two files using  a column that is common to both data files, create new rows based on columns and vice versa... export cleaned, transformed data data manipulation pipelines data dashboards Data quality management Life Science Researchers PhD students post-docs 2016-04-22 2017-10-09