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Scientific topics: Data quality management 

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) https://tess.elixir-europe.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
ObjTables Python tutorials

ObjTables is a toolkit for creating re-usable datasets that are both human and machine-readable, combining the ease of spreadsheets (e.g., Excel workbooks) with the rigor of schemas (classes, their attributes, the type of each attribute, and the possible relationships between instances of...

Scientific topics: Data submission, annotation and curation, Data quality management, Data integration and warehousing, Data management

Operations: Validation

Keywords: spreadsheet, schema, table, workbook, worksheet, XLSX, Excel, standard, reuse, compose, integrate, quality control

Resource type: Jupyter notebook

ObjTables Python tutorials https://tess.elixir-europe.org/materials/objtables-python-tutorials ObjTables is a toolkit for creating re-usable datasets that are both human and machine-readable, combining the ease of spreadsheets (e.g., Excel workbooks) with the rigor of schemas (classes, their attributes, the type of each attribute, and the possible relationships between instances of classes). ObjTables consists of a format for describing schemas for spreadsheets, numerous data types for science, a markup format for indicating the class and attribute represented by each table and column in a workbook, and software for using schemas to rigorously validate, merge, split, compare, and revision datasets. ObjTables is ideal for supplementary materials of journal article, as well as for emerging domains which need to quickly build new formats for new types of data and associated software with minimal effort. The tutorials provide a brief introduction to the ObjTables format for schemas for spreadsheets, the ObjTables markup syntax for spreadsheets, and the ObjTables Python package for parsing, validating, querying, editing, comparing, merging, splitting, revisioning, migrating, and analyzing spreadsheets. Data submission, annotation and curation Data quality management Data integration and warehousing Data management spreadsheet, schema, table, workbook, worksheet, XLSX, Excel, standard, reuse, compose, integrate, quality control Researchers Scientists Data scientists computational scientists
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 https://tess.elixir-europe.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