Data quality

Goodtables is a free online service for tabular data validation, developed by the Frictionless Data team of the Open Knowledge Foundation. This open source tool will check basic structural errors such as blank or duplicate rows, duplicate headers, whether all rows have the same number of columns, etc. The data can be validated by providing a URL to the file (e.g. link to GitHub repository) or by uploading a file. Several formats are admitted: csv, excel, LibreOffice, Data Package, etc. Besides, a data schema can be uploaded to enable further checks, such as whether the data type (e.g. date), format (e.g. YYYY-MM-DD) and possible data constrains (e.g. no later than 2000-01-01) are respected. Documentation about the tool is available at: http://docs.goodtables.io/index.html

Chemotion is an Open Source Electronic Laboratory Notebook for chemical researchers. The Chemotion ELN is equipped with the basic functionalities necessary for the acquisition and processing of chemical data, in particular the work with molecular structures and calculations based on molecular properties. The ELN allows the search for molecules and reactions not only within the user’s data but also in conventional external sources as provided by SciFinder and PubChem. The ELN provides tools to share data in the Chemotion Data Repository. More information available at: Tremouilhac, P., Nguyen, A., Huang, Y. et al. Chemotion ELN: an Open Source electronic lab notebook for chemists in academia. J Cheminform 9, 54 (2017). https://doi.org/10.1186/s13321-017-0240-0

The Data Curation primers are documents used as a reference to curate research data within a specific discipline area or when using certain software or data types. They are developed during a series of workshops were attendees get input from a mentor of the Data Curator Network. The results are published in GitHub repositories. The GeoDatabase Data Curation Primer provides guidelines to manage and organize geographic data in geodatabases, to describe such data using geospatial metadata standards and which actions can be undertaken to preserve geospatial data in the long term.

The knowledge base’s of the DataWiz is a complete RDM guideline for Psychology research to support or complement the use of the DataWiz data management tool. The content is structured in three sections: before, during and after data collection & analysis. The first section covers data management planning as well as the various legal and ethical aspects related to data management. The second section focuses on best practices and tips for handling and documenting data during research. Finally, the last section focuses on how to share and preserve data at the end of the project.

Utrecht University organises regular workshops to teach R basics: data handling and visualisation, and making research reproducible with R and R Markdown. The R Café has a more informal set-up, where researchers with R programming skills can meet and learn from each other, or from prepared exercises.

Data Carpentry has developed this course of data pre-processing with Open Refine, an open tool to work with data. The course covers several topics such as error correction and data formatting and harmonization.