Interoperability

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.

This interactive on-line course prepared by the Social Science Research Council and the Qualitative Data Repository contains four modules about different aspects of RDM of qualitative data in Social Sciences. Each module is composed by multiple lessons and can also function as a stand-alone resource to be completed individually. Most lessons include associated readings, resources, exercises, and activities.

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.

DataWiz is an automated assistant for data management in Psychology, developed by the Leibniz Institute for Psychology Information. It is a web-based application that supports researchers in planning their data management before the project starts and in managing their research data during the project. It provides functions to cover the entire research data lifecycle: data preparation, documentation and archiving. It also provides a digital collaborative working environment for you and your team. With DataWiz researchers can reduce the time spent on RDM, increase the quality and ensure the long-term reusability of research data.

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.

Utrecht University has created a simple decision-tree tool that helps researchers to choose a generic repository that best fits their needs. To do so, criteria such as restriction of access and cost of the repository are taken into account.

The University of Helsinki created, upon request, a compact guide for researchers to help with research data documentation. It first introduces the basic elements of documentation, and then provides practical instructions and strategies to proceed with documentation during the research project, but also for the publishing phase.

The OpenAire project has prepared a guideline to cost data management based on the work of the UK Data Service and the Landelijk Coördinatiepunt Research Data Management. For each data management phase, different activities are foreseen and a description and estimated costs are provided. The guidelines come with brief instructions on how to used them and a useful infographic about RDM and sharing data costs, prepared for OpenAire by the Digital Curation Centre.

The Southern Methodist University has compiled a list of recommended resources to find existing data, together with a list of sources categorized by research discipline.