Researcher

The ARDC is a transformational initiative that enables Australian research community and industry access to nationally significant, leading edge data intensive eInfrastructure, platforms, skills and collections of high-quality data. The purpose of the ARDC is to provide Australian researchers with competitive advantage through data, providing access to leading edge eResearch collections, tools, infrastructure and services. Its mission is to accelerate research and innovation by driving excellence in the creation, analysis and retention of high-quality data assets.

The DDI Training Group developed training material for trainers to use and published them in Zenodo. Further slides will be added to the Zenodo Community in the future.

The Luxembourg Centre for Contemporary and Digital History (C²DH) is the University of Luxembourg’s third interdisciplinary research centre, focusing on high-quality research, analysis and public dissemination in the field of contemporary Luxembourgish and European history. It promotes an interdisciplinary approach with a particular focus on new digital methods and tools for historical research and teaching.

Learning modules on longitudinal studies. Each module of the Learning Hub can be downloaded to work through offline. In this section, you’ll find all the module section downloads all in once place. The learning modules include:

• Introduction to longitudinal studies
• Study design
• Data harmonisation
• Understanding metadata
• Analysing longitudinal data
• Research communications

Section of the Library and information service of Stellenbosch University offering Training and Consultancy on Research Data Management

Ranke.2 is a teaching platform for lecturers and students of History to teach how to apply source criticism to digitised and digital born historical sources.

This is a five-week course for individuals that support researchers to manage and share their data, including librarians, IT and information specialists, data stewards, and research office staff. You’ll discover common research support services, how to create data management plans, and how to develop your own research data management roadmap. You will learn from experts in the field from the internationally-recognised Digital Curation Centre and Research Data Netherlands and build your confidence in supporting researchers and preserving data. This course has been certified by the CPD Certification Service as conforming to continuing professional development principles.

Stellenbosch University Library and Information Service is pleased to announce the launch of the Research Data Management (RDM) Adventure Game. The RDM Adventure Game is a text-based role-playing interactive fiction serious game, based on the data management challenges of a research project. The game takes the form of an online choose-your-own-adventure format in which game players take a simulated research project through the following processes: data management planning, data collection/generation, data organisation, data description and research publication, while encountering data management challenges along the way. The game was developed as part of a collaboration between the University of Bath Library and Stellenbosch University Library and Information Service between 2017 and 2020 by Alex Ball (University of Bath), Samuel Simango (Stellenbosch University) and Nushrat Khan (University of Bath). In January 2021, the Wellcome Trust's Early Career Researchers Advisory Board endorsed the game by including it in the Wellcome Open Research early career researchers pack, recognising it as a useful tool for researchers.

The Game itself is available here 

QAMyData is an easy-to-use, open source tool that provides a health check for numeric data. The tool uses automated methods to detect and report on some of the most common problems in survey or numeric data, such as missingness, duplication, outliers and direct identifiers.

The tool offers a number of configurable tests that have been categorised into four types: file, metadata, data integrity, and identifiers, which can be run on popular file formats, including SPSS, Stata, SAS and CSV. A standard config file has default settings for each test, such as a threshold for pass or fail on various tests (e.g. detect value label that are truncated, email addresses identified as a string, or undefined missing values) which can be easily adapted to meet the user’s own desired thresholds. The configuration feature allows the creation of a unique Data Quality Profile. The software creates a ‘data health check’ that details errors and issues as both a summary and detailed report, providing a location of the failed test. New tests can easily be added. Data depositors and publishers can act on the results and resubmit the file until a clean bill of health is produced.

These introductory level interactive modules are designed for users who want to get to grips with key aspects of survey, longitudinal and aggregate data.

Modules can be conducted in your own time and you are able to dip in and out when needed. The modules give an introduction to key aspects of the data using short instructional videos, interactive quizzes and activities using open access software where possible.

Each module stands alone but those with little experience of surveys may find it useful to start with the Survey Data Module before moving on to the Longitudinal Data Module.

Modules include: Survey Data, Longitudinal Data, Aggregate Data