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This resource is a collection of short guides designed to make lesson planning more efficient for those teaching data analysis skills. Drawing on real classroom experiences, each guide includes suggested research questions, dataset and exercises:

• Gender differences in sexual attitudes (PDF) (using the National Survey of Sexual Attitudes and Lifestyles).
• Risk factors associated with increased levels of systolic blood pressure (PDF) (using the Health Survey for England).
• The gender gap in life satisfaction (PDF) (using the Opinions and Lifestyle Survey).
• Public confidence in the police (PDF) (using the Crime Survey for England and Wales).

This resource is designed for teachers to get students to think about data and numbers, teach them how to interpret, analyse and visualise data. This will be done by answering questions such as what proportion of the British public opposes capital punishment, how have attitudes about gender roles changed over the last 30 years and how have levels of crime changed in the last few decades. 

Citing a dataset correctly is just as important as citing articles, books, images and websites - each dataset is a source of evidence to support our argument.

This resource includes videos, presentations and top ten tips for citing data. These can be used by trainers to teach and highlight the importance of data citation. 

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.

The Standardization Survival Kit (SSK) is designed to support researchers in selecting and using the appropriate standards for their particular disciplines and work flows. The SSK is an online tool which focuses on giving researchers access to standards in a meaningful way by using research scenarios which cover all the domains of the Humanities, from literature to heritage science, including history, social sciences, linguistics, etc.

FAQ by OpenAIRE answering various questions around Open Science and RDM.

OpenAIRE is preparing use case narratives with scenarios of Open Science services offered by OpenAIRE targeting different users: researchers, research communities/research infrastructures, content providers, funders, managers of research.

The main goal is to showcase how OpenAIRE services are contributing to embed Open Science into researchers' daily workflow and to implement and align Open Science policies and infrastructures across European research institutions.

Benefits and assumptions of those who already use the OpenAIRE services and several best practices on Open Access publishing, sharing research data and enriching the repositories content will be made available on the website

In an effort to make open access for publications and data simple for everyone, OpenAIRE is creating factsheets with a brief overview of how to comply with H2020 OA mandates and how to use OpenAIRE services where available.

This is a collection of resources dedicated to teachers, trainers and their students but could also be useful to researchers and the general public. It includes guides, e-books, slides and webinars covering a wide range of topics: quantitative methods, statistical software, teaching data analysis, data visualisation, qualitative methods and psychosocial approaches.

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