English

This guide aims to help researchers utilise extensive survey data available. In particular, this guide is designed to support those starting small research projects, especially students doing dissertations. 

The guide includes materials to read, worksheets for getting started and questions to think about and answer.

This guide will cover how to map census data in QGIS. The example used in this guide creates a choropleth map showing the percentage of males who work in the manufacturing service using the QGIS package. 

This guide aims to show the strength of using Census Microdata for a variety of research purposes, via a worked example taken from real-life research. This guide assumes some familiarity with microdata, mapping and statistical software. 

These quantitative methods e-books and accompanying quizzes are for direct use in teaching students or for self-study. They aim to build skills in quantitative methods and statistical software and use the Living Costs and Food Survey.

Using SPSS, lecturers and students can utilise both the practical and quiz elements of each e-book topic. Topics include examining variables, correlations, regression and multiple regression.

The e-books have been developed through a collaboration of the UK Data Service, National Centre for Research Methods (NCRM), and the Centre for Multi-Level Modelling at the University of Bristol and were created using the StatJR software based on original outputs from the project Using Statistical E-books to teach undergraduate students quantitative methods and statistical software funded by the British Academy.

This module is a part of the introductory online course “Data Steward Training”. In this course learners will develop the skills and gain knowledge on how to be a successful data steward. 

By the end of this module, learners will:

• Understand different types of RDM services which their institution or organisation may need to provide. 

• Be able to use the RISE model to plan and develop your RDM services.

This module is suitable for data stewards and trainers seeking introductory learning material. It will take on average one hour to complete the module. 

The materials include a video presentation, a full video transcript, a PowerPoint presentation and a learning activity to support learning.   

This learning material has been developed in collaboration with the FAIRsFAIR and EOSC Synergy projects. The majority of the material has been used in previous online data steward instructor training workshops in 2020 and 2021.

This module is a part of the introductory online course “Data Steward Training”. In this course learners will develop the skills and gain knowledge on how to be a successful data steward. 

By the end of this module, learners will:

• Understand the range of elements of responsible research ecosystems.

• Be able to identify different ways to sustain and support responsible research. 

This module is suitable for data stewards and trainers seeking introductory learning material. It will take on average one hour to complete the module. 

The materials include a video presentation, a full video transcript, a PowerPoint presentation and a quiz to support learning.

This learning material has been developed in collaboration with the FAIRsFAIR and EOSC Synergy projects and has been adapted from the Data Steward Instructor Training Workshops run throughout 2020 and 2021.

This module is a part of the introductory online course “Data Steward Training”. In this course learners will develop the skills and gain knowledge on how to be a successful data steward. 

By the end of this module, learners will:

• Understand the role of pedagogy and learning activities to teach effectively. 

• Be able to critically assess the reasons for organising training activities.  

• Be able to create training which meets their aims and the needs of their learners.

This module is suitable for data stewards and trainers seeking introductory learning material. It will take on average one hour to complete the module. 

The materials include a video presentation, a full video transcript, a PowerPoint presentation and various learning activities and resources to support learning.   

This learning material has been developed in collaboration with the FAIRsFAIR and EOSC Synergy projects. The majority of the material has been used in previous online data steward instructor training workshops in 2020 and 2021. 

This module is a part of the introductory online course “Data Steward Training”. In this course learners will develop the skills and gain knowledge on how to be a successful data steward. 

By the end of this module, learners will:

• Be able to explain the difference between FAIR and Open Data to researchers.

• Be able to make data FAIR by using a set of practical guidelines and tools.

• Understand the range of skills and knowledge associated with data stewardship.

• Be aware of different approaches to stewardship service provision.

• Be able to identify key elements that help make research data discoverable, accessible, interoperable and reusable.

• Be able to practise making data FAIR. 

This module is suitable for data stewards and trainers seeking introductory learning material. It will take around 1 hour and 30 minutes to complete the module. 

The materials include video presentations, full video transcripts, PowerPoint presentations and various learning activities and resources to support learning.

This handbook aims to support higher education institutions with the integration of FAIR-related content in their curricula and teaching.  It was written and edited by a group of about 40 collaborators in a series of six book sprint events that took place between 1 and 10 June 2021. The document provides practical material, such as competence profiles, learning outcomes and lesson plans, and supporting information. It incorporates community feedback received during the public consultation which ran from 27 July to 12 September 2021.

The overall objective of FAIRsFAIR is to accelerate the realization of the goals of the EOSC by opening up and sharing all knowledge, expertise, guidelines, implementations, new trajectories, courses and education on FAIR matters. To support this, FAIRsFAIR is tasked to set up a single FAIR Data Stewardship Competence Centre which this report defines as a shared hub of expertise in implementing FAIR data stewardship principles, offering leadership, coordination and cataloging services to connect relevant people, guidance, learning resources and curricula in different thematic areas.

Requirements for competence centres in general and a core competence centre for FAIR data stewardship in general were identified by interviewing other members of the FAIRsFAIR project to understand their expectations for a core competence centre as well as the resources they will contribute to the knowledge base. Furthermore, we carried out a broad characterisation of current competence centres enriched with case studies of good examples for certain aspects of a competence centre. We created user stories for how stakeholders might interact with the competence centres and refined them through an open consultation answered by 106 people, interviews with EOSC clusters, and feedback gathered in workshops at the Open Science Fair 2019.