Video

Through a series of videos featuring a variety of voices and perspectives and discussing a range of methodologies and theoretical approaches, this course aims to explore the history, practice and people involved in the evolving, highly diverse, and interdisciplinary field of Digital Humanities.

This introductory webinar is for anyone who is involved in the collection of data and is considering making (some of) their data available in accordance with funders’ requirements. More and more funders are requiring that research data be made available after completion of the research project, usually through the archiving of data in a trusted repository. However, research teams often still lack the appropriate skills and knowledge regarding how to properly prepare their data for archiving and sharing. This webinar aims to raise awareness about relevant key data management practices for sharing, specifically regarding data documentation, gaining consent, and data anonymisation. Addressing each of these three topics, it provides a short theoretical introduction, including what FAIR means and how it is implemented, as well as practical illustrations drawing on a large-scale cross-national survey (the European Social Survey). It also provides some practical tips with respect to data archiving, in particular how to choose an appropriate archive or repository.

This webinar is intended for everyone who wants to learn about ways of finding and reusing research data. Managing your research data in a FAIR and transparent manner is important. It helps researchers to meet requirements of funding institutions and ensures long-term re-usability of their data. The webinar introduces the CESSDA ERIC Data Catalogue as a means of finding and accessing research data. It enables participants to understand conditions for reuse (licenses) and introduces use-cases. This event is part of a workshop/webinar series organised by members of the SERISS project.

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 is privacy by design in research! The aim of this training material is to show researchers how to perform a data protection impact assessment for an innovative research scenario to enable responsible re-use of archived speech corpora.

The project website provides help to develop learning goals.

Taken from: Teaching with CLARIN: https://www.clarin.eu/content/privacy-design-research

These learning materials consist of a two-course module that seeks to provide humanities majors with a basic understanding of language technology and the practical skills needed to apply language technology using Python. The module is intended to empower the students by showing that language technology is both accessible and applicable to research in the humanities.

Taken from: Teaching with CLARIN 

https://www.clarin.eu/content/applied-language-technology 

The UK Data Service SecureLab has enabled secure access to the most sensitive and confidential data in the collection since 2011. SecureLab provides controlled access to data that are too detailed, sensitive or confidential to be made available under less restrictive access levels.