Data Protection and Ethics

training | ENG

This course focuses on data protection and ethics. It will help you understand the fundamental principles of data protection and introduce techniques to integrate these principles into your research processes.

By completing the course, you will learn:

• what personal data is and how to protect it,
• key considerations when creating consent forms,
• how to store your data securely,
• how to anonymize your data.

EOSC Task Force FAIR Metrics and Data Quality

set of recommendations | ENG

The Data Quality Group focused on establishing a shared understanding of key aspects of data quality, such as approaches, dataset lifecycle, stakeholders, and certification. Their activities included literature research, reviewing standards (e.g., ISO), and gathering insights from various initiatives (e.g., RDA, INSPIRE, CoreTrustSeal).

The group produced a draft set of recommendations in December 2022, hosted a professional discussion in June 2022, and released a survey in April that garnered over 700 views.

Towards a data quality framework for EOSC

Report | ENG

The document “Towards a Data Quality Framework for EOSC” highlights the pivotal role of data quality and outlines standards and processes that ensure trustworthiness, legitimacy, and practical usability of data. It emphasizes establishing compliance mechanisms and fostering trust within the research community, thereby strengthening EOSC as a reliable data management framework.

The recommendations are based on systematic literature reviews and consultations with the expert community. The framework aims to:

• Support community consensus on standards for FAIR data in research,
• Improve the structure and documentation of datasets for enhanced usability,
• Engage data producers and providers in actively enhancing data quality.

These efforts strive to raise awareness of the importance of data quality across scientific disciplines and propose a governance model that can significantly influence data management practices and policies within and beyond EOSC.

Compilation of data sources per research discipline

list of recommended resources | ENG

Southern Methodist University has compiled a list of recommended resources for finding existing data, along with a list of resources categorized by research field.

BioCollect (Advanced field data collection)

software| ENG

BioCollect: An advanced tool for collecting biodiversity data

BioCollect is a modern yet easy-to-use data collection tool for biodiversity science. It was developed by the Atlas of Living Australia in collaboration with a range of organisations to help users efficiently collect data for their projects. It also allows newly acquired biodiversity data to be easily integrated into the ALA database, where it is available for further use in research, policy and natural resource management. In this way, individual projects contribute to larger scientific goals.

BioCollect is designed for scientists, ecologists, citizen scientists and natural resource managers who need to collect and manage data related to biodiversity, ecology and natural resource management (NRM). The system is hosted on the ALA platform and is available to the public free of charge.

BioCollect main features:

Structured data collection through forms:
- Assessment and monitoring activities: For example, ad hoc surveys or systematic structured surveys based on specific methodologies.
- Activity-based projects: For example, vegetation restoration, ecosystem rehabilitation, or protection against invasive species of plants and animals.
Upload unstructured data, including:
- Data sets,
- Grey literature,
- Images, audio recordings and video links.
BioCollect is an innovative way to collect, manage and share biodiversity data, thus promoting collaboration and contributing to a better understanding and conservation of natural resources.