Introduction
The understanding of the development of scientific disciplines, knowledge dissemination, and technological evolution is predominantly informed by analyzing scientific publications, collaborative networks, and patent records. Brazil holds a prominent position in Latin America’s scientific production, becoming a key regional player and talent attractor. The growing digitization of...
The challenges of data sovereignty and AI
in the European Health Data Space (EHDS)
Talk abstract contribution to
SciDATACon Abstract ID: 61
Advancing Healthcare Research with Data, Analytics & AI Commons
Francis P. Crawley
Chair, International Data Policy Committee, CODATA
francis@codata.org
Version 3.0, 24 April 2025
The European Health Data Space (EHDS) represents a...
Background and Motivation
Controlled vocabularies and ontologies are essential for enabling data interoperability, discovery, and integration across domains. Repositories that host and expose these artifacts play a critical role in implementing the FAIR (Findable, Accessible, Interoperable, Reusable) principles. The OntoPortal Alliance, a collaboration of academic and commercial partners,...
Solid Earth science seeks to understand the complex chemical and physical processes shaping our planet. This knowledge is essential for addressing key societal challenges, from mitigating natural hazards to managing vital resources. Yet, the scale and nature of the data required for such research—spanning petabytes and crossing geographical, disciplinary, and temporal boundaries—necessitate a...
The increasing use of AI-based approaches such as machine learning (ML) across diverse scientific fields presents challenges for reproducibly disseminating and assessing research. As ML becomes increasingly integral to clinical applications, there is also a critical need for transparent reporting methods to ensure both comprehensibility and the reproducibility of pre-clinical research and...
Conducting high-quality research increasingly involves complex workflows and the generation of numerous intermediate datasets. Achieving reproducibility requires the availability of extensive and well-structured information. To enable this, researchers need interfaces and tools that are not only user-friendly but also FAIR-aware.
Data analysis workflows typically span multiple tools and...
- Introduction and Background
Recent policies and laws in the US that threaten data access have highlighted the need for infrastructure to ensure important government data is not lost during regime changes. US federal government information has been in the public domain since the 1895 Printing Act which prohibited any copyright on federal government publications (United States Congress,...
Rapid advances in AI technology have the potential to ease or speed Research into research data management challenges. The CODATA and WDS communities are already coming up with ways to leverage AI for data stewardship. With much of the research data community dedicated to FAIR implementation and the colloquial second meaning of FAIR being ‘Fully AI Ready’, there is conflation and confusion...
