The rapid growth in global data production, particularly from remote sensing and Earth observation, has created significant opportunities to address pressing global challenges such as climate change, biodiversity loss, and sustainable resource management. Open data from satellites, drones, and environmental sensors, although increasingly available, often require complex integration due to...
As funding agencies increasingly emphasize responsible data stewardship in alignment with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, Data Management Plans (DMPs) have become a core requirement in research proposals. This emphasis reflects a growing recognition that data serves as the foundation for scientific discovery and progress. Since 2023, the National...
EcoCommons is a national digital infrastructure purpose-built to advance responsible, reproducible, and scalable ecological modelling in the era of FAIR data. It enables researchers, policymakers, and environmental managers to access integrated datasets, run validated modelling workflows, and share reproducible outputs that can inform biodiversity conservation, climate adaptation, and land-use...
Recent advancements in artificial intelligence (AI) and access to new types of data have led to increased applications of AI in computational social science and humanities (SSH). A wide range of cutting-edge examples shows the results of bringing AI and SSH together, from the latest computer vision AI models used to detect archaeological traces in satellite imagery or to identify mounds on...
Integrated Reference Architecture for AI-Enabled Healthcare Research:
An Australian Harmonized Approach
Gnana K Bharathy and Adrian Burton, Australian Research Data Commons (ARDC)
gnana.bharathy@ardc.edu.au
(SciDATACon Abstract ID: 61 suitable for Healthcare Data, Analytics & AI Commons...
Funding bodies and publishing venues increasingly require researchers to deposit and share their data in order to support rigorous, responsible, and reproducible science. Rising to the occasion, libraries have been expanding their scope to support research data as a scholarly resource and are increasingly recognized as providers of research data management and repository services. These trends...
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 โFully AI Readyโ, there is conflation and confusion...
The FAIR guiding principles indicate that scientific datasets should be annotated with โrichโ metadata that adhere to relevant community standards. Those standards include metadata reporting guidelines, which enumerate the attributes needed to describe the features of the experiments that led to the corresponding data, and the controlled terms that standardize the values of those metadata...
