The RMGDD workshop will explore machine-augmented workflows to provide reliable FAIR metadata easily and reliably, as well as the required data discovery mechanisms that can leverage this metadata. Key topics include: Automated Metadata Extraction, Data Discovery Platforms, Solution Development Experience Showcase, and Clear Next Steps.
This workshop explores the fundamental scientific communication methodology using AI technology, software ecosystems, and methods of software usability, discovery, and automation, AI-enabled software and repository for enriching scientific communications, constructing tools like automated knowledge processing, knowledge graph constructions, and documentation generation in the context of science communication.
Through a series of presentations and discussions, participants will gain a comprehensive understanding of how AI, particularly generative AI, can transform science communication, making complex information more accessible and engaging for a broader audience. Furthermore, beyond communication, the workshop will highlight the broader impact of AI on scientific software ecosystems and repositories, as well as integration with critical technologies such as databases, workflow management, knowledge graphs, ontologies, and security frameworks. Discussions will explore AI-driven techniques for software analysis, repository management, discovery, and reusability.
Additionally, the workshop will highlight the interconnectedness of generative AI with other critical technologies, including databases, workflow management, knowledge graphs, ontologies, and security mechanisms. By examining these relationships, participants will develop a deeper appreciation of the broader impact of generative AI on scientific research and communication.
This workshop seeks to explore ideas and experiences on what kinds of infrastructure developments can improve upon the state of the art. Explorations of component packaging via containers and virtual machines, automation scripting, deployment, portability builds, and system support for these and other relevant activities are key infrastructure. Provenance collection, exploration, and tracking are key for a well-documented scientific output. Using existing systems to achieve these goals via experiences is important for developing best practices that span application domains. Data privacy techniques such as multi-party encryption and differential privacy are important as well. Issues with managing large data sets and workflow intermediate data, particularly those intended to manage publicly accessed data for use and reuse are encouraged. New techniques and technologies that address reproducibility requirements are also requested. We seek work on all of these, and related, topics as well as position and experience papers looking to drive the conversation for practitioners and researchers in these spaces.
This workshop contributes by sharing experiences and exploring the various technological infrastructure needs to support effective, convenient workflow systems and application composition structures and approaches across a broad spectrum of HPC environments from clusters to supercomputers to cloud systems.
The Global Research Platform (GRP) is an international scientific collaboration that aims to create one-of-a-kind advanced ubiquitous services that integrate resources around the globe at speeds of gigabits and terabits per second. GRP focuses on design, implementation, and operation strategies for next-generation distributed services and infrastructure to facilitate high-performance data gathering, analytics, transport, computing, and storage, at 100 Gbps or higher. GRP actively works with partners in North America, Asia, Europe, and South America to customize international fabrics and distributed cyberinfrastructure to support data-intensive scientific workflows.
This half-day workshop is designed for computer and data scientists, researchers, and academics who are actively engaged in eScience projects. The workshop addresses challenges in applying eScience technologies to real-world problems and provides a structured approach to enhancing collaboration, influence, and communication within interdisciplinary teams. Participants will gain insights into navigating complex academic, industry, and governmental landscapes to secure funding, align stakeholders, and drive impactful research outcomes.
Through interactive discussions and hands-on group exercises, attendees will explore frameworks such as ABT narrative structure (“And, But, Therefore”), empathy mapping for stakeholder alignment, and root-cause analysis using the 5 Whys. The workshop emphasises learning from both successful and failed initiatives to cultivate strategies for overcoming barriers in eScience work and research.
This workshop is tailored for computer and data scientists, PhD students, postdoctoral researchers, Professors, and senior academics actively involved in eScience projects. It is particularly relevant for those working at the intersection of computational science and societal challenges who seek to improve their ability to communicate research outcomes effectively, foster interdisciplinary collaboration, and secure funding.