A5060540398- Scientific Computing and Data Management
- Research Data Management Practices
- Data Quality and Management
- Distributed and Parallel Computing Systems
- Advanced Data Storage Technologies
- Big Data and Business Intelligence
- Information and Cyber Security
- Explainable Artificial Intelligence (XAI)
- Artificial Intelligence in Healthcare
- Advanced Proteomics Techniques and Applications
- Machine Learning and Data Classification
- Genetics, Bioinformatics, and Biomedical Research
- Bioinformatics and Genomic Networks
- Online Learning and Analytics
- scientometrics and bibliometrics research
- Innovation and Socioeconomic Development
- Libraries and Information Services
- Cloud Computing and Resource Management
- Animal Nutrition and Physiology
- Interdisciplinary Research and Collaboration
- Food Chemistry and Fat Analysis
- Metabolomics and Mass Spectrometry Studies
- Advanced Database Systems and Queries
- Private Equity and Venture Capital
- Plant Virus Research Studies
University of California, San Diego
2016-2025
San Diego Supercomputer Center
2016-2025
Emory University
2025
Universidade do Porto
2023
Ronin Institute
2023
University of Tennessee at Knoxville
2023
University of Utah
2023
Lawrence Livermore National Laboratory
2023
Swiss Data Science Center
2022
Université Libre de Bruxelles
1994-1998
The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders since their publication in 2016. By intention, the 15 guiding do not dictate specific technological implementations, but provide guidance for improving Findability, Accessibility, Interoperability Reusability digital resources. This has likely contributed to adoption principles, because individual stakeholder communities can implement own solutions. However, it also resulted inconsistent...
A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management stewardship, with the goal enabling reusability scholarly data. The also meant to apply other digital assets, at a high level, over time, FAIR guiding have been re-interpreted or extended include software, tools, algorithms, workflows that produce are now being adapted context AI models datasets. Here, we present perspectives, vision,...
A growing number of software tools have been developed for metabolomics data processing and analysis. Many new are contributed by practitioners who limited prior experience with development, the subsequently implemented users expertise that ranges from basic point-and-click analysis to advanced coding. This Perspective is intended introduce developers important considerations determine overall impact a publicly available tool within scientific community. The recommendations reflect...
Machine learning research has long focused on models rather than datasets, and prominent datasets are used for common ML tasks without regard to the breadth, difficulty, faithfulness of underlying problems. Neglecting fundamental importance data given rise inaccuracy, bias, fragility in real-world applications, is hindered by saturation across existing dataset benchmarks. In response, we present DataPerf, a community-led benchmark suite evaluating data-centric algorithms. We aim foster...
Computational models are complex scientific constructs that have become essential for us to better understand the world. Many valuable peers within and beyond disciplinary boundaries. However, there no widely agreed-upon standards sharing models. This paper suggests 10 simple rules you both (i) ensure share in a way is at least “good enough,” (ii) enable others lead change towards model-sharing practices.
This article explores the global implementation of FAIR Guiding Principles for scientific management and data stewardship, which provide that should be findable, accessible, interoperable reusable. The these principles is designed to lead stewardship as digital objects establishment Internet Data Services (IFDS). If reaches a tipping point, IFDS has potential revolutionize how managed by making machine human readable discoverable reuse. Accordingly, this examines expansion Principles,...
Jordan is one of the most water-scarce regions in world, facing climate change impacts on water, energy, and food—the core components WEF Nexus. Health, as an additional dimension nexus, being investigated through NIH-funded Global Center Climate Change, Water, Energy, Food, Health Systems (GC3WEFH). A key component its Data Hub, which focuses providing analytical access to datasets that reflect WEFH nexus assembling open-source software ecosystem support integrative research while...
Childhood maltreatment and HIV are both associated with a greater risk for adverse mental health, including posttraumatic stress disorder (PTSD), depression, increased systemic inflammation. However, it remains unknown whether childhood interact to exacerbate PTSD, inflammation in manner that may further increase the of health outcomes people living HIV. This study investigated interaction between status on PTSD depression symptom severity, peripheral concentrations lipopolysaccharide (LPS)...
Understanding the earth as a system requires integrating many forms of data from multiple fields. Builders and funders cyberinfrastructure designed to enable open sharing in geosciences risk key failure mode: What if geoscientists do not use share, discover reuse data? In this study, we report baseline assessment engagement with NSF EarthCube initiative, an effort for geosciences. We find scientists perceive need cross-disciplinary engage where there is organizational or institutional...
The industry sector is a very large producer and consumer of data, many companies traditionally focused on production or manufacturing are now relying the analysis amounts data to develop new products services. As sources needed distributed outside company, FAIR will have major impact, both by reducing existing internal silos enabling efficient integration with external (public commercial) data. Many still in early phases “FAIRification”, providing opportunities for SMEs academics apply...
As efforts advance around the globe, US falls behind.
This article investigates expansion of the Internet FAIR Data and Services (IFDS) to Africa, through three GO pillars: CHANGE, BUILD TRAIN. Introduction IFDS in Africa has a focus on digital health. Two examples introducing are compared: regional initiative for health by governments East Community (EAC) an local provider (Solidarmed) collaboration with Great Zimbabwe University Zimbabwe. The obstacles identified as underrepresentation data from at this moment, lack explicit recognition...
La rickettsie Cowdria ruminantium a été cultivée avec succès dans des lignées de cellules endothéliales bovines (ombilicales, BUEC, et microvasculature, BMC), ainsi que cultures primaires d'aorte bovin (BAEC), mais manière plus surprenante, également d'origine humaine : veine ombilicale (HUVEC) microvasculature (HEMEC). Cette première preuve pathogénicité cette bovine pour le système cellulaire humain provoque un nouvel intérêt concernant sa signification possible la santé humaine. Elle...
The growing size of high-value sensor-born or computationally derived scientific datasets are pushing the boundaries traditional models data access and discovery. Due to their size, these often accessible only through systems on which they were created. Access for exploration reproducibility is limited file transfer by applying used store generate original data, infeasible. There a trend toward providing large-scale research in-place via container-based analysis environments. This paper...
The lack of a readily accessible, tightly integrated data fabric connecting high-speed networking, storage, and computing services remains critical barrier to the democratization scientific discovery. To address this challenge, we are building National Science Data Fabric (NSDF), holistic ecosystem facilitate domain scientists in their daily research. NSDF comprises services, as well outreach initiatives. In paper, present testbed integrating three (i.e., computing). We evaluate performance....
Across domains massive amounts of scientific data are generated. Because the large volume information, discoverability is a challenge, especially for scientists who have not generated or from other domains. As part NSF-funded National Science Data Fabric (NSDF) initiative, we developed testbed to demonstrate that these boundaries can be overcome. In support this effort, identify need indexing large-amounts across We propose NSDF-Catalog, lightweight service with minimal metadata complements...
This perspective article presents the vision of combining findable, accessible, interoperable, and reusable (FAIR) Digital Objects with National Science Data Fabric (NSDF) to enhance data accessibility, scientific discovery, education.Integrating FAIR into NSDF overcomes access barriers facilitates extraction machine-actionable metadata in alignment principles.The discusses examples climate simulations materials science workflows establishes groundwork for a dataflow design that prioritizes...
Urgent responses to the COVID-19 pandemic depend on increased collaboration and sharing of data, models, resources among scientists researchers. In many scientific fields disciplines, institutional norms treat as proprietary, emphasizing competition researchers locally internationally. Concurrently, long-standing open data exist in some have accelerated within last two decades. both cases-where arrangements are ready accelerate for needed a where they run counter what is needed-the rules...
The CHEESE project supplements and enhances traditional cybersecurity education with hands-on, practical experience in common flaws solutions. requires only a web browser, allowing users to develop skills without compromising their own computer or spending hours setting up complex virtual machine (VM) sandbox environment. In this tutorial we will conduct hands-on walkthrough of couple demonstrations on present an overview the platform community-driven contribution development process.