Related papers: Collaborative Cloud Computing Framework for Health…
In era of ever-expanding data and knowledge, we lack a centralized system that maps all the faculties to their research works. This problem has not been addressed in the past and it becomes challenging for students to connect with the right…
High-performance computing (HPC) is essential for tackling complex computational problems across various domains. As the scale and complexity of HPC applications continue to grow, the need for scalable systems and software architectures…
Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source…
The fundamental aim of the healthcare sector is to incorporate different technologies to observe and keep a track of the various clinical parameters of the patients in day to day life. Distant patient observation applications are becoming…
In open-source software development environments; textual, numerical and relationship-based data generated are of interest to researchers. Various data sets are available for this data, which is frequently used in areas such as software…
Developing software to undertake complex, compute-intensive scientific processes requires a challenging combination of both specialist domain knowledge and software development skills to convert this knowledge into efficient code. As…
With the shifting focus of organizations and governments towards digitization of academic and technical documents, there has been an increasing need to use this reserve of scholarly documents for developing applications that can facilitate…
This work explores the use of big data technologies deployed in the cloud for processing of astronomical data. We have applied Hadoop and Spark to the task of co-adding astronomical images. We compared the overhead and execution time of…
The advent of experimental science facilities-instruments and observatories, such as the Large Hadron Collider, the Laser Interferometer Gravitational Wave Observatory, and the upcoming Large Synoptic Survey Telescope-has brought about…
Experimental Particle Physics has been at the forefront of analyzing the world's largest datasets for decades. The HEP community was among the first to develop suitable software and computing tools for this task. In recent times, new…
Scientific communities naturally tend to organize around data ecosystems created by the combination of their observational devices, their data repositories, and the workflows essential to carry their research from observation to discovery.…
Influenced by the advances in data and computing, the scientific practice increasingly involves machine learning and artificial intelligence driven methods which requires specialized capabilities at the system-, science- and service-level…
Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift towards…
The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as…
Environmental science is often fragmented: data is collected using mismatched formats and conventions, and models are misaligned and run in isolation. Cloud computing offers a lot of potential in the way of resolving such issues by…
The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of…
As software systems increase in complexity, conventional monitoring methods struggle to provide a comprehensive overview or identify performance issues, often missing unexpected problems. Observability, however, offers a holistic approach,…
The excessive amounts of data generated by devices and Internet-based sources at a regular basis constitute, big data. This data can be processed and analyzed to develop useful applications for specific domains. Several mathematical and…
This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which convened more than 40 experts from national…
Data commons collate data with cloud computing infrastructure and commonly used software services, tools and applications to create biomedical resources for the large-scale management, analysis, harmonization, and sharing of biomedical…