Related papers: A Case for Data Commons: Towards Data Science as a…
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…
The data volumes stored in telescope archives is constantly increasing due to the development and improvements in the instrumentation. Often the archives need to be stored over a distributed storage architecture, provided by independent…
Data science requires time-consuming iterative manual activities. In particular, activities such as data selection, preprocessing, transformation, and mining, highly depend on iterative trial-and-error processes that could be sped-up…
The computational demands for scientific applications are continuously increasing. The emergence of cloud computing has enabled on-demand resource allocation. However, relying solely on infrastructure as a service does not achieve the…
Data and Science has stood out in the generation of results, whether in the projects of the scientific domain or business domain. CERN Project, Scientific Institutes, companies like Walmart, Google, Apple, among others, need data to present…
Cyber-security solutions are traditionally static and signature-based. The traditional solutions along with the use of analytic models, machine learning and big data could be improved by automatically trigger mitigation or provide relevant…
High Performance Computing (HPC), Artificial Intelligence (AI)/Machine Learning (ML), and Quantum Computing (QC) and communications offer immense opportunities for innovation and impact on society. Researchers in these areas depend on…
Spatial data science has emerged in recent years as an interdisciplinary field. This position paper discusses the importance of building and sharing high-quality datasets for spatial data science.
Objective: To create a commons for infectious disease (ID) epidemiology in which epidemiologists, public health officers, data producers, and software developers can not only share data and software, but receive assistance in improving…
The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of…
Neurophysiology research has demonstrated that it is possible and valuable to investigate sensory processing in scenarios involving continuous sensory streams, such as speech and music. Over the past 10 years or so, novel analytic…
Every research project necessitates data, often requiring sharing and collaborative review within a team. However, there is a dearth of good open-source data sharing and reviewing services. Existing file-sharing services generally mandate…
Technology market is continuing a rapid growth phase where different resource providers and Cloud Management Frameworks are positioning to provide ad-hoc solutions -in terms of management interfaces, information discovery or billing- trying…
Undergraduate research experiences hold many potential benefits. Students can learn about new areas opening up previously unknown paths in academia and industry. The hands-on experience often provides a deeper understanding of what science,…
The landscape of workflow systems for scientific applications is notoriously convoluted with hundreds of seemingly equivalent workflow systems, many isolated research claims, and a steep learning curve. To address some of these challenges…
Finding data is a necessary precursor to being able to reuse data, although relatively little large-scale empirical evidence exists about how researchers discover, make sense of and (re)use data for research. This study presents evidence…
Modern tools for biological research, especially microscopy, have rapidly advanced in recent years, which has led to the generation of increasingly large amounts of data on a regular basis. The result is that scientists desperately need…
Data Science is a complex and evolving field, but most agree that it can be defined as a combination of expertise drawn from three broad areascomputer science and technology, math and statistics, and domain knowledge -- with the purpose of…
Research-computing continues to play an ever increasing role in academia. Access to computing resources, however, varies greatly between institutions. Sustaining the growing need for computing skills and access to advanced…
Collaborative Data Sharing raises a fundamental issue in distributed systems. Several strategies have been proposed for making shared data consistent between peers in such a way that the shared part of their local data become equal. Most of…