Related papers: Data Aggregation In The Astroparticle Physics Dist…
Machine learning has proved to be a useful tool for extracting knowledge from scientific data in numerous research fields, including astrophysics, genomics, and molecular dynamics. Often, data sets from these research areas need to be…
The Smithsonian/NASA Astrophysics Data System (ADS) provides a search system for the astronomy and physics scholarly literature. All major and many smaller astronomy journals that were published on paper have been scanned back to volume 1…
In this paper, we present a survey of "on-disk" data processing (ODDP). ODDP, which is a form of near-data processing, refers to the computing arrangement where the secondary storage drives have the data processing capability. Proposed ODDP…
The ZEUS data preservation (ZEUS DP) project assures continued access to the data and documentation related to the experiment. It aims to provide the ability to continue the generation of valuable scientific results from these data in the…
Over the next decade we will witness the development of a new infrastructure in support of data-intensive scientific research, which includes Astronomy. This new networked environment will offer both challenges and opportunities to our…
As an alternative to downloading content from a cellular access network, mobile devices could be used to store data files and distribute them through device-to-device (D2D) communication. We consider a D2D-based storage community that is…
The battery-less Internet of Things (IoT) devices are a key element in the sustainable green initiative for the next-generation wireless networks. These battery-free devices use the ambient energy, harvested from the environment. The energy…
Physics analysis in astroparticle experiments requires the capability of recognizing new phenomena; in order to establish what is new, it is important to develop tools for automatic classification, able to compare the final result with data…
As scientific discovery becomes increasingly data-driven, software platforms are needed to efficiently organize and disseminate data from disparate sources. This is certainly the case in the field of materials science. For example,…
As the amount of scientific data continues to grow at ever faster rates, the research community is increasingly in need of flexible computational infrastructure that can support the entirety of the data science lifecycle, including…
Data access and interoperability module connects the observation proposals, data, virtual machines and software. According to the unique identifier of PI (principal investigator), an email address or an internal ID, data can be collected by…
Data assimilation addresses the general problem of how to combine model-based predictions with partial and noisy observations of the process in an optimal manner. This survey focuses on sequential data assimilation techniques using…
ASPID stands for the "Archive of Spectral, Photometric, and Interferometric Data". The world largest collection of raw 3D spectroscopic observations of galactic and extragalactic sources is provided. ASPID-SR is a prototype of an archive of…
Data center operators are typically faced with three significant problems when running their data centers, i.e., rising electricity bills, growing carbon footprints and unexpected power outages. To mitigate these issues, running data…
Association rule mining is a time consuming process due to involving both data intensive and computation intensive nature. In order to mine large volume of data and to enhance the scalability and performance of existing sequential…
Recent and forthcoming advances in instrumentation, and giant new surveys, are creating astronomical data sets that are not amenable to the methods of analysis familiar to astronomers. Traditional methods are often inadequate not merely…
Distributed multi-party learning provides an effective approach for training a joint model with scattered data under legal and practical constraints. However, due to the quagmire of a skewed distribution of data labels across participants…
By combining data from the text, citation, and reference databases with data from the ADS readership logs we have been able to create Second Order Bibliometric Operators, a customizable class of collaborative filters which permits…
In this paper we propose a new approach for Big Data mining and analysis. This new approach works well on distributed datasets and deals with data clustering task of the analysis. The approach consists of two main phases, the first phase…
In the past two years, the environment within which astronomers conduct their data analysis and management has rapidly changed. Working Groups associated with international societies and Big Data projects have emerged to support and…