Related papers: ADS: The Next Generation Search Platform
We introduce AXS (Astronomy eXtensions for Spark), a scalable open-source astronomical data analysis framework built on Apache Spark, a widely used industry-standard engine for big data processing. Building on capabilities present in Spark,…
The Sloan Digital Sky Survey Science Archive is the first in a series of multi-Terabyte digital archives in Astronomy and other data-intensive sciences. To facilitate data mining in the SDSS archive, we adapted a commercial database engine…
Automated decision systems (ADS) are increasingly used for consequential decision-making. These systems often rely on sophisticated yet opaque machine learning models, which do not allow for understanding how a given decision was arrived…
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…
The NASA Planetary Data System (PDS) hosts millions of images of planets, moons, and other bodies collected throughout many missions. The ever-expanding nature of data and user engagement demands an interpretable content classification…
Observational astronomy has changed drastically in the last decade: manually driven target-by-target instruments have been replaced by fully automated robotic telescopes. Data acquisition methods have advanced to the point that terabytes of…
Multiplication is arguably the most cost-dominant operation in modern deep neural networks (DNNs), limiting their achievable efficiency and thus more extensive deployment in resource-constrained applications. To tackle this limitation,…
Nowadays, science has been coming into a new paradigm, called data-intensive science. While current studies of the new phenomenon focused on building up infrastructure for this new paradigm, yet a few studies concern users of scientific…
Despite the large budgets spent annually on astronomical research equipment such as telescopes, instruments and supercomputers, the general trend is to analyse and view the resulting datasets using small, two-dimensional displays. We report…
With the vast majority of scientific papers now available online, this paper describes how the Web is allowing physicists and information providers to measure more accurately the impact of these papers and their authors. Provides a…
We describe the current status of CATS, a publicly accessible database (web-server http://cats.sao.ru) allowing one to search in hundreds of catalogs of astronomical objects discovered all along the electromagnetic spectrum. Our emphasis is…
With the rapid advancements in observational technologies and the widespread implementation of large-scale sky surveys, diverse electromagnetic wave data (e.g., optical and infrared) and non-electromagnetic wave data (e.g., gravitational…
Large digital sky surveys, over a broad range of wavelengths, both from the ground and from space observatories, are becoming a major source of astronomical data. Some examples include the Sloan Digital Sky Survey (SDSS) and the Digital…
To search an optimal sub-network within a general deep neural network (DNN), existing neural architecture search (NAS) methods typically rely on handcrafting a search space beforehand. Such requirements make it challenging to extend them…
The Keck Observatory Archive (KOA) curates all observational data acquired at the W. M. Keck Observatory. The archive is expected to grow rapidly as complex new instruments are commissioned and as the expectations of archive users have…
In the past few years, Differentiable Neural Architecture Search (DNAS) rapidly imposed itself as the trending approach to automate the discovery of deep neural network architectures. This rise is mainly due to the popularity of DARTS, one…
A Data Access Statement (DAS) is a formal declaration detailing how and where the underlying research data associated with a publication can be accessed. It promotes transparency, reproducibility, and compliance with funder and publisher…
ACS is an annual meeting for research on the initial goals of artificial intelligence and cognitive science, which aimed to explain the mind in computational terms and to reproduce the entire range of human cognitive abilities in…
The ever-increasing volumes of scientific data present new challenges for distributed computing and Grid technologies. The emerging Big Data revolution drives exploration in scientific fields including nanotechnology, astrophysics,…
As the Science Mission Directorate contemplates establishing an open code policy, we consider it timely to share our experiences as the developers of the open-source partial differential equation solver Dedalus. Dedalus is a flexible…