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The current fleet of X-ray telescopes produces a wealth of multi-dimensional data, allowing us to study sources in time, photon energy and polarization. At the same time, it has become increasingly clear that progress in our physical…
Managing data and code in open scientific research is complicated by two key problems: large datasets often cannot be stored alongside code in repository platforms like GitHub, and iterative analysis can lead to unnoticed changes to data,…
The increasing availability of free high-resolution earth observation data covering any point on the globe every few days led to the emergence of new remote sensing tools that can manipulate the very large volumes of data generated by those…
As current- and next-generation astronomical instruments come online, they will generate an unprecedented deluge of data. Analyzing these data in real time presents unique conceptual and computational challenges, and their long-term storage…
Fossil DNA preservation varies with depositional environments and diagenesis, producing fragments of heterogeneous origins and degradation states. We use first-principles biomolecular analysis to classify fossil molecular environments into…
We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data…
Smartphones and wearable sensors offer an unprecedented ability to collect peripheral psychophysiological signals across diverse timescales, settings, populations, and modalities. However, open-source software development has yet to keep…
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…
The Stratospheric Observatory for Infrared Astronomy (SOFIA) is an airborne astronomical observatory comprised of a 2.5-meter telescope mounted in the aft section of a Boeing 747SP aircraft. During routine operations, several instruments…
With the widespread application of drones in recent years, object detection of aerial images has attracted increasing attention, especially open-vocabulary aerial detection which is not restricted to predefined categories. Due to the…
Crucial steps in the formation of stars and planets can be studied only at mid-infrared to far-infrared wavelengths, where SIRTF provides an unprecedented improvement in sensitivity. We will use all three SIRTF instruments (IRAC, MIPS, and…
The introduction of large language models and other influential developments in AI-based language processing have led to an evolution in the methods available to quantitatively analyse language data. With the resultant growth of attention…
Major advancements in fields as diverse as biology and quantum computing have relied on a multitude of microscopic techniques. All optical, electron and scanning probe microscopy advanced with new detector technologies and integration of…
Four years after the last LISA meeting, the NASA Astrophysics Data System (ADS) finds itself in the middle of major changes to the infrastructure and contents of its database. In this paper we highlight a number of features of great…
Diamond Light Source (DLS), the UK synchrotron facility, attracts scientists from across the world to perform ground-breaking x-ray experiments. With over 3000 scientific users per year, vast amounts of data are collected across the…
We present the DTFE public software, a code for reconstructing fields from a discrete set of samples/measurements using the maximum of information contained in the point distribution. The code is written in C++ using the CGAL library and is…
The NASA Astrophysics Data System Abstract Service has become a key component of astronomical research. It provides bibliographic information daily, or near daily, to a majority of astronomical researchers worldwide. We describe the history…
In this paper, we introduce SciANN, a Python package for scientific computing and physics-informed deep learning using artificial neural networks. SciANN uses the widely used deep-learning packages Tensorflow and Keras to build deep neural…
We introduce the Mechanic, a new open-source code framework. It is designed to reduce the development effort of scientific applications by providing unified API (Application Programming Interface) for configuration, data storage and task…
Deep learning techniques have evolved rapidly in recent years, significantly impacting various scientific fields, including experimental particle physics. To effectively leverage the latest developments in computer science for particle…