Related papers: Combining data and metadata: hybrid tabular file f…
Multi-modal fusion approaches aim to integrate information from different data sources. Unlike natural datasets, such as in audio-visual applications, where samples consist of "paired" modalities, data in healthcare is often collected…
The astronomical community is grappling with the increasing volume and complexity of data produced by modern telescopes, due to difficulties in reducing, accessing, analyzing, and combining archives of data. To address this challenge, we…
Multimodal data fusion is a key approach for enhancing diagnosis in medical applications. We propose an asymmetric fusion strategy starting from a primary modality and integrating secondary modalities by disentangling shared and…
Cloud-based data commons, data meshes, data hubs, and other data platforms are important ways to manage, analyze and share data to accelerate research and to support reproducible research. This is an annotated glossary of some of the more…
Heterogeneous systems are becoming more common on High Performance Computing (HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task to obtain optimal performance on the GPU. Approaches to simplifying this task include…
Several different controlled vocabularies have been developed and used by the astronomical community, each designed to serve a specific need and a specific group. The Unified Astronomy Thesaurus (UAT) attempts to provide a highly structured…
Implementing big data storage at scale is a complex and arduous task that requires an advanced infrastructure. With the rise of public cloud computing, various big data management services can be readily leveraged. As a critical part of…
Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require…
Experimental materials data are heterogeneous and include a variety of metadata for processing and characterization conditions, making the implementation of data-driven approaches for developing novel materials difficult. In this paper, we…
We make a case for "planetary computing" -- infrastructure to handle the ingestion, transformation, analysis and publication of global data products for furthering environmental science and enabling better informed policy-making. We draw on…
Complex scientific codes and the datasets they generate are in need of a sophisticated categorization environment that allows the community to store, search, and enhance metadata in an open, dynamic system. Currently, data is often…
Astronomy has a long history of acquiring, systematizing, and interpreting large quantities of data. Starting from the earliest sky atlases through the first major photographic sky surveys of the 20th century, this tradition is continuing…
The sharing and citation of research data is becoming increasingly recognized as an essential building block in scientific research across various fields and disciplines. Sharing research data allows other researchers to reproduce results,…
Although the roles of data centers and computing centers are becoming more and more important, and on-line research is becoming the mainstream for astronomy, individual research based on locally hosted data is still very common. With the…
The explosive growth of multimodal data - spanning text, image, video, spatial, and relational modalities, coupled with the need for real-time semantic search and retrieval over these data - has outpaced the capabilities of existing…
This elementary review covers the basics of working with astronomical data, notably with images, spectra and higher-level (catalog) data. The basic concepts and tools are presented using both application software (DS9 and TOPCAT) and…
Biologists study Diatoms, a fundamental algae, to assess the health of aquatic systems. Diatom specimens have traditionally been preserved on analog slides, where a single slide can contain thousands of these microscopic organisms.…
We provide an overview of tools enabling users to utilize data from open sources for decision-making support in weakly-structured subject domains. Presently, it is impossible to replace expert data with data from open sources in the process…
In modern spatial statistics, the structure of data that is collected has become more heterogeneous. Depending on the type of spatial data, different modeling strategies for spatial data are used. For example, a kriging approach for…
For decades, the growth and volume of digital data collection has made it challenging to digest large volumes of information and extract underlying structure. Coined 'Big Data', massive amounts of information has quite often been gathered…