arXiv subjects

Toba Oluyide

Publications and source records attributed to Toba Oluyide.

3 recordsLinked to original sources

arXiv2026

A New Plotly-Dash-based Query Infrastructure for the Keck Observatory Archive

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 expanded. In response, KOA has implemented a new Python-based, VO-compliant query infrastructure. This work is a continuation of the architectural design and technology selection identified at ADASS 2024. We have deployed real-time ingestion of newly acquired data and a dedicated interface for observers to manage these data. Our ADASS 2024 poster identified the new technologies chosen: Plotly-Dash, a low-code framework that exploits event-driven callbacks to simplify the handling of user interactions; R-tree spatial indexing to speed up spatial searches by x20; a VO-compliant TAP middleware, already in use at the NASA Exoplanet Archive and NEID archive; and mViewer, a visualization engine in the Montage Image Mosaic toolkit that is optimized for astronomy images. These technologies will underpin new services that can be hosted on web pages or in Jupyter notebooks, and when completed, will replace the current query infrastructure. We have completed two new services now in beta release. The first is the Data Discovery Service, a web-based dashboard that returns spatial and temporal queries of the entire archive in seconds. It supports filtering observations by keywords, previewing results in an interactive data grid, and visualizing images, and it offers data downloads. The second is a Jupyter notebook that performs interactive visualization of Keck observations of protostars in the Rho Oph Dark Cloud and uses data from CDS and IRSA, as well as KOA.

astro-ph.IM↗

arXiv2025

The NASA Exoplanet Archive and Exoplanet Follow-up Observing Program: Data, Tools, and Usage

The NASA Exoplanet Archive and the Exoplanet Follow-up Observing Program service are two widely used resources for the exoplanet community. The NASA Exoplanet Archive provides a complete and accurate accounting of exoplanetary systems published by NASA missions and by the community in the refereed literature. In anticipation of continued exponential growth in the number of exoplanetary systems, and the increasing complexity in our characterization of these systems, the NASA Exoplanet Archive has restructured its primary tables and interfaces, as well as extending and standardizing their modes of access. The Exoplanet Follow-up Observing Program service provides the exoplanet community with a venue for coordinating and sharing follow-up and precursor data for exoplanets, their host stars, and stars that might eventually be targets for future planet searches, and recently reached one million files uploaded by the community. In this paper we describe the updates to our data holdings, functionality, accessibility, and tools, as well as future priorities for these two services.

astro-ph.EP↗

arXiv2024

New Python-based Architecture for the Keck Observatory Archive

We describe the development of the Keck Observatory Archive (KOA) Data Discovery Service, a web-based dashboard that returns metadata for wide-area queries of the entire archive in seconds. Currently in beta, this dashboard will support exploration, visualization, and data access across multiple instruments. This effort is underpinned by an open-source, VO-compliant query infrastructure and will offer services that can be hosted on web pages or in Jupyter notebooks. The effort also informs the design of a new, modern landing page that meets the expectations of accessibility and ease of use. The new query infrastructure is based on nexsciTAP, a component-based, DBMS-agnostic Python implementation of the IVOA Table Access Protocol, developed at NExScI and integrated into the NASA Exoplanet Archive and the NEID Archive, and into the PyKOA Python client. This infrastructure incorporates R-tree spatial indexing, built as memory-mapped files as part of Montage, a software toolkit used to create composite astronomical images. Although R-trees are used most often in geospatial analysis, here they enable searches of the entire KOA archive, an eclectic collection of 100 million records of imaging and spectroscopic data, in 2 seconds, and they speed up spatial searches by x20. The front end is built on the open-source Plotly-Dash framework, which allows users to build an interactive user interface based on a single Python file.

astro-ph.IM↗