OXI is a graphical tool for labeling time series data. Labeling is typically used to record interesting or anomalous points in time series data. For example, if you had temperature data from a sensor mounted in the satellite, you could label points that constitute unexpected temperature drops. You can upload multiple series and apply one or many labels. In the GIF below, series_a
is being labeled with a bar
label while series_b
is serving as a reference.
This tool is based on the open-source TRAINSET (commit cb6fcb4) application by Geocene Inc. However, we significantly improved it in terms of performance and added a bunch of features for working with long multi-channel time series (such as satellite telemetry). All the changes relative to TRAINSET can be inspected in this commit.
Our publicly hosted version is accessible under https://oxi.kplabs.pl/
# install dependencies
npm install
# serve with hot reload at localhost:8080
npm run dev
# build for production with minification
npm run build
# testing script for serving prod build locally
npm run start
This tool was designed by KP Labs . KP Labs is a company that develops advanced solutions such as processing units (DPU, OBC with DPU), machine learning algorithms and software for edge processing on Smallsats. Its key domain is earth observation with a focus on hyperspectral data processing. The company was set up in 2016, with its headquarters in Poland. At the moment, the team of over 70 people develops products and projects for ESA, NASA and CSA. KP Labs also has its own product line called Smart Mission Ecosystem. For mission integrators and operators who need to build advanced spacecraft, the Smart Mission Ecosystem brings together the necessary hardware, software, and AI-powered algorithms for in-orbit data processing.
The detailed description of OXI is published in the SoftwareX journal: https://doi.org/10.1016/j.softx.2023.101476
Please use the following Bibtex entry to cite OXI.
@article{ruszczak_oxi_2023,
title = {{OXI}: {An} online tool for visualization and annotation of satellite time series data},
volume = {23},
issn = {2352-7110},
doi = {10.1016/j.softx.2023.101476},
journal = {SoftwareX},
author = {Ruszczak, Bogdan and Kotowski, Krzysztof and Andrzejewski, Jacek and Haskamp, Christoph and Nalepa, Jakub},
month = jul,
year = {2023},
note = {Publisher: Elsevier}
}