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Top 20 open-science Open-Source Projects
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hugo-blox-builder
😍 EASILY BUILD THE WEBSITE YOU WANT - NO CODE, JUST MARKDOWN BLOCKS! 使用块轻松创建任何类型的网站 - 无需代码。 一个应用程序，没有依赖项，没有 JS
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pyvista
3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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ITK
Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.
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awesome-open-geoscience
Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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Anahita
Anahita is a platform and framework for developing open science and knowledge sharing applications on a social networking foundation.
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avogadrolibs
Avogadro libraries provide 3D rendering, visualization, analysis and data processing useful in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas.
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tomviz
Cross platform, open source application for the processing, visualization, and analysis of 3D tomography data
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pycbc
Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.
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itk-wasm
High performance spatial analysis in a web browser, Node.js, and across programming languages and hardware architectures
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peerreview
A diamond open access (free to access, free to publish), open source scientific and academic publishing platform.
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Awesome-Historic_al-Maps
Historic(al) Maps: Meta guidance, tools, repositories, databases, search engines, and online resources for the exploration of Historic and Historical Maps.
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chromatographR
Toolset for the reproducible analysis of chromatography data in R (HPLC-DAD/UV, GC-FID).
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guide
The citizen science guide is designed to be a practical and compact gateway publication for the purpose of assisting research libraries to start setting up a citizen science programme. #cs4rl (by cs4rl)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
https://grass.osgeo.org/
GRASS GIS offers powerful raster, vector, and geospatial processing engines in a single integrated software suite. It includes tools for terrain and ecosystem modeling, hydrology, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It comes with a temporal framework for advanced time series processing and a Python API for rapid geospatial programming. GRASS GIS has been optimized for performance and large geospatial data analysis.
Project mention: Observable 2.0, a static site generator for data apps | news.ycombinator.com | 2024-02-15I think the idea of Framework is really good, but static data limits the applications, excluding monitoring and other cases in which the data is constantly changing, but the dashboard can stay as it is. For example, I'd love to see a revamped Framework version of the LHC beam monitor and related pages (see https://op-webtools.web.cern.ch/vistar/, but check again in 2 months or so, when the accelerator will be running).
In high-energy physics, ROOT is /the/ toolkit for data analysis, and I guess jsROOT (https://root.cern.ch/js/) could also be used to load data to be shown in Framework dashboards. I thought the idea of Framework as a blogging engine with powerful data visualization built-in could be very interesting. Think, for example, about physicists pulling open data (https://opendata.cern.ch) and writing about their analysis or someone pulling data from https://ourworldindata.org/ in their own visualizations to support their case while writing about a particular subject, etc.
Project mention: Loading a trillion rows of weather data into TimescaleDB | news.ycombinator.com | 2024-04-16Why?
Most weather and climate datasets - including ERA5 - are highly structured on regular latitude-longitude grids. Even if you were solely doing timeseries analyses for specific locations plucked from this grid, the strength of this sort of dataset is its intrinsic spatiotemporal structure and context, and it makes very little sense to completely destroy the dataset's structure unless you were solely and exclusively to extract point timeseries. And even then, you'd probably want to decimate the data pretty dramatically, since there is very little use case for, say, a point timeseries of surface temperature in the middle of the ocean!
The vast majority of research and operational applications of datasets like ERA5 are probably better suited by leveraging cloud-optimized replicas of the original dataset, such as ARCO-ERA5 published on the Google Public Datasets program [1]. These versions of the dataset preserve the original structure, and chunk it in ways that are amenable to massively parallel access via cloud storage. In almost any case I've encountered in my career, a generically chunked Zarr-based archive of a dataset like this will be more than performant enough for the majority of use cases that one might care about.
[1]: https://cloud.google.com/storage/docs/public-datasets/era5
Project mention: Request for Feedback: An open-source, open-access, community governed academic publishing platform that crowdsources review using reputation | /r/AskAcademia | 2023-06-28Hey everyone, I'm an experienced software engineer from an academic family. I've been aware of the problems in academic publishing for most of my life, and for the last several years I've been running headlong into the paywalls as I work on municipal policy advocacy. I've been pondering software solutions to this problem for a long time. This is exactly the sort of problem internet based software is, in theory, best suited to solving: sharing and discussing information. It should be possible to build a web platform that allows academia to share work, collect feedback, organize review that maintains quality, and find relevant papers with out relying on private, for-profit journal publishers. It should be possible to build and run a web platform that handles all of academic publishing for 1% of the current cost of for-profit publishing or less - which would (in theory) allow the universities to keep it funded while allowing it to be free to publish and free to access. Hell, it could probably be run lean enough that individual academics could fund it through small dollar donations. There's really no good reason to allow the private publishers to charge academia $11 billion a year while keeping 80% of the work locked behind paywalls. I've had several ideas for how to approach the problem, and I spent the last year building out a beta of one of them as a side project. Software development is experimental and iterative. It only works when the developers are able to get active feedback from the people most effected by the problems they are trying to solve. So I'm reaching out for feedback on the beta, and on possible paths forward. The web platform that I've built enables crowdsourced peer review of academic papers. It uses a reputation system (similar to StackExchange) and ties reputation to a field/concept tagging system. Submitted papers must be tagged with 1 - n fields, and only peers who have passed a reputation threshold in one of the tagged fields may offer review. Review is also split into two phases: pre-publish and post-publish. Pre-publish review is author driven. It's focused on collaborative, constructive feedback and uses an interface heavily inspired by both Github Pull Requests and Google Docs. Post-publish review is much closer to traditional review, and is focused on maintaining the integrity of the literature by filtering out spam, misinformation, fraud, and poorly done work. Reputation is mostly gained and lost through voting that happens during post-publish review. Reputation can also be gained by offering particularly constructive pre-publish reviews. All reviews are open and published alongside the papers. Post-publish review is on-going. That's iteration one. As much as I believe review could be crowdsourced, it seems pretty clear that going straight from what we have to this platform would be a huge leap. So I have ideas for how to build a journal overlay on top of the crowdsourced review system that would allow editors to manage teams of reviewers and run their journals through the platform. This would allow them to take advantage of the review interface, and would still give authors the benefit of being able to have a conversation with their reviewers. Authors would then be able to choose to submit their papers to one or more journals, crowdsourced review, or both. Building that out is the next project. Right now I'm working on this as a side project and an experiment -- could a web platform like this work? Would people even use it? If the answer turns out be yes, I'd love for it to become a non-profit, multi-stakeholder cooperative. Essentially independent public infrastructure similar to Wikipedia, only more transparent and more clearly democratically governed. I would love feedback on all aspects of this project - both the current crowdsourcing iteration and the thought to build a generic, open platform for diamond open access journals to run their operations through. Could you ever see yourself using something like this to publish? What about to collect pre-print review? Could you see yourself reviewing through it? What about submitting to journals through it? Are there other approaches to building a web platform that might work better? Am I barking up the wrong tree? Should I press forward, abandon, or is there a better tree? You can find the beta platform here: https://peer-review.io The source here: https://github.com/danielbingham/peerreview And more details about exactly how it works (in its current iteration) here: https://peer-review.io/about Maintaining an open roadmap here: https://github.com/users/danielBingham/projects/6/views/1
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
open-science related posts
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GraphCast: AI model for faster and more accurate global weather forecasting
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NFS > FUSE: Why We Built Our Own NFS Server in Rust
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Request for Feedback: An open-source, open-access, community governed academic publishing platform that crowdsources review using reputation
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Show HN: Scientific publishing platform to crowdsource review using reputation
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Request for Feedback: Peer Review - Open Source, Open Access Scientific Publishing Platform drawing on Github and StackExchange
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Open-Source Science (OSSci) to launch interest group on reproducible science
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Levels of Open Access · nasa/Transform-to-Open-Science · Discussion #454 · GitHub
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A note from our sponsor - InfluxDB
www.influxdata.com | 5 May 2024
Index
What are some of the best open-source open-science projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | hugo-blox-builder | 7,804 |
| 2 | pyvista | 2,360 |
| 3 | fma | 2,108 |
| 4 | ITK | 1,342 |
| 5 | awesome-open-geoscience | 1,341 |
| 6 | grass | 768 |
| 7 | Transform-to-Open-Science | 660 |
| 8 | opendata.cern.ch | 635 |
| 9 | Anahita | 432 |
| 10 | avogadrolibs | 409 |
| 11 | tomviz | 317 |
| 12 | pycbc | 295 |
| 13 | serratus | 243 |
| 14 | itk-wasm | 179 |
| 15 | arco-era5 | 176 |
| 16 | peerreview | 51 |
| 17 | Awesome-Historic_al-Maps | 51 |
| 18 | chromatographR | 12 |
| 19 | LITOS | 10 |
| 20 | guide | 3 |
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