Use py2mappr to render fully interactive networks from simple csv files of node and links. Use tag2network to build a similarity network from a list of nodes with associated tags (e.g. documents with keywords). Nodes can host images, video, Twitter and Instagram feeds, and music streams.
Easily style the appearance of nodes, links, and node labels. Reveal patterns in network structure with scatterplot and geospatial layouts. Save custom views and layouts with seamless animated transitions between them. Share a fully interactive network by publishing openmappr files to any static website.
Code-free data exploration with dynamic filters and search tools to query nodes by any combination of node characteristics. Effortlessly zoom in to node details and zoom out to see them in the broader network context. See summaries of node characteristics - both for the entire network and selected groups of nodes.
You'll have to explore a bit to find the tools' links to Github. It could be better organized.
The A.R.M. (Automatic Ripping Machine) detects the insertion of an optical disc, identifies the type of media, and autonomously performs the appropriate action:
- DVD / Blu-ray -> Rip with MakeMKV and Transcode with Handbrake
- Audio CD -> Rip and Encode to MP3 or FLAC and Tag the files if possible.
- Data Disc -> Make an ISO backup
It runs on Linux, it’s completely headless and fully automatic requiring no interaction or manual input to complete its tasks (other than inserting the disk). Once it completes a rip it ejects the disc for you and you can pop in another one.
A small library for legible console plotting in Python. Uses plain ASCII and some ANSI colors to do it.
A curated list of awesome open source healthcare software, libraries, tools and resources. Each link has been vetted to ensure the project is active and provides value to healthcare facilities, providers, developers, policy experts, and/or research scientists.
Golem is a demonstration of how to distribute content over ActivityPub securely over peer to peer networks.
The problems this demo is trying to address are:
- Nodes go down, and their content tends to go with them. How can we have content that survives? Content which is distributable over a peer to peer network seems like it would help.
- Except if an entire network is helping hold onto and distribute content, how do we keep private content private?
- How to do this in a way that is compatible with the ActivityPub specification?
By encrypting the file and splitting it into chunks distributed through the network and only sharing the decryption key with the intended recipient, and by using a URI scheme that captures the appropriate information, we can accomplish all the above. Golem uses the magenc extension of the magnet URI scheme to accomplish the above.
A standard for transferring Files between airgapped units over a simplex transmission agnostic to the medium, transfer speed and distribution network. Most existing Protocols don't handle simplex transmissions at all or very poorly.
The data to be tansmitted is to be collected in a container [this may be a folder or tar archive]. The container is then optionally compressed and encrypted. The container is hashed (SHA3-512 is recommended). A header is used to communicate the essential parameters, including compression algorithm, encryption used, checksum, container size and number of fragments, timestamp, and checksum of the header.
Documentation aside, proof of concept of each feature is part of the repo in the form of shell scripts.
The National UFO Historical Records Center is a 501(c)(3) Nonprofit Corporation in the state of New Mexico that seeks to educate the public on the history of the UFO/UAP phenomenon, preserve and digitize historical documents and media, and promote scientific research into the topic. We are an organization of leading researchers and archivists who together hold the largest collection of historical UFO records in the United States of America. We intend to bring all these collections together under one roof to preserve this important piece of history for future generations. There is no central place for the public to get the true story of UFOs and we endeavor to provide clarity to current developments and past events through the lens of historical records and data.
The NOAA runs this project.
The State Climate Summaries provided here were initially produced to meet the demand for state-level climate information in the wake of the Third U.S. National Climate Assessment. This 2022 version provides new information and extends the historical climate record to 2020 for each state. The summaries cover assessment topics directly related to NOAA’s mission, specifically historical climate variations and trends, future climate model projections of climate conditions during the 21st century, and past and future conditions of sea level and coastal flooding. Additional background information and links are given below.
MEALPY is the largest python library in the world for most of the cutting-edge meta-heuristic algorithms (nature-inspired algorithms, black-box optimization, global search optimizers, iterative learning algorithms, continuous optimization, derivative free optimization, gradient free optimization, zeroth order optimization, stochastic search optimization, random search optimization). These algorithms belong to population-based algorithms (PMA), which are the most popular algorithms in the field of approximate optimization.
A generic automation tool around data stored as plaintext YAML files. This program uses YAML files to store data about various kind of items (bookmarks, software projects, ...) and apply various processing tasks. Functionality is implemented in separate modules.
One of the things namechecked is use with Shaarli.
sjvisualizer is a data visualization and animation library for Python for time-series data.
Tries to be easy to use. Give it a file of data (the examples given are .xlsx files, can probably use others) and it seems to know what to do if it thinks it's time-series data.
Has an actual website with more detailed and elaborate examples, including background information: https://www.sjdataviz.com/software
This library provides several functions for nicely printing data to the terminal. MatPlotLib is a very nice library, but it can be a bit tedious at times when all you want is something quick and dirty.
By default, this library will use Unicode symbols (specifically braille) for plotting. A good font to use is JuliaMono. However, if your font does not support the necessary Unicode symbols, you can tell the library to not use them by setting itrm.config.uni to False.
Find out who’s behind more than 810,000 offshore companies, foundations and trusts from the Pandora Papers, Paradise Papers, Bahamas Leaks, Panama Papers and Offshore Leaks investigations.
Did you ever wonder how QR codes work? You've come to the right place! This is an interactive explanation that we've written for a workshop at 37C3, but you can also use it on your own. You will learn the anatomy of QR codes and how to decode QR codes by hand.
Source code: https://codeberg.org/Piko/qr-explainer
Welcome to Vimm's Lair! This site is dedicated to nostalgia for many of the greatest game consoles ever made. Inside you'll find thousands of games, full-color manual scans, user ratings and reviews, and much more! Whether you're looking for some videogame nostalgia or just curious, you're sure to find everything you need!
The USDA Plant Hardiness Zone Map is the standard by which gardeners and growers can determine which perennial plants are most likely to thrive at a location. The map is based on the average annual extreme minimum winter temperature, displayed as 10-degree F zones and 5-degree F half zones. A broadband internet connection is recommended for the interactive GIS-based map above.
To find the Plant Hardiness Zone at your location quickly, enter your zip code in the Quick Zip Code Search box in the map above, or click anywhere on the map to view the corresponding interactive map.
This repository contains Open Source freely usable Threat Intel feeds that can be used without additional requirements. The file ThreatIntelFeeds.csv is stored in a structured manner based on the Vendor, Description, Category and the URL. The vendors offering ThreatIntelFeeds are described below. The following feed categories are available:
COVID-19 continues to kill and injure many people daily. With the collapse in case data reporting it has become difficult to show that high-risk events such as large meetings, performances, and other events result in quantifiable harms.
This web app allows you to create a sharable event link for attendees to report their symptoms and test status anonymously. The public event page will then display how many attendees have become sick or tested positive in an easy-to-digest form along with expected impact (e.g. how many might be expected to get Long COVID). These statistics can be used to help you advocate for increased COVID-19 mitigations in your workplace or other groups.
It may be difficult to get people to disclose their status publicly with their name attached to colleagues (it's embarassing and everyone is trying to ignore COVID), but it is much easier for an activist to drop a link and aggregate anonymous statistics since there is less chance of blowback for such disclosures for the individuals and they'll feel like they're contributing to public health and workplace safety.
For the organizer or activist, information is power. Statistics are able to show the real harms that are occuring and can be used to advocate for safe events and workplaces. It also gives your fellow attendees a way to help each other in a clear and structured way that the Federal government should be providing, but isn't.
Plots the vertical atmospheric structure as plots between altitude and temperaturem and altitude vs. wind speed using aircraft data collected from the dump1090-fa ADSB decoder. The calculations are similar to those used in the tar1090 package. Reads the JSON data from dump1090-fa/history_xx.json files.