Open Source JavaScript Data Management Systems - Page 4

The project would include the development of XUL, CSS and Javascript components to assist biologists in sequence manipulations, data mining, data analysis, etc.).

The purpose of the project is to develop a quantitative medical imaging & visualization program for use on brain MR, DTI and MRS data. It is a joint project of the Kennedy Krieger Institute & the Johns Hopkins University, Psychiatric Neuroimaging Lab

Book-A-Lyze is an open source web application for analysis and visualization of social structures at Facebook. The project is part of the study course “Media Management and Production” at the University of Applied Sciences, Kaiserslautern.

Use Pentaho open source business intelligence tools and MySQL to collect & distribute web analytics (clickstream) data. Extract data from logs, load database tables, & present the information in dashboards, analysis cubes, and reports for business users. This project has been moved to github - https://github.com/cjlavigne/breadboard

In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own learnable weights and biases. Let’s break down a CNN into its basic building blocks. A tensor can be thought of as an n-dimensional matrix. In the CNN above, tensors will be 3-dimensional with the exception of the output layer. A neuron can be thought of as a function that takes in multiple inputs and yields a single output. The outputs of neurons are represented above as the red → blue activation maps.

Goal of our project CSX (City Stats X) is to program a generic interface to visualize and present social data about a city. We will present this on the example of the city of Linz in Austria.

Camp information management system, including event registration, lodging, donor giving, mailings, rental management, and more.

This is a short C++/Java/C#/Python benchmark. Based on Paul Heckbert's sources. Thank you Paul!

Chokidar is a solution for all the users of Node.js fs.watch who are tired of it not reporting filenames on MacOS and events at all when using editors like Sublime on MacOS. Node.js fs.watch often reports events twice, emits most changes as rename, and it does not provide an easy way to recursively watch file trees nor supports recursive watching on Linux. Same as with Node.js fs.watchFile. Therefore, Chokidar resolves these problems. Initially made for Brunch (an ultra-swift web app build tool), it is now used in Microsoft's Visual Studio Code, gulp, karma, PM2, browserify, webpack, BrowserSync, and many others. It has proven itself in production environments. Chokidar does still rely on the Node.js core fs module, but when using fs.watch and fs.watchFile for watching, it normalizes the events it receives, often checking for truth by getting file stats and/or dir contents.

Cleaver is a one-stop-shop for generating HTML presentations in record time. Using some spiced up markdown, you can produce good-looking, interactive presentations with a just a few lines of text. Cleaver supports several basic options that allow you to further customize the look and feel of your presentation, including author info, stylesheets, and custom templates. Cleaver has substantial theme support to give you more fine-grained control over your presentation, similar to options. Instead of manually specifying a stylesheet, template, layout, and others, you can specify a single theme containing each of these assets. Cleaver comes with a stylesheet that looks good by default, but you can extend it at your heart's desire. Themes are prepackaged options you can invoke from a directory, URL, or even a GitHub repository.

Clustergrammer is a visualization library built using D3.js that enables intuitive interaction with high-dimensional data. Clustergrammer was built with biological data in mind. Clustergrammer is a web-based tool for visualizing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap. Clustergrammer's front end (Clustergrammer-JS) is built using D3.js and its back-end (Clustergrammer-PY) is built using Python. Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several biology-specific features (e.g. enrichment analysis, see Biology-Specific Features) to facilitate the exploration of gene-level biological data.

CollectD-CSV Plotter is a web interface for fetching and visualizing data that is saved in CollectD CSV format. An HTML form is used for defining the time interval and choosing the wanted measurements. The plotter is actually a front-end for collectd-csv module (http://pypi.python.org/pypi/collectd-csv/), which it uses for fetching the data. Technologies CollectD-CSV Plotter uses include CGI/Python, HTML5/JavaScript, jQuery, jQuery-UI and Gnuplot.

A toolkit for processing and visualising sensor data in real time with support for use with embedded platforms.

Compiere MFG+SCM Manufacturing Extended System (MES). Include Shop Floor Control, Supply chain management, Quality management, modbus interface, iReport barcode extension etc. Support batch and on demand manufacturing. Works alone or connected to ERP.

CoreMan (Correspondence Management System) is a web-based document and correspondence management system that enables companies and organizations to develop an easily accessible digital document and correspondence archive that can be efficiently managed.

CrimeStat is an web-application which analyses the police's press releases of Berlin and visualizes the different criminal offences on a map of Berlin. It also shows different statistics about the crimes.

The application Crimeblips provides up-to-date crime statistics for Berlin (Germany). It maps and visualizes crimes, allowing users to identify crime hot spots, trends and general patterns. Bayesian algorithms are used to extract relevant information.

Cscape is an application for visualizing and navigating through data from a Reverse Phase Protein Microarray (RPMA). Cscape uses the Google Maps API to map the RPMA data on top of an image of a cancer cell and its associated pathways.

With CueLake, you can use SQL to build ELT (Extract, Load, Transform) pipelines on a data lakehouse. You write Spark SQL statements in Zeppelin notebooks. You then schedule these notebooks using workflows (DAGs). To extract and load incremental data, you write simple select statements. CueLake executes these statements against your databases and then merges incremental data into your data lakehouse (powered by Apache Iceberg). To transform data, you write SQL statements to create views and tables in your data lakehouse. CueLake uses Celery as the executor and celery-beat as the scheduler. Celery jobs trigger Zeppelin notebooks. Zeppelin auto-starts and stops the Spark cluster for every scheduled run of notebooks.

DRINKS Toolkit is a collection of web-based widget, focused in the first release, to realize an online strumentation. It provides a practical and immediate interface to represent your data in the best possible way. Every widget is drawed using HTML5 Canvas API in a Javascript based environment. Drinks was born to allow users to easily realize custom dashboards without any programming knowledge, infact, you can use your instrument on a webpage simply using HTML tags, or using BarMan IDE to create your applications in a click. DRINKS Toolkit (hardware and software) are released as Open Source project.

The Data Science Specialization Courses repository is a collection of materials that support the Johns Hopkins University Data Science Specialization on Coursera. It contains the source code and resources used throughout the specialization’s courses, covering a broad range of data science concepts and techniques. The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow.

The goal of the Data Quality Dashboard (DQD) project is to design and develop an open-source tool to expose and evaluate observational data quality. This package will run a series of data quality checks against an OMOP CDM instance (currently supports v5.4, v5.3 and v5.2). It systematically runs the checks, evaluates the checks against some pre-specified threshold, and then communicates what was done in a transparent and easily understandable way. The quality checks were organized according to the Kahn Framework1 which uses a system of categories and contexts that represent strategies for assessing data quality. Using this framework, the Data Quality Dashboard takes a systematic-based approach to running data quality checks. Instead of writing thousands of individual checks, we use “data quality check types”. These “check types” are more general, parameterized data quality checks into which OMOP tables, fields, and concepts can be substituted to represent a singular data quality idea.

DataSync Suite is an open source platform for integrating tools like Zimbra, SugarCRM, and Drupal. The tool is focused on a single sign-on, application data integration, and fast, flexible deployment.

This package provides Julia integration for the Voyager data exploration tool. DataVoyager.jl can be used for data exploration. It can help you visualize and understand any data that is in a tabular format.

DeciGen is an ERP with added features for help in decision making process. DeciGen incorporates Decision Support System over an framework of ERP to provide a feature rich solution. It aims to achieve the final goal of IT - to run business smoothly. Dec