Open Source Java Data Analytics Tools

DataMelt (or "DMelt") is an environment for numeric computation, data analysis, computational statistics, and data visualization. This Java multiplatform program is integrated with several scripting languages such as Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using powerful Java API. Elements of symbolic computations using Octave/Matlab scripting are supported.

PMM-Lab is an open-source extension to the Konstanz Information Miner (KNIME). It consists of three components: • a library of KNIME nodes (called PMM-Lab), • a library of “standard” workflows • an HSQL database.to store experimental data and microbial models. Altogether these components are designed to ease and standardize the statistical analysis of experimental microbial data and the development of predictive microbial models (PMM). Users can apply PMM-Lab to proprietary or public data and create bacterial growth / survival / inactivation models. The framework can easily be extended to other model types, e.g. growth/no-growth boundary models. PMM-Lab has been initiated and provided by the Federal Institute for Risk Assessment - BfR (Berlin, Germany). The software is in Beta status. Before using the software you have to read and accept the license and disclaimer (https://sourceforge.net/p/pmmlab/wiki/Disclaimer/). If you do not agree, do not use this software.

KeplerDB is a temporal database to store time/value entries where the type of value could be integer, float/double, boolean and string. KeplerDB is dedicated to be scalable and to create clusters of server allowing the user to analyse and store massing amount of data to monitor systems like computers, clusters, building and captors or financial systems like markets and accounts. The user can use KeplerDB to make data analysis on enormous amount of data (statistics and modelling).

Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming

A shell for using the methods of Contextual Logic to do qualitative data analysis, mathematical research on the theory underlying Conceptual Knowledge Processing, or learning Formal Concept Analysis. It uses the framework provided by the Tockit project..

This Java software includes algorithms of combinatorical optimization for the NP-hard offline ship lock scheduling problem. Solutions and performed computations can be displayed graphically. Besides, there is a framework for generating test instances and running these in parallel, as well as R/JGR code for statistical evaluation. Some tools for estimating the quality of calculated solutions will be further improved. Initially the software was developed within a project of TU Berlin regarding the Kiel Canal. See project wiki for conditions that should be met by applications.

TOPS provides the benchtop scientist with a free toolset to analyze, filter and visualize data from functional genomic gene-gene and gene-drug interaction screens with a flexible interface to accommodate various different technologies and analysis algorithms in addition to those already provided here.

jHepWork (2005-2013) was an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with the Jython (Python) scripting language. Currently the project is known under the name DataMelt (https://datamelt.org)

Java OpenCL Process Virtual Machine. Spring IoC based framework for complex data analysis with OpenCL computing.