Search Results for "data analysis and visualizing"

Turf is a JavaScript library for spatial analysis. It includes traditional spatial operations, helper functions for creating GeoJSON data, and data classification and statistics tools. Turf can be added to your website as a client-side plugin, or you can run Turf server-side with Node.js. Modular, simple-to-understand JavaScript functions that speak GeoJSON. Turf is a collection of small modules, you only need to take what you want to use.

An innovative Open Source CEP (Complex Event Processing) engine. It implements the event stream processing as a library embeddable in C++ and Perl. You can think of the Complex Event Processing engine as an in-memory database driven by triggers, or a data-flow machine, or a spreadsheet on steroids (and without the GUI part).

ODABA is an terminology-oriented database management system (TODBMS) on a high conceptual level. It provides a number of enhanced features based on natural language analysis. Terminology orientation allows designing user oriented data models. Enhanced event model and Active Data Link technology support rapid development of GUI applications. Several development, documentation, test and analyzing tools are provided in order to support developers and administrators. .NET interface and a powerful object-orjented script language (OSI) improve development efficiency.

The Lemur Project develops search engines, browser toolbars, text analysis tools, and data resources that support research and development of information retrieval and text mining software, including the Indri search engine in C++, the Galago search engine research framework in Java, the RankLib learning to rank library, ClueWeb09 and ClueWeb12 datasets and the Sifaka data mining application.

representation by relations vs data storage. pile unifies the contradicted qualities of tables/trees (databases) and complex networks, order and flexibility. dynamical data generation on call. fast. natively compressing similarities. search across scopes.

An experimental CEP (Complex Event Processing) engine. It implements the event stream processing as a library embeddable in C++ and Perl. Since then it has been renamed to Triceps, so please look at the new location https://sourceforge.net/projects/t

XAIRA (XML Aware Indexing and Retrieval Architecture) supports indexing and analysis of large XML textual resources such as natural language corpora.

Neurospaces is a development center for tools in computational neuroscience. See http://www.neurospaces.org/

A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining

FLAG was designed to simplify the process of log file analysis and forensic investigations. FLAG facilitates efficient analysis of large quantities of data within an interactive environment. PyFlag is the reimplementation of FLAG in Python.

IDSS is a statistical application for e-mail surveys. It parses HTML questionnaires filled in by respondents. Output is a separated database, a SAS DATA step import program and correspondence tables between variable characteristics and field values.

KML is a knowledge base with support of logical modeling. Advanced model is used to represent knowledge as a set of statements similar to natural language sentences. This project hosts a set of model storage library and server (vrb-ols) and clients.

A set of software components used to investigate and implement searching of music and audio. This covers content-based retrieval and meta-data based solutions, segmentation and content selection (summarisation) of audio and music (MIDI, MP3 and WAV).

Project MOVED to Codehaus New location is http://esper.codehaus.org The Esper project aims to provide a general-purpose event processing facility in Java for complex event processing of real-time, high throughput data streams.

...Therefore, the complex analysis (Expert system analysis in accordance with world-wide data) has to be done on server. The environment data is collected via sensors is uploaded to the website