Ciao is a complete Prolog system subsuming ISO-Prolog with a novel modular design which allows both restricting and extending the language. Ciao extensions currently include feature terms (records), higher-order, functions, constraints, objects, persistent predicates, a good base for distributed execution (agents), and concurrency. Libraries also support WWW programming, sockets, and external interfaces (C, Java, TCL/Tk, relational databases, etc.). An Emacs-based environment, a stand-alone compiler, and a toplevel shell are also provided.
GRASS (the Geographic Resources Analysis Support System) is a software raster- and vector-based GIS (Geographic Information System), image processing system, graphics production system, and spatial modeling system. It contains many modules for raster data manipulation, vector data manipulation, rendering images on the monitor or paper, multispectral image geocoding and processing, point data management and general data management. It also has tools for interfacing with digitizers, scanners, and the PostgreSQL, DBF, and ODBC connected databases. GRASS operates on all common operating systems.
imaverage uses the viewing frequency and viewing time from a spawned image viewer to build a dynamic database entry for images to gauge their relative preference for a given user. Once the entries have been created, imaverage will continue to show images randomly, with dynamic preference weights. On average, your favorite images should show up most frequently.
JReferences is a program written in Java for managing bibliographic references in the BibTeXML format. Storage is done in a binary file database or, optionally, in a MySQL database. A PHP Web frontend is available. It can input BibTex, RIS, BibTeXML, and DocBook formated references.
Moodss is a modular monitoring application, which supports operating systems (Linux, UNIX, Windows, etc.), databases (MySQL, Oracle, PostgreSQL, DB2, ODBC, etc.), networking (SNMP, Apache, etc.), and any device or process for which a module can be developed (in Tcl, Python, Perl, Java, and C). An intuitive GUI with full drag'n'drop support allows the construction of dashboards with graphs, pie charts, etc., while the thresholds functionality includes emails and user defined scripts. Monitored data can be archived in a SQL database by both the GUI and the companion daemon, so that complete history over time can be made available from Web pages or common spreadsheet software. It can even be used for future behavior prediction or capacity planning, from the included predictor tool, based on powerful statistical methods and artificial neural networks.
ROOT is an OO framework for large-scale scientific data analysis and data mining. It contains an efficient hierarchical OO database, a C++ interpreter, advanced statistical analysis, visualization, introspection, documentation, networking, and GUI classes. The command/scripting language is C++, and large scripts can be compiled and dynamically linked in. Using the PROOF (Parallel ROOT Facility) extension, large databases can be analyzed in parallel. The system runs on all known POSIX platforms, Windows, and MacOS X.
Sixpack is a graphical and command-line bibliography database manager written in Perl/Tk. It interacts with the supplied package 'bp', which can import and export from a number of formats including bibtex, endnote, medline, procite, and many others. It can download references directly off the Web, and open articles using external viewers. It can also interface with Emacs/XEmacs and Lyx.
ToutDoux is a project manager for GNOME. The approach of data manipulation is abstract (database free). It's extensible with plugins. Most tasks are and will be subcontracted with commandline frontends. The file format is XML (including a schema, plugins parameters, and datatables).
Weka is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka is also well-suited for developing new machine learning schemes. The development version contains a GUI with visualization tools and direct database access.