A communiqué from Jan Algermissen and Sam Hunting announces the public alpha release of an open-source toolkit which implements the Topic Maps Processing Model. The GooseWorks.org Toolkit for Topic Map Information Processing (GWTK) was announced at the XML 2001 Conference in Orlando, Florida. GWTK is a "free, open-source implementation of the Topic Maps Processing Model 1.0.2 (TMPM4), which will inform the topic maps Reference Model under development at ISO SC34. Written in C by Jan Algermissen, the GWTK toolkit takes XML topic maps (and HTML plus Dublin Core documents) and represents them as a TMPM4 graph that can be queried with the sTMQL module, viz., subject-based Topic Map Query Language. GWTK complies with the rules for topic map integrity laid down in TMPM4, including the Subject-based Merging rule, the Name-based Merging rule, the 'Node Demander is a Subject Indicator' rule, and three of the four 'No Redundancies' rules. GWTK has a flexible storage strategy adopted at graph creation. The graph can be stored in-memory, or (in future releases) with the Postgres, MySQL, ODBC, or sdbm databases. The toolkit also permits association template validation."

From the online documentation:

"The GooseWorks (GW) Toolkit is an implementation of the 'Topicmaps.net's Processing Model for XTM' by Steven R. Newcomb and Michel Biezunski, referred to as PMTM4. It is a toolkit that provides the major building blocks to assemble topic map applications of various kinds such as command line tools, CGI applications, web browser plug-ins, and large-scale editing and processing applications. It is written in C and thus can be easily used as an extension to common scripting languages such as Python, Ruby, or Perl. Currently a Python extension module is included in the distribution.

The GW toolkit currently consists of the following parts: (1) A Processor capable of parsing various document types that contain topic map information; (2) A Python extension to use the processor in a scripting environment; (3) A topic map graph implementation with in memory storage of all data. This can be used for validation of or quick inquiry into a topic map; (4) A prototype implementation of a topic map graph in Python to be used with the Python extension. This prototype also implements a sketch for a subject based topic map query language (sTMQL); (5) Some tools and examples to get started with and to explore topic maps.