HEBCI is a technique that allows a Web form handler to transparently detect the character set with which its data was encoded. By using carefully-chosen character references, the browser's encoding can be inferred. Thus, it is possible to guarantee that data is in a standard encoding without relying on (often unreliable) Web server/browser encoding interactions.
Historical Event Markup and Linking Project (Heml) provides an XML schema for historical events and a Java Web app which transforms conforming documents into hyperlinked timelines, maps and tables. It aims to provide a most information-rich interchange format for historical data, and thus add a historical component to the growing movement for a 'Semantic Web.'
LuMriX is a search engine that exploits XML and XML Topic Maps. In contrast to other retrieval methods, it does not relate single items to resources, but combines given items into meaningful associations (concepts), which are in turn linked to resources. XML Topic Maps allow an intelligent mapping of relations between terms and pages. The meaning of the query is captured by transverse joint relations between the search items. LuMriX is also able to auto-extend its thesaurus and create new relations between failed search items and information resources. It is completely implemented in Java. It can consist of many individual distributed LuMriX servers, which communicate with each other by distributed algorithms. Standardized interfaces such as TCP, SOAP, HTTP, XML, and XTM allow simple utilization and maintenance by other applications.
MyHeadlines is module that adds syndicated headline functionality to any PHP and MySQL-based website. Your users may subscribe to multiple RSS feeds from a fully categorized database of over 1,000 sources. It was previously a PHPNuke/PostNuke Addon, but can now be integrated with any Web site.
PhiloLogic is a full-text database engine developed for humanities computing text analysis by the ARTFL Project and the Digital Library Development Center at the University of Chicago. It is optimized for fast searching across very large collections of documents. It currently supports TEI-Lite, TEI XML, and TEI SGML documents.