As part of the Semantic Assistants project, we developed the idea of a "self-aware" wiki system that can develop and organize its own content using state-of-art techniques from the Natural Language Processing (NLP) and Semantic Computing domains. This is achieved with our open source Wiki-NLP integration, a Semantic Assistants add-on that allows to incorporate NLP services into the MediaWiki environment, thereby enabling wiki users to benefit from modern text mining techniques.

Here, we want to exhibit how a seamless integration of NLP techniques into wiki systems helps to increase their acceptability and usability as a powerful, yet easy-to-use collaborative platform. We hope this will help you to identify new human-computer interaction patterns for other scenarios, allowing you to make the best possible use of this new technology.

Semantic Assistants for wikis are our novel architecture for the integration of Natural Language Processing (NLP) capabilities into wiki systems, based on the Semantic Assistants framework. The vision is that of a new generation of wikis that can help developing their own primary content and organize their structure by using state-of-the-art technologies from the NLP and Semantic Computing domains. The motivation for this integration is to enable wiki users – novice or expert – to benefit from modern text mining techniques directly within their wiki environment.

Researchers need to extract and manage critical knowledge from the massive amount of literature available in multiple and ever-growing repositories. The sheer volume of information makes the exhaustive analysis of literature a labor-intensive and time-consuming task, during which significant knowledge can be easily missed. We present IntelliGenWiki, a service-oriented solution that combines state-of-the-art techniques from the Natural Language Processing (NLP) and Semantic Web domains to support the knowledge discovery workflow in omics sciences.

ReqWiki is a novel open source web-based approach for software requirements engineering. It is based on a semantic wiki that includes natural language processing (NLP) assistants, which work collaboratively with humans on the requirements specification documents. It is the first Requirements Engineering tool that combines wiki technology for collaborative use and semantic knowledge representation for formal queries and reasoning with natural language processing assistants within a single, cohesive interface.

Springer just published a new book, Language Technology for Cultural Heritage, where we also contributed a chapter: "Integrating Wiki Systems, Natural Language Processing, and Semantic Technologies for Cultural Heritage Data Management". The book collects selected, extended papers from several years of the LaTeCH workshop series, where we presented our work on the Durm Project back in 2008.

In this project, which ran from 2004–2006, we analysed the historic Encyclopedia of Architecture, which was written in German between 1880-1943. It was one of the largest projects aiming at conserving all architectural knowledge available at that time. Today, its vast amount of content is mostly lost: few complete sets are available and its complex structure does not lend itself easily to contemporary application. We were able to track down one of the rare complete sets in the Karlsruhe University's library, where it fills several meters of shelves in the archives. The goal, then, was to apply "modern" (as of 2005) semantic technologies to make these heritage documents accessible again by transforming them into a semantic knowledge base (due to funding limitations, we only worked with one book in this project, but the system was developed to be able to eventually cover the complete set). Using techniques from Natural Language Processing and Semantic Computing, we automatically populate an ontology that can be used for various application scenarios: Building historians can use it to navigate and query the encyclopedia, while architects can directly integrate it into contemporary construction tools. Additionally, we made all content accessible through a user-friendly Wiki interface, which combines original text with NLP-derived metadata and adds annotation capabilities for collaborative use (note that not all features are enabled in the public demo version).

All data created in the project (scanned book images, generated corpora, etc.) is publicly available under open content licenses. We also still maintain a number of open source tools that were originally developed for this project, such as the Durm German Lemmatizer. A new version of our Wiki/NLP integration, which will allow everyone to easily set up a similar system, is currently under development and will be available early 2012.