Keynote on SlideWiki at SMWCon Fall 2017 – the 14th Semantic MediaWiki Conference
Semantic MediaWiki (SMW) is a free, open-source extension to MediaWiki – the wiki software that powers Wikipedia – that lets you store and query data within the wiki’s pages.
Similar to MediaWiki, and its popular instance WikiPedia, SlideWiki aims to be a wiki for educational material. During the Keynote we presented the origin, context, and goals of the SlideWiki project.
We discussed the weaknesses of existing OpenCourseWare and MOOC Initiatives following a systematic analysis of courses from OpenCourseWare repositories. We highlighted the position of SlideWiki among other collaborative authoring platforms, such as the successful Wikipedia (a MediaWiki), GitHub, and OpenStreetMaps.
An overview was given of the current and planned state of development of the new SlideWiki, including its collaborative authoring environment, social groups and features, translation features, and content revisioning mechanisms. These features play an important role in MediaWiki environments as well, and
We emphasised and demonstrated the semantic functionalities of SlideWiki, as it was highly relevant for the audience of the Semantic MediaWiki conference. For example, the use of tags to describe presentation decks on a meta-level – improving both understanding and searchability of educational material. Another semantic feature discussed was the in-development prototype of in-page annotation of materials in slides. A user of the in-page annotator can select a text phrases and other content to make it explicit as being an instance of a type (class) of knowledge. For example, ” Rubric X” and “syllabus Y” can be classified in a slide as (instances of) different types (classes) of learning materials, and their meaning can be made explicit this way. Similarly “Nucleic acid sequence” can be annotated as a biological concept and further explained in semantic annotations.
Finally we discussed the work on the Natural Language Processing microservice which allows automatic annotation and content recommendation. This SlideWiki microservice processes the textual content of the slides. It tokenizes the text inside slides and retrieves named entities based on classical named entity recognition as well as based on DBPedia Spotlight, where entities from existing knowledge repositories, such as DBpedia (a semantic/linked data version of Wikipedia) are identified in the slides. The tokens and named entities are analysed to see how important they are in the presentation as well as reagrding all slides currently on SlideWiki. Identifying important tokens and named entities allows for semi-automatic in-slide annotation as well as on recommendations for suitable tags. A further application area of these analysis results will be the content recommendation.
We further discussed feature work on semantics in SlideWiki, including RDB2RDF mapping and providing a SPARQL endpoint. Moreover, we provided more general furure development plans SlideWiki, e.g., adoption by users and open source community and interoperability. We invited participants to comment on our plans and use SlideWiki themselves, which provided useful feedback.
The keynote slides are available on SlideWiki and you can view them below.