According to Tim Berners-Lee, inventor of the world wide web and the semantic web, he defines the semantic web as “a web of datas that can be processed directly and indirectly by machines”. Presently, data is stored in silos. The current web is often defined as the web 2.0 version.
The Semantic Web is the 3.0 version, where data is linked in the cloud as connected points on a massive global graph. This graph allows computers to read it, understand it, infer meaning and produce an answer to whatever the searcher is looking for. The value of data on the web increases when they are connected to other data sources and since the Semantic Web is in a machine readable language, this helps computers to understand more information on the Web so that they can support richer discovery, data integration, navigation, and automation of tasks.
When you need to find information today about any artist or film in Africa, you will be required to go to multiple websites to get all the information you seek, but that’s the problem. The solution is to aggregate these multiple data sources, unify them and build profiles, building a giant graph of film entities (Actors, Directors, Films, Genres, etc.) and then provide additional services (such as search and recommendations) on top of this aggregated data using semantic web technologies.
Semantic Web technology also provides new ways to explore the cultural universe of actors and directors, and lets them discover other connected ones, based on a rich set of connections that can exist. This will offer an enriched online discovery user-experience via browsing actors, film titles or directors, or by combining these features together to find new ones.
For instance, when you enter an actor’s name, it will serve up biographical information, films, and other related entities.
You can also enter multiple search terms and search in combination. For instance, “Show me all the films directed byOusmane Sembene in Senegal”.
Mokolo will become an answer engine for user’s enquiries on movies or movie related things. Structured data increases trust for the provider organization like Mokolo on the web which helps validate content by search engines. Mokolo’s data can be leveraged by all sorts including movie recommendation apps, movie prediction apps, intelligent organizers, Big Data for movie analysis researchers, etc.
Taken from the interview with Emeka Okoye. Read here