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The semantic web made simple the semantic web makes for a better programme. and the course – would be almost unmanageable. The engine that enables this linking and association of data is critical to the success. As well as forming the links it has to be able to present it in a way which is readily understood by the typical non-specialist user. There is no point in enabling comprehensive research if learning how to interpret the data is going to take longer than sitting down with an outline script and Google. But all of this information exists, on the websites of the PGA, the tournament, the sponsors and the club. So Metadata Central polls these sources and sets up the logging screens so that when the tournament starts, all the right information is presented to the loggers. It eliminates a huge amount of work. And better core information for the loggers makes for better metadata from the event, which makes the archive more valuable in the future. We have invested a great deal of time and effort into developing this user interface. It is hard to describe it on paper, aside from saying it is really obvious once you get your head around it. If you think you have an application, ask for a demonstration. Metadata Central Underlying the associative intelligence there is another layer, which does the core work of accessing multiple databases and, most important, evaluating the results. That in itself is a powerful tool, so we also offer it as a separate module if required, called Metadata Central. In the USA the Golf Channel covers all the professional tournaments on the tours, so is constantly adding content, all of which needs to be tagged. Each week is a different set of players at a different course. Simply loading the basic information – the players and their current rankings, the yardage of the course, the history of the tournament 54 | TV-BAY MAGAZINE The same advantage would apply to aggregator broadcasters, for example. Say you have just bought a package of movies. You could get a team of researchers to sit and copy-type the cast lists and synopses for your database. Or you could use Metadata Central to talk to IMDB and set it all up, virtually instantaneously, and with good metadata you help consumers find content on VoD and over the top platforms which boosts access and revenues. Combining Metadata Central with some of the added intelligence in Teragator and you can make value judgements on data which is automatically collected. You can, for example, interpret tweets as a programme is being transmitted to determine the general audience reaction. If it is a live show you can report on them, or even respond to what the audience is saying by changing the production. Intelligence in the system can determine the difference between genuine sentiment, irony and sarcasm for comic effect, making the results reasonably reliable. IPV has demonstrated a topical application in the use of reality TV based programmes that are heavily reliant on audience reaction and sentiment. Using Teragator, they are able to poll multiple sources of live audience data (social networking data) and provide a valuable insight to the Production team, both during the show and in commentary afterwards. Using this data in realtime and monitoring social interaction around characters and presenters, for example, allows the show producers to optimise the show and its reach. That is the aim of semantic web tools such as Teragator and Metadata Central from IPV. They make it easy to explore and correlate many, many sources of information, to evaluate what you are finding, and to explore links and lines of development which may never otherwise appear. By giving researchers and programme makers more powerful and more comprehensive tools they speed up the process and shine a spotlight on new angles to the story. Ultimately, they help make better programmes even when the budgets tighten, and they help broadcasters find and serve audiences with the content they need.