The Financial Times Builds Up Its Semantic Publishing Infrastructure

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ftpixby Jennifer Zaino

The former lead architect at the BBC who handled its semantic publishing projects, such as its FIFA World Cup 2010, 2012 Olympics and redesigned BBC Sports Site, today is building up the semantic infrastructure at another media might, The Financial Times

Jem Rayfield, who holds the title Head of Solution Architecture Technology there, is rebuilding the Financial Times’ whole publishing stack to use semantic technology. “We are working on republishing the architecture on the back end, basically engineering the whole of the backend stack to use the RDF model” for data interchange, he says. Its work involves modeling ontologies for companies, organizations, brands, exchanges, shares, financial instruments and other key business terms.

It has decided not to use the Financial Industry Business Ontology (FIBO) model, instead modeling its own representation of business and finance. The reason, Rayfield says, is that the FIBO model doesn’t “really fit the news case particularly well.”

The semantic relationships in the financial domain represented by its ontologies “are key for us moving forward,” says Rayfield, as are APIs that will make it possible to get data stored within its triple stores, or from other sources to which its semantic model maps, out for use in interesting products. For example, this can power a user’s navigation from a story about a particular company to information the Financial Times stores about its directors. Or, “if readers are on a story about [the company] BP, we know its ticket from our semantic model, we go to the Data API and can get a graph of a particular instrument from a third-party data source,” he says.

Among other semantically-infused capabilities available now are recommended reads, based on the concept of semantic fingerprints, he explains. That is, the Financial Times leverages a concept extraction mechanism to understand what published stories cover and annotates them with identifiers found within the content, which is matched against users’ reading habits to identify what they’d likely want to peruse next. A similar approach semantically matches readers to ads. “Semantic advertising is good In terms of getting very targeted ads to the right people and profiles so that we can charge more for ads,” he says. “And serving the right content to the right people gets them to click to read more content so people stay on the site longer.”

In the coming year, he expects the focus to be on user-facing products as a new version of the site is being built with front-end apps to sit atop its semantic model and APIs.

The Financial Times is using Ontotext technology for its effort, and it’s been working with the vendor on features to improve performance. For instance, The Financial Times works across three data centers – two in the UK and one in the US – and faced the task of efficiently operating consistent transactions across geographies with the ongoing changes to its triple store architecture that are based on requests affecting its fairly large datasets. Its list of companies alone contains about 200 million triples statements, and there are frequent changes to those every day as company hierarchies change or businesses merge or other transactions take place. “Business and finance changes frequently,” he says.

Semantics, he thinks, is of age in the publishing industry. “I think editorial and business [sides] have seen the benefits of the [semantic] approach and they want to follow it,” he says. “A number of other publishers already are following the same model.”



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