You are here:  Home  >  Education Resources For Use & Management of Data  >  Data Daily | Data News  >  Current Article

IPTC Releases Comprehensive Controlled Vocabularies for SportsML 3.0 Standard

By   /  November 18, 2016  /  No Comments

ipby Angela Guess

According to a recent press release, “The IPTC has released a comprehensive set of sports controlled vocabularies as a supplement to the SportsML 3.0sports-data interchange format, which was released in July 2016. These controlled vocabularies (CVs) are in the format of NewsML-G2 Knowledge Items plus RDF variants and are available on IPTC’s CV server at http://cv.iptc.org/newscodes. There are 113 CVs representing such core sports concerns such as event and player status, as well as specialized lists for 11 sports (basketball, soccer, rugby, American football, etc.) for statistics, player positions, scoring types, etc. ‘The SportsML 3.0 standard’s semantic tech capabilities are improved greatly by the new controlled vocabularies,’ said Trond Husø, system developer for Norwegian news agency NTB, one of the early adopters of SportsML 3.0. ‘Data can be easily imported, structured, and stored’.”

The release goes on, “For the Summer 2016 Olympics, NTB acquired the rights to distribute the results and data from the International Olympics Committee’s Olympic Data Feed (ODF). NTB then transformed ODF to SportsML 3.0, and then to NITF3.2. ‘Using SportsML to structure the ODF’s data is a broad and comprehensive solution to approaching all sports and competitions worldwide,’ said Husø, who is also a member of IPTC’s Sports Content Working Group. ‘SportsML is now a truly flexible and universal format that can incorporate multiple vendor codes and still provide a defense against vendor lock-in’… Another advantage to the new SportsML 3.0 standard is that if new concepts are added to a sports vocabulary or modified in it, the data model and the XML Schema don’t change; they stay stable. It also supports all languages for the concept labels.”

Read more at Marketwired.

Photo credit: IPTC

You might also like...

Analytics vs. Data Discovery

Read More →