You are here:  Home  >  Data Education  >  Current Article

Picture This: Muséophile Leads Art Lovers To Art Works

By   /  October 14, 2013  /  No Comments

rsz_museophilepixWhere in Paris might you find an exhibit featuring the artist Charles Le Brun?

If you didn’t know to check into the Musée du Louvre, Muséophile can help. Just plug in an artist or movement, and city, and see what comes to the fore. The service, still in beta, comes courtesy of Sémanticpédia, a platform for collaboration between France’s Ministry of Culture and Communication; INRIA, the country’s public institution of scientific and technological research;   and Wikimedia France, whose aim is to perform research and development applied to corpus or collaborative cultural projects, using data extracted from Wikimedia projects.

Currently, data from French DBpedia is available for Sémanticpédia projects to leverage, and Muséophile is the first effort of the collaboration to do so. In fact, an overall effort by the government of France to boost the representation of French cultural resources on the web, which should aid in Muséophile’s continued development, is underway: Those within the Ministry of Culture and Communication with expertise in various content bases related to French culture are being charged to contribute their knowledge to the still youthful French DBpedia, which constitutes an extraction of structured information from the French Wikipedia. That will lead to a single reference system that they also can rely on to collaborate, and exchange and integrate data.

Muséophile owes its existence, however, to Mara Dumitru, who had the idea to develop it while she was a student at the American University of Paris majoring in computer science and minoring in art history. She began developing it to fulfill an assignment in a class on the semantic web led by Dr. Milan Stankovic, and continued to move it forward while working in the French Ministry of Culture with the help of Stankovic, acting in his role as president and chief science officer of startup, SÉPAGE, that specializes in creating semantic web-based recommender systems. The SÉPAGE team finalized the interface for directly querying DBpedia in realtime, recommending museums based on the results it obtains of where artists or their works of art are found.

“Muséophile shows how everyone can build applications on French DBpedia and reuse this data,” says Stankovic. “The second reason for being is also to show how using semantic references, you can easily have a multilingual website.” Muséophile is accessible in nine languages, which he says was easy to accomplish because of its manipulation of concepts, not text. “Each concept is described on DBpedia in many languages, so when a user performs a search we have results that are concepts, and we present that in any language we want. The Ministry is very happy about it because they are very interested in putting more regional languages and more French languages on the web, and making this more represented on the web.”

rsz_museopixMilan explains that the system currently is working on very little data, for now. “On Wikipedia unfortunately you don’t find a description of all works of art, just the major ones. But even with that, we can recommend good museums and make a relevant experience,” he notes. Indeed, by showcasing what can be done with relatively little data online, the project should justify further efforts on the ministry side to publish more data in French DBpedia, and for public administrators to give more data to citizens to do useful things with, he says. “We are lucky to have people in French Ministry of culture we need to publish public data in a semantic way, so we expect bigger data sets from cultural domains being published.”

As Dumitru points out, such contributions mean Muséophile is able to incorporate data about works of art from museums in small cities in France that don’t surface on English Wikipedia. “Maybe you never heard of a city close by to Paris but it has a painting belong to your favorite artist or movements. You can discover new things you wouldn’t normally find,” she says.

The system also recently was updated to include recommendations of artists similar to the one a user is searching for, and where their works are being featured.  “It is the semantic similarity of two artists – if they were influenced by one another or by a similar artist,” Stankovic says. “For instance, if you like Claude Monet, you probably also would be interested in Degas, and then Museophile can recommend you to look for Degas and museums that have his works.”

About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.

You might also like...

Is Data Governance Solely About Controls on Data?

Read More →