Posts Tagged ‘Michael Hausenblas’
Here are some final thoughts from our panel of semantic web experts on what to expect to see as the New Year rings in:
Broader deployment of the schema.org terms is likely. In the study by Muehlisen and Bizer in July this year, we saw Open Graph Protocol, DC, FOAF, RSS, SIOC and Creative Commons still topping the ranks of top semantic vocabularies being used. In 2013 and beyond, I expect to see schema.org jump to the top of that list.
Christine Connors, Chief Ontologist, Knowledgent:
I think we will see an uptick in the job market for semantic technologists in the enterprise; primarily in the Fortune 2000. I expect to see some M&A activity as well from systems providers and integrators who recognize the desire to have a semantic component in their product suite. (No, I have no direct knowledge; it is my hunch!)
We will see increased competition from data analytics vendors who try to add RDF, OWL or graphstores to their existing platforms. I anticipate saying, at the end of 2013, that many of these immature deployments will leave some project teams disappointed. The mature vendors will need to put resources into sales and business development, with the right partners for consulting and systems integration, to be ready to respond to calls for proposals and assistance.
As we close out 2012, we’ve asked some semantic tech experts to give us their take on the year that was. Was Big Data a boon for the semantic web, or is the opportunity to capitalize on the connection still pending? Is structured data on the web not just the future but the present? What sector is taking a strong lead in the semantic web space?
We begin with Part 1, with our experts listed in alphabetical order:
John Breslin, lecturer at NUI Galway, researcher and unit leader at DERI, creator of SIOC, and co-founder of Technology Voice and StreamGlider:
I think the schema.org initiative really gaining community support and a broader range of terms has been fantastic. It’s been great to see an easily understandable set of terms for describing the objects in web pages, but also leveraging the experience of work like GoodRelations rather than ignoring what has gone before. It’s also been encouraging to see the growth of Drupal 7 (which produces RDFa data) in the government sector: Estimates are that 24 percent of .gov CMS sites are now powered by Drupal.
Martin Böhringer, CEO & Co-Founder Hojoki:
For us it was very important to see Jena, our Semantic Web framework, becoming an Apache top-level project in April 2012. We see a lot of development pace in this project recently and see a chance to build an open source Semantic Web foundation which can handle cutting-edge requirements.
Still disappointing is the missing link between Semantic Web and the “cool” technologies and buzzwords. From what we see Semantic Web gives answers to some of the industry’s most challenging problems, but it still doesn’t seem to really find its place in relation to the cloud or big data (Hadoop).
Christine Connors, Chief Ontologist, Knowledgent:
One trend that I have seen is increased interest in the broader spectrum of semantic technologies in the enterprise. Graph stores, NoSQL, schema-less and more flexible systems, ontologies (& ontologists!) and integration with legacy systems. I believe the Big Data movement has had a positive impact on this field. We are hearing more and more about “Big Data Analytics” from our clients, partners and friends. The analytical power brought to bear by the semantic technology stack is sparking curiosity – what is it really? How can these models help me mitigate risk, more accurately predict outcomes, identify hidden intellectual assets, and streamline business processes? Real questions, tough questions: fun challenges!
The Digital Enterprise Research Institute (DERI) is kicking off a project with Fujitsu Laboratories Ltd. in Japan to build a large-scale RDF store in the cloud capable of processing hundreds of billions of triples. The idea, says DERI research fellow Dr. Michael Hausenblas, “is to build up a platform that allows you to process and convert any kind of data” — from relational databases to LDAP record-based, directory-like data, but also streaming sources of data, such as sensors and even the Twitter firehose.
The project has defined eight different potential enterprise use cases for such a platform, ranging from knowledge-sharing in health care and life science to dashboards in financial services informed by XBRL data. “Once the platform is there we will implement at least a couple of these use cases on business requirements, and essentially we are going to see which are the most promising for business units,” Hausenblas says.
What do you get when you partner up the Schema.org markup vocabulary and the Web Intents specification? A win-win both for content publishers and search engines, says Dr. Michael Hausenblas, Linked Data Research Centre, DERI, NUI Galway, Ireland.
Hausenblas this week wrote about the “awesomeness” of connecting the two, describing how a search for a camera marked up using the schema.org vocabulary also could serve up a wave of Web Intents actions (existing and new ones) to take on the object. That could range from reviewing it to buying it.
“With Schema.org we have a way to describe the things we publish on our Web pages, such as books or cameras. And with WebIntents we have a technology at hand that allows us to interact with these things in a flexible way,” he wrote. With Web Intents, a framework for client-side service discovery and inter-application communication, services register their intention to be able to handle an action on the user’s behalf.
Speaking with the Semantic Web Blog, Hausenblas explains how the win-win happens: “Content publishers have an added incentive to use semantic markup there, not just to be better-ranked but to make their content more interactive,” he says. “And it’s a huge thing for search engines, as users can directly interact from them.”
Ward Cunningham, inventor of the wiki, is percolating another project: The Smallest Federated Wiki. This week he gave a presentation entitled, Missing From the Beginning: The Federation of Wikis Abstract, at the University of Advancing Technology (UAT) theatre, which is viewable here, and he’s been hosting Google+ hangouts about the work, too.
So, what is the Smallest Federated Wiki? The idea behind the work-in-progress, launched at IndieWebCamp this past summer and as explained here, is to innovate in three ways: The new Wiki shares through federation, composes by refactoring and wraps data with visualization. As Cunningham said in the March 7 presentation, “We’re making an ecosystem here for sharing data about ideas. I’m taking the conversation about how we’re going to live going forward, to be based on ideas backed up by data that we can understand because it has sensible visualizations.”
[Editor’s Note: This week, Juan Sequeda is reporting in from the International Semantic Web Conference in Bonn, Germany]
The Semantic Web Death Match: Industry vs Academica vs Standards at ISWC this week consisted of 5 panelists and Jim Hendler as the moderator. Each panelist summarized their point of view in a short phrase:
- Martin Hepp (Don’t shoot the messenger: the Fall of Constantinople)
- Michael Hausenblas (Now we have the basement, let’s go for the floors and the roof!)
- Chris Welty (Standards aren’t bad, just misunderstood)
- Ivan Herman (Did We forget about the client-side web applications’ world?)
- Ian Horrocks (Maybe the Web is the wrong application…)
[Update: Richard Cyganiak offers this interesting look at the process of creating VoID, “Creating an RDF vocabulary: Lessons learned“]
W3C recently published “Describing Linked Datasets with the VoID Vocabulary.” The document has been published as an interest group note edited by Keith Alexander, Richard Cyganiak, Michael Hausenblas, and Jun Zhao.
According to the W3C, “VoID is an RDF Schema vocabulary for expressing metadata about RDF datasets. It is intended as a bridge between the publishers and users of RDF data, with applications ranging from data discovery to cataloging and archiving of datasets. Read more