Keynote speaker Aaron Bradley from Electronic Arts (EA) has observed the development of enterprise knowledge graphs, where companies have begun to reap the benefits of linked data technologies. We had the chance to ask Aaron for a statement.
Danilo: How do you see the uptake of semantic technologies in the industry today?
Aaron: I think it’s pretty evident that there’s been a surge in the use of semantic technologies across different types of industries, and there are a number of reasons for this.
First, there are increasingly demonstrable success stories to which would-be users of semantic technologies can turn to for inspiration, cite to support development proposals, and use to craft their own linked data strategies. When I first started dipping my toes in semantic waters, around 2008, there was much hand-wringing in the community about whether or not these technologies would ever power a “killer app” that would expose the benefits of using linked data. That changed in 2012 with the release of the Google Knowledge Graph, which not only provided that go-to success story, but also provided proponents of semantic technologies with a new way of talking about them without the baggage with which the term “semantic web” had become encumbered.
Second, the tooling around semantic technologies has vastly improved, both in terms of availability and quality, making it far easier - especially for more traditional software engineers - to start building semantically-enabled applications. And while core semantic standards like RDF and OWL have been backed for some time, I’d probably roll some standards and knowledge base development into this too. This includes the 2011 release of schema.org, which provided the world with a lightweight yet robust ontology, and rollout of Wikidata in 2012, which provided the world with a natively semantic knowledge base. But from an uptake perspective it’s perhaps been the introduction of JSON-LD that’s been most significant, as it provides a developer-friendly serialization format for linked data.
Finally, there are now a far greater number of developers and data architects with the skills to successfully employ these technologies. This talent pool continues to grow as enterprises adopt these technologies, and as more and more people are exposed to the tools and standards required for success.
Danilo: Do companies look at semantic technologies any differently today compared to when you first started working in the field?
Aaron: Absolutely. In the past linked data solutions to real-world enterprise data challenges were viewed skeptically - where such solutions were not entertained at all - whereas today, these approaches are now very much on the table. This change is directly related to the factors I outlined above. The combination of citable semantic success stories, improved tooling, new standards and a growing talent pool have made semantically-enabled initiatives viable in a way they weren’t in the past.
Even more, though, the trajectory of semantic technology development and use has made such solutions not only viable, but attractive, that is, in many cases it’s turning out that a semantic approach is a more efficient, robust and extensible means of satisfying an enterprise’s information needs than any other alternative, especially when connecting large amounts of data from disparate sources is required, adds otherwise-unobtainable benefits, or both. Evidence of this can now be observed in the rollout of enterprise knowledge graphs in specific industries to meet specific needs: in e-commerce, news media and other consumer-facing enterprises for personalization and for product or content recommendations; in the pharmaceutical and financial industries for regulatory compliance; in manufacturing for supply chain management; in the biomedical realm for the insights gained by more meaningfully connected data points; in government for greater transparency and improved, data-driven decision making; and, enduringly, in enterprise search for everything from query understanding to meeting the complex demands of providing usable answers in a multi-device world.
In short, businesses are now increasingly turning to semantic technologies in situations where a knowledge graph, in particular, is the best method of satisfying a particular business need, and we’re now at a point where these technologies can be deployed with relative ease and at a reasonable cost, at least in comparison to the not-so-distant past.
Aaron Bradley works as a Knowledge Graph Strategist at Electronic Arts in Vancouver, Canada. With a background in library science, web design and search engine marketing, Aaron now works as part of a team that is focused on the development, expansion and improvement of EA’s knowledge graph.
