Photo Courtesy: Flickr/Lars Plougmann

In recent blogs we’ve discussed where semantic technologies have gone in 2012, and a bit about where they will go this year (see here, here and here).

Here are some final thoughts from our panel of semantic web experts on what to expect to see as the New Year rings in:

John Breslin,lecturer at NUI Galway, researcher and unit leader at DERI, creator of SIOC, and co-founder of Technology Voice and StreamGlider

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.

Seth Grimes, industry analyst, consultant and organizer of the Sentiment Analysis Symposium:

Expect to hear more about “sensemaking” in 2013. The concept has been around for a while — application of analytical and semantic techniques to synthesize situationally-relevant insights from diverse data — and it’s gaining new currency given mobile devices and the Variety element of Big Data.

 

Dr. Michael Hausenblas, Research Fellow and Research Center coordinator at DERI:

  • Advances concerning visualisations and interactions with LD – there are some promising activities such as this and this already.
  • The need for large-scale, interactive analytics, as I suggested during the ISWC 2012 lighting talks (see here)

Ivan Herman, W3C Semantic Web Activity Lead:

What I listed in the previous answer [regarding the path semantic technology took in 2012; see here] are evolutions that are still going on, mainly the library/publishing issue which, I believe, will have an even greater voice in 2013.

I would expect (hope?) to see much more applications that make real use of linked data, and open data on the web in general. The recent ODI (Open Data Institute) initiative may have a great effect in this, helping relevant start-ups and small companies deploying new type of applications. We still need many applications that are less large-scale (and behind-the-door) enterprise applications, but agile, end-user oriented Web based ones.

Another aspect of Linked Data usage that is worth paying attention to in 2013 is the ‘write’ side of things. At the moment, most of the Linked Data applications are “simply” consumers of data; producing that data, changing the data, etc., happens ‘out of band’, so to say. However, with the soon-to-be-finalized SPARQL Update standard and the work done at W3C under the heading of Linked Data Platform, the ‘write’ aspect of Linked Data will come to the fore; that may open the door for new aspects, new application patterns, which I hope will appear in 2013.

Shyam Kapur, President and CEO, TipTop Technologies Inc.:

Before the end of 2013, there will be semantic technology-driven, established alternatives to widely used search services like Google and social networks like Facebook and Twitter.

Leo Sauermann, CEO of Gnowsis:

We didn’t get it that all the money in enterprise goes to “Business Intelligence” and not into “RDF.” That said, those semantic vendors who go for Big Data and Business Intelligence will be able to sell their stuff — whatever it is — just because decision makers are too (lazy/busy) to read through the fine print and are already dazzled by BI marketing flashbangs.

The LOD use cases will grow and will change the way democracy works. The political aspect of LOD has the biggest potential, informed masses will make humanity better. Understanding public government information is a historic landmark in the semantic web, because although by legislation, the people have the power, in reality the leaders have an unfair information advantage. Manipulations by government and lobbyists should be detected in LOD data and crowd-sourced social campaigns will help to raise awareness to corruption and help fight it.

The one to make use of schema.org data in creative ways for marketing/sales/channel startups will be able to cash in a big check at the end of 2013.

Nova Spivack, CEO and co-founder, Bottlenose:

I think a lot more focus is shifting to semantics on the real-time stream (Twitter and Facebook primarily).

I am seeing more apps that can intelligently understand language (for calendaring apps for example, as well as other apps — even Evernote does language recognition)

Marco Neumann, CEO and co-founder, KONA and director, Lotico:

A prediction I have for 2013 is: due to the availability of robust tools and a wide range of business- ready products in the semantic technology space we will observe an increase in data providers and data services. This most likely will shift the focus from low-level feature implementation and infrastructure deployment to data quality and application development.

Some of the areas KONA will track in 2013 are the standardization and deployment of provenance recommendations by the W3C and trust services. In parallel we will take a close look at the race among the top 10 Web companies and potentially new players to become the Identity Provider of choice for profiled web services, personal business transactions and targeted advertising services.

Amit Sheth, LexisNexis Ohio Eminent Scholar, Kno.e.sis Center, Wright State University:

  • Growing role of background knowledge:  Semantic Web researchers and early entrepreneurs knew (as exemplified by this first patent on Semantic Web technologies filed in 2000) that with moderate effort, it is possible to create background knowledge and populated ontologies by aggregating and disambiguating high-quality information and facts from multiple sources. It has also been long known that by using such knowledge bases, we can substantially improve information extraction and develop a variety of semantic tools and applications including semantic search, browsing, personalization, advertisement, etc. Over the past 3-5 years, several efforts to create such knowledge bases took place, of which Freebase is a showcase. What has drawn everyone’s attention to this aspect of semantic approach is Google’s acquisition of the company that created Freebase and significantly extending techniques largely known, but scaling it to the next level, to create Google Knowledge Base (GKB).  Further on, applying GKB to enhance search (and I am sure other applications in future), has forever changed the importance of creating and using background or domain models for semantic applications. I believe this form of semantic application building will see the fastest growth in the near future. I have discussed related thoughts in my article titled  “Semantics Scales Up.”
  • Growing pains for Linked Open Data (LOD): Publication of over 300 large data sets with 30+ billion triples certainly draws the attention of many.  Data holders will continue to find LOD an attractive vehicle to publish and share their data, so it will continue to grow at a rapid pace. Some of the data sets, more than others, will find additional usage as data reference, interlinking, and transformation. But in the near term, broader or aggregate usage of LOD will be a slog because we are running into some of the harder technical challenges: questionable quality of data and provenance, unconstrained and uneven use of semantics (e.g. same-as used inconsistently), and limited use of richer relationship types (part-of relationship, causality), and poor interlinking (lack of high-quality alignment).  We will need to have better handle of these issues along with a better ability to identify the most relevant and high-quality data sets (a semantic search for LOD) and better alignment tools (not limited to just same-as), before we can start realizing the true promise of LOD. So, I would give it another five years to fully develop.