At the recent SemTech conference in NYC, The Semantic Web Blog had an opportunity to ask some leaders in the field about where semantic technology has been, and where it’s going.

David Wood, CTO, 3RoundStones:

The short take: Hiring has been on in a big way at semantic tech players as enterprises are moving in greater numbers to buy semantic software, recognizing their traditional vendors won’t solve their interoperability issues. Sem tech vendors should have a happy 2013 as semantics continues going mainstream.

The full take:

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Futurity.org reports, “Scientists have found that the brain is wired to put the categories of objects and actions we see daily in order, and have created the first interactive map of how the brain organizes these groupings. The result—achieved through computational models of brain imaging data collected while the subjects watched hours of movie clips—is what researchers call ‘a continuous semantic space.’ Some relationships between categories make sense (humans and animals share the same ‘semantic neighborhood’) while others (hallways and buckets) are less obvious. The researchers found that different people share a similar semantic layout. ‘Our methods open a door that will quickly lead to a more complete and detailed understanding of how the brain is organized. Already, our online brain viewer appears to provide the most detailed look ever at the visual function and organization of a single human brain,’ says Alexander Huth, a doctoral student in neuroscience at University of California, Berkeley and lead author of the study published in the journal Neuron.” Read more

The Conductrics blog has shared a list of data science and machine learning resources. The introduction states, “Every now and then I get asked for some help or for some pointers on a machine learning/data science topic.  I tend respond with links to resources by folks that I consider to be experts in the topic area.   Over time my list has gotten a little larger so I decided to put it all together in a blog post. Since it is based mostly on the questions I have received, it is by no means complete, or even close to a complete list, but hopefully it will be of some use.  Perhaps I will keep it updated, or even better yet, feel free to comment with anything you think might be of help. Also, when I think of data science, I tend to focus on Machine Learning rather than the hardware or coding aspects. If you are looking for stuff on Hadoop, or R, or Python, sorry, there really isn’t anything here.” Read more

Kathleen Roney of Becker’s Hospital Review recently opined, “In order for the healthcare industry to move toward preventive care and population health management, clinical information needs to flow freely across networks and between hospitals and physicians. For this reason, healthcare organizations need interoperability — efficient yet secure means for IT systems and software applications to communicate and exchange patient data. While CMS focused the latest stage of its meaningful use program on measures and objectives to encourage interoperability, the effect of that will not be seen until later in 2013 and early 2014 when providers begin to incorporate those measures and objectives into their clinical work. ” Read more

The team at Nextgov reports, “The team that manages Data.gov is well on its way to making the government data repository open source using a new back-end called the Open Government Platform, officials said during a Web discussion Wednesday. The governments of India and Ghana have already launched beta versions of their data catalogues on the open source platform, said Jeanne Holm who heads the Data.gov team. Government developers from the U.S. and India built the OGPL jointly. They posted it to the code sharing site GitHub where other nations and developers can adopt it as is or amend it to meet their specific needs.” Read more

Borris Evelson of the Forrester Research blog recently shared Forrester’s prediction for business intelligence advances in 2013 and beyond. Evelson writes, “BI-specific DBMSes will gain popularity. Alternative database management system (DBMS) engines architected specifically for agile BI will emerge as one of the key fundamental agile BI technologies that BI pros should closely evaluate and consider. These specialized, BI-specific DBMS databases — those that are designed specifically for BI reporting and analysis — currently have lower adoption rates when compared with their bigger, older, more versatile, jack-of-all-trades RDBMS cousins. But don’t expect these low adoption rates to continue; BI-specific DBMSes started to become mainstream in 2012 and the trend will continue in 2013. Forrester expects that more than 20% of all BI applications will be based on this technology within the next two years.” Read more

In December, a group of Semantic thought leaders from around the globe met with their host and colleague, Eric Franzon, for the latest installment of the Semantic Link, a monthly podcast covering the world of Semantic Technologies. This episode includes a discussion about the newly launched Open Data Institute (ODI) in the UK, and “the Linkers” were joined by a special guest: Nigel Shadbolt, Chairman and Co-Founder of the ODI. You can learn more about the ODI here.
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Courtesy: Flickr/LadyDragonflyCC <3

Yesterday we began our look back at the year in semantic technology here. Today we continue with more expert commentary on the year in review:

Ivan Herman, W3C Semantic Web Activity Lead:

I would mention two things (among many, of course).

•  Schema.org had an important effect on semantic technologies. Of course, it is controversial (role of one major vocabulary and its relations to others, the community discussions on the syntax, etc.), but I would rather concentrate on the positive aspects. A few years ago the topic of discussion was whether having ‘structured data’, as it is referred to (I would simply say having RDF in some syntax or other), as part of a Web page makes sense or not. There were fairly passionate discussions about this and many were convinced that doing that would not make any sense, there is no use case for it, authors would not use it and could not deal with it, etc. Well, this discussion is over. Structured data in Web sites is here to stay, it is important, and has become part of the Web landscape. Schema.org’s contribution in this respect is very important; the discussions and disagreements I referred to are minor and transient compared to the success. And 2012 was the year when this issue was finally closed.
•  On a very different aspect (and motivated by my own personal interest) I see exciting moves in the library and the digital publishing world. Many libraries recognize the power of linked data as adopted by libraries, of the value of standard cataloging techniques well adapted to linked data, of the role of metadata, in the form of linked data, adopted by journals and soon by electronic books… All these will have a profound influence bringing a huge amount of very valuable data onto the Web of Data, linking to sources of accumulated human knowledge. I have witnessed different aspects of this evolution coming to the fore in 2012, and I think this will become very important in the years to come.

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Alex Howard of O’Reilly Radar recently shared examples of great data journalism from across the globe. He writes, “When I wrote that Radar was investigating data journalism and asked for your favorite examples of good work, we heard back from around the world. I received emails from Los Angeles, Philadelphia, Canada and Italy that featured data visualization, explored the role of data in government accountability, and shared how open data can revolutionize environmental reporting. A tweet pointed me to a talk about how R is being used in the newsroom… Several other responses are featured at more length below. After you read through, make sure to also check out this terrific Ignite talk on data journalism recorded at this year’s Newsfoo in Arizona.” Read more