Ontology/Ontologies

Off Semantic Tech Goes Into The Wild Blue Yonder

rsz_amprimeLook, up in the sky! It’s a bird, it’s a plane, no – it’s an Amazon drone!

Admittedly, Amazon Prime Air’s unmanned aerial vehicles in commercial use are still a little ways off. But such technology – along with other recent innovations, such as the use of unmanned aircraft in crop-dusting or even Department of Homeland Security border applications, or future capabilities to extend the notion of auto-piloting in passenger airplanes using autonomous machine logic to control airspace and spacing between planes –needs to be accounted for in terms of its impact on the air space. The Next-Generation Air Transportation System is taking on the change in the management and operation of the national air transportation system.

And semantic technology, natural language processing, and machine learning, too, will have a hand in helping out, by fostering collaboration among the agencies that will be working together to develop the system, including the Federal Aviation Administration, the U.S. Air Force, U.S. Navy, and the National Aeronautics and Space Administration, under the coordination of the Joint Planning and Development Office. These agencies will need to leverage each other’s knowledge and research, as well as ensure – as necessary – data privacy.

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New Vocabularies Are Now W3C Recommendations

W3C LogoWe reported yesterday on the news that JSON-LD has reached Recommendation status at W3C. Three formal vocabularies also reached that important milestone yesterday:

The W3C Documentation for The Data Catalog Vocabulary (DCAT), says that DCAT “is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web….By using DCAT to describe datasets in data catalogs, publishers increase discoverability and enable applications easily to consume metadata from multiple catalogs. It further enables decentralized publishing of catalogs and facilitates federated dataset search across sites. Aggregated DCAT metadata can serve as a manifest file to facilitate digital preservation.”

Meanwhile, The RDF Data Cube Vocabulary  addresses the following issue: “There are many situations where it would be useful to be able to publish multi-dimensional data, such as statistics, on the web in such a way that it can be linked to related data sets and concepts. The Data Cube vocabulary provides a means to do this using the W3C RDF (Resource Description Framework) standard. The model underpinning the Data Cube vocabulary is compatible with the cube model that underlies SDMX (Statistical Data and Metadata eXchange), an ISO standard for exchanging and sharing statistical data and metadata among organizations. The Data Cube vocabulary is a core foundation which supports extension vocabularies to enable publication of other aspects of statistical data flows or other multidimensional data sets.”

Lastly, W3C now recommends use of the Organization Ontology, “a core ontology for organizational structures, aimed at supporting linked data publishing of organizational information across a number of domains. It is designed to allow domain-specific extensions to add classification of organizations and roles, as well as extensions to support neighbouring information such as organizational activities.”

 

Interest Grows In Riding The Semantic Wave

Image Courtesy: Flickr/ Peter Kaminski

Image Courtesy: Flickr/ Peter Kaminski

Industry leaders in sectors including banking and financial services look to have high hopes for semantic technology. They’re thinking about FIBO (Financial Industry Business Ontology) and leveraging semantic technology for more traditional types of data integration and analytics projects. At Cognizant, Thomas Kelly, a director in its Enterprise Information Management practice – and the author of this white paper on How Semantic Technology Drives Agile Business – sees the positive development that clients in the Fortune 500 space like these “are maturing in their use of semantic technology, from a project focus to more enterprise initiatives.”

The interest in FIBO, he says, is representative of an overall interest across in industries in leveraging industry ontologies as mechanisms to help companies better standardize, align and learn from the output of industry-wide efforts. The attention that industry analysts, including Gartner, have put on the semantic web in the last year – not to mention regulators beginning to consider its use in sharing information on a regulatory basis – have helped increase interest by commercial organizations, Kelly notes. That’s also evident in the life sciences sector, as another example, with the efforts of the FDA/PhUSE  Semantic Technology Working Group Project to include a draft set of existing CDISC standards in RDF.

The pickup in attention to many things semantic ties to the different perspectives that organizations need to manage about their data, which include “how they currently think of their data, how it is currently perceived in managing business operations; and where they are looking to go in the future that makes it more inclusive of what’s going on in the world outside their walls – that is, how the rest of the industry looks at this data and uses it to support their business processes,” he says.

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Senzari’s MusicGraph APIs Look To Enhance Musical Journeys

MusicGraph image

News came the other week that Senzari had announced the MusicGraph knowledge engine for music. The Semantic Web Blog had a chance to learn a little bit more about it what’s underway thanks to a chat with Senzari’s COO Demian Bellumio.

MusicGraph used to go by the geekier name of Adaptable Music Parallel Processing Platform, or AMP3 for short, for helping users control their Internet radio. “We wanted to put more knowledge into our graph. The idea was we have really cool and interesting data that is ontologically connected in ways never done before,” says Bellumio. “We wanted to put it out in the world and let the world leverage it, and MusicGraph is a production of that vision.”

Since its announcement earlier this month about launching the consumer version on the Firefox OS platform that lets users make complex queries about music and learn and then listen to results, Senzari has submitted its technology to be offered for the iOS, Android, and Windows Mobile platforms.  “You can ask anything you can think of in the music realm. We connect about 1 billion different points to respond to these queries,” he says. Its data covers more than twenty million songs, connected to millions of individual albums and artists across all genres, with extracted information on everything from keys to concept extractions derived from lyrics.

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Senzari Launches MusicGraph, a Knowledge Engine for Music

senzari

MIAMI–(BUSINESS WIRE)–Senzari® today announced MusicGraph, the world’s first knowledge engine for music, which will be available as a consumer app across most major mobile platforms, as well as a powerful “graph API” that can be leveraged by developers to enhance their applications with deep musical intelligence. MusicGraph contains over a billion facts that have been organized into a rich music ontology, which includes acoustical and lyrical features, detailed artist, album and song information, as well hundreds of other data points related user preferences. Read more

Help For HealthCare: Mapping Unstructured Clinical Notes To ICD-10 Coding Schemes

Photo of Amit ShethThe health care industry – and the American citizenry at large – has been focused of late on the problems surrounding the implementation of the Affordable Care Act, the federal website’s issues foremost among them. But believe it or not, there are other things the healthcare industry needs to prepare for, among them the October 1, 2014 date for replacing the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems ICD-9 code sets used to report medical diagnoses and inpatient procedures by ICD-10 code sets. ICD-9 uses 14,000 diagnosis codes which will increase to 68,000 in ICD-10, which is a HIPAA (Health Insurance Portability and Accountability Act) code set requirement.

Natural language processing has had the primary role in many solutions aimed at transforming large volumes of unstructured clinical data into information that healthcare IT application vendors and their hospital customers can leverage. But there’s an argument being made that understanding unstructured text of clinical notes that contain a huge stash of information and then mapping them to fine-grained ICD-10 coding schemes requires a combination of NLP, advanced linguistics, machine learning and semantic web technologies, and Amit Sheth, professor of computer science and engineering at Wright State University and director of the Kno.e.sis Center is making them. (See our story yesterday for a look at how the NLP market is evolving overall, including in healthcare.)

“ICD-10 has thousands of codes with millions of possible permutations and combinations. A rule-based approach is not effective to cover the huge number of ICD-10 codes.” Sheth says. Extracting the correct concepts, identifying the relationship between these concepts and mapping them to the correct code is a major challenge, with codes often formed by information from various sections of a clinical document that itself is subject to individual physicians’ style of recording information, among other factors.

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Sem Tech Solution For Materials Design And Development Wins Small Business Innovation Research Grant

rsz_matontoA Small Business Innovation Research grant, sponsored by the U.S. Air Force through the Office of the Secretary of Defense, has gone to a semantic technology solution for materials design and development. The project is aligned with the Materials Genome Initiative  that’s targeted to accelerate the pace of discovery and deployment of advanced material systems.

“This will help to showcase the semantic web technologies and methodologies in a large and meaningful domain and application area,” says Sam Chance, Innovation Evangelist and Special Programs Lead at iNovex Information Systems, which is the principal investigator and technical agent for development and integration for the project that will leverage W3C semantic standards. The project also includes as team members the University of Queensland, Penn State University, SRI International’s Materials Laboratory, and with Cambridge Semantics for access to its semantic tools to be bootstrapped onto the solution.

The University of Queensland brings to the effort a high-level domain ontology to represent structured knowledge about materials, their structure and properties and the processing steps involved in their composition and engineering, as well as certain case studies and data sources around jet fuels for hypersonic flight that are considered part of the materials design domain. The group at Penn State has been involved with the Materials Genome Initiative and also brings to the work particular case studies and data sources, this time for materials with nickel alloy as the base system. SRI has case studies and data sources for turbine blade coating.

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Expert System Launches Cogito Intelligence API on Mashape API Marketplace

Expert System logoCHICAGO, ILLINOIS–(Marketwired – Oct. 16, 2013) - Expert System, the semantic technology company, today announces the availability of the “freemium” version of its semantic API on Mashape, the online API marketplace. Cogito Intelligence API is the first API for the semantic analysis of large quantities of unstructured texts for supporting intelligence, counter crime and cybersecurity activities. Read more

The Library of 2020

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Joseph Janes, editor of Library 2020, recently shared an excerpt from that publication on LibraryJournal.com. The article envisions two research libraries in the year 2020, one that has embraced technology, and one that has not. Janes prefaces the article, “Transformation. The word is so pervasive these days, it’s a cliché. We’re so inured to it—even tired of it—that it’s becoming background noise, and perhaps some of us don’t hear it anymore. As we all know, accomplishing real transformation is easier said than done. This is the theme taken up by Mary Ann Mavrinac in her essay for Library 2020, which LJ excerpts here. She is the vice provost and dean of River Campus Libraries at the University of Rochester, NY; I met her when teaching a few summers ago at the University of Toronto, when she was running the splendid library at its campus in Mississauga.” Read more

The Internet of Things is Here

Drew Turney of WA Today recently wrote, “Today your smartphone knows your location, so everything from the local weather to nearby Facebook friends is available. What about tomorrow when your jacket can measure your vital signs or a hat can extrapolate your mood from your brain activity? Connect it with information on your schedule (from your calendar), spatial information such as whether you’re running or at rest, the time of day and a hundred other factors, and machines everywhere can decide on, find and present the information they think you need. The field is opened even wider by search technology that finds abstract connections for you, rather than you starting a search at a given point. A system out of Bangalore, India called CollabLayer lets you watch for specific keywords you assign to almost any kind of data in a network.” Read more

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