Archive for the 'OWL' Category
September 19th, 2014, by Tim Finin, posted in Mobile Computing, OWL, RDF, Semantic Web, Wearable Computing
Primal Pappachan, Roberto Yus, Anupam Joshi and Tim Finin, Rafiki: A Semantic and Collaborative Approach to Community Health-Care in Underserved Areas, 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 22-15 October2014, Miami.
Community Health Workers (CHWs) act as liaisons between health-care providers and patients in underserved or un-served areas. However, the lack of information sharing and training support impedes the effectiveness of CHWs and their ability to correctly diagnose patients. In this paper, we propose and describe a system for mobile and wearable computing devices called Rafiki which assists CHWs in decision making and facilitates collaboration among them. Rafiki can infer possible diseases and treatments by representing the diseases, their symptoms, and patient context in OWL ontologies and by reasoning over this model. The use of semantic representation of data makes it easier to share knowledge related to disease, symptom, diagnosis guidelines, and patient demography, between various personnel involved in health-care (e.g., CHWs, patients, health-care providers). We describe the Rafiki system with the help of a motivating community health-care scenario and present an Android prototype for smart phones and Google Glass.
May 23rd, 2013, by Tim Finin, posted in AI, Google, KR, NLP, OWL, Semantic Web
Top Charts is a new feature for Google Trends that identifies the popular searches within a category, i.e., books or actors. What’s interesting about it, from a technology standpoint, is that it uses Google’s Knowledge Graph to provide a universe of things and the categories into which they belong. This is a great example of “Things, not strings”, Google’s clever slogan to explain the importance of the Knowledge Graph.
Here’s how it’s explained in in the Trends Top Charts FAQ.
“Top Charts relies on technology from the Knowledge Graph to identify when search queries seem to be about particular real-world people, places and things. The Knowledge Graph enables our technology to connect searches with real-world entities and their attributes. For example, if you search for ice ice baby, you’re probably searching for information about the musician Vanilla Ice or his music. Whereas if you search for vanilla ice cream recipe, you’re probably looking for information about the tasty dessert. Top Charts builds on work we’ve done so our systems do a better job finding you the information you’re actually looking for, whether tasty desserts or musicians.”
One thing to note is that the Knowledge Graph, which is said to have more than 18 billion facts about 570 million objects, is that its objects include more than the traditional named entities (e.g., people, places, things). For example, there is a top chart for Animals that shows that dogs are the most popular animal in Google searches followed by cats (no surprises here) with chickens at number three on the list (could their high rank be due to recipe searches?). The dog object, in most knowledge representation schemes, would be modeled as a concept or class as opposed to an object or instance. In some representation systems, the same term (e.g., dog) can be used to refer to both a class of instances (a class that includes Lassie) and also to an instance (e.g., an instance of the class animal types). Which sense of the term dog is meant (class vs. instance) is determined by the context. In the semantic web representation language OWL 2, the ability to use the same term to refer to a class or a related instance is called punning.
Of course, when doing this kind of mapping of terms to objects, we only want to consider concepts that commonly have words or short phrases used to denote them. Not all concepts do, such as animals that from a long way off look like flies.
A second observation is that once you have a nice knowledge base like the Knowledge Graph, you have a new problem: how can you recognize mentions of its instances in text. In the DBpedia knowledge based (derived from Wikipedia) there are nine individuals named Michael Jordan and two of them were professional basketball players in the NBA. So, when you enter a search query like “When did Michael Jordan play for Penn”, we have to use information in the query, its context and what we know about the possible referents (e.g., those nine Michael Jordans) to decide (1) if this is likely to be a reference to any of the objects in our knowledge base, and (2) if so, to which one. This task, which is a fundamental one in language processing, is not trivial, but luckily, in applications like Top Charts, we don’t have to do it with perfect accuracy.
Google’s Top Charts is a simple, but effective, example that demonstrates the potential usefulness of semantic technology to make our information systems better in the near future.
September 15th, 2011, by Tim Finin, posted in Google, KR, Ontologies, OWL, Semantic Web, Social media
The Wall Street Journal article Walked Into a Lamppost? Hurt While Crocheting? Help Is on the Way describes the International Classification of Diseases, 10th Revision that is used to describe medical problems.
“Today, hospitals and doctors use a system of about 18,000 codes to describe medical services in bills they send to insurers. Apparently, that doesn’t allow for quite enough nuance. A new federally mandated version will expand the number to around 140,000—adding codes that describe precisely what bone was broken, or which artery is receiving a stent. It will also have a code for recording that a patient’s injury occurred in a chicken coop.”
We want to see the search engine companies develop and support a Microdata vocabulary for ICD-10. An ICDM-10 OWL DL ontology has already been done, but a Microdata version might add a lot of value. We could use it on our blogs and Facebook posts to catalog those annoying problems we encounter each day, like W59.22XD (Struck by turtle, initial encounter), or Y07.53 (Teacher or instructor, perpetrator of maltreat and neglect).
Humor aside, a description logic representation (e.g., in OWL) makes the coding system seem less ridiculous. Instead of appearing as a catalog of 140K ground tags, it would emphasize that it is a collection of a much smaller number of classes that can be combined in productive ways to produce them or used to create general descriptions (e.g., bitten by an animal).
October 27th, 2009, by Tim Finin, posted in AI, KR, Ontologies, OWL, Semantic Web
OWL 2, the new version of the Web Ontology Language, officially became a W3C standard yesterday. From the W3C press release:
“Today W3C announces a new version of a standard for representing knowledge on the Web. OWL 2, part of W3C’s Semantic Web toolkit, allows people to capture their knowledge about a particular domain (say, energy or medicine) and then use tools to manage information, search through it, and learn more from it. Furthermore, as an open standard based on Web technology, it lowers the cost of merging knowledge from multiple domains.”
July 9th, 2009, by Tim Finin, posted in Conferences, iswc, OWL, RDF, Semantic Web, Web
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Semantics for the Rest of Us: Variants of Semantic Web Languages in the Real World is a workshop that will be held at the on 26 October 2009 in Washington, DC.
The Semantic Web is a broad vision of the future of personal computing, emphasizing the use of sophisticated knowledge representation as the basis for end-user applications’ data modeling and management needs. Key to the pervasive adoption of Semantic Web technologies is a good set of fundamental “building blocks” – the most important of these are representation languages themselves. W3C’s standard languages for the Semantic Web, RDF and OWL, have been around for several years. Instead of strict standards compliance, we see “variants” of these languages emerge in applications, often tailored to a particular application’s needs. These variants are often either subsets of OWL or supersets of RDF, typically with fragments OWL added. Extensions based on rules, such as SWRL and N3 logic, have been developed as well as enhancements to the SPARQL query language and protocol.
This workshop will explore the landscape of RDF, OWL and SPARQL variants, specifically from the standpoint of “real-world semantics”. Are there commonalities in these variants that might suggest new standards or new versions of the existing standards? We hope to identify common requirements of applications consuming Semantic Web data and understand the pros and cons of a strictly formal approach to modeling data versus a “scruffier” approach where semantics are based on application requirements and implementation restrictions.
The workshop will encourage active audience participation and discussion and will include a keynote speaker as well as a panel. Topics of interest include but are not limited to
- Real world applications that use (variants of) RDF, OWL, and SPARQL
- Use cases for different subsets/supersets of RDF, OWL, and SPARQL
- Extensions of SWRL and N3Logic
- RIF dialects
- How well do the current SW standards meet system requirements ?
- Real world “semantic” applications using other structured representations (XML, JSON)
- Alternatives to RDF, OWL or SPARQL
- Are ad hoc subsets of SW languages leading to problems?
- What level of expressive power does the Semantic Web need?
- Does the Semantic Web require languages based on formal methods?
- How should standard Semantic Web languages be designed?
We seek two kinds of submissions: full papers up to ten pages long and position papers up to five pages long. Format papers according the ISWC 2009 instructions. Accepted papers will be presented at the workshop and be part of the workshop proceedings.
December 22nd, 2008, by Tim Finin, posted in AI, KR, OWL, Semantic Web
Tom Briggs defended his PhD dissertation last month on discovering domain and range constraints in OWL and the final copy is now available.
Thomas H. Briggs, Constraint Generation and Reasoning in OWL, 2008.
The majority of OWL ontologies in the emerging SemanticWeb are constructed from properties that lack domain and range constraints. Constraints in OWL are different from the familiar uses in programming languages and databases. They are actually type assertions that are made about the individualswhich are connected by the property. Because they are type assertions these assertions can add vital information to the individuals involved and give information on how the defining property may be used. Three different automated generation techniques are explored in this research: disjunction, least-common named subsumer, and vivification. Each algorithm is compared for the ability to generalize, and the performance impacts with respect to the reasoner. A large sample of ontologies from the Swoogle repository are used to compare real-world performance of these techniques. Using generated facts is a type of default reasoning. This may conflict with future assertions to the knowledge base. While general default reasoning is non-monotonic and undecidable a novel approach is introduced to support efficient contraction of the default knowledge. Constraint generation and default reasoning, together, enable a robust and efficient generation of domain and range constraints which will result in the inference of additional facts and improved performance for a number of Semantic Web applications.
November 10th, 2008, by Tim Finin, posted in OWL, RDF, Semantic Web, UMBC
Tom Briggs will defend his dissertation, Constraint Generation and Reasoning in OWL, at Noon on Monday 17 November 2008 in ITE 325b. His work has focused on automatically computing reasonable domain and range constraints for Semantic Web properties. Here’s the abstract:
The majority of OWL ontologies in the emerging Semantic Web are constructed from properties that lack domain and range constraints. Constraints in OWL are different from the familiar uses in programming languages and databases, and are actually type assertions that are made about the individuals which are connected by the property. These assertions can add vital information to the model because they are assertions of type on the individuals involved, and they can also give information on how the defining property may be used.
Three different automated generation techniques are explored in this research: disjunction, least-common named subsumer, and vivification. Each algorithm is compared for the ability to generalize, and the performance impacts with respect to the reasoner. A large sample of ontologies from the Swoogle repository are used to compare real-world performance of these techniques.
Finally, using generated facts, a type of default reasoning, may conflict with future assertions to the knowledge base. While general default reasoning is non-monotonic and undecidable a novel approach is introduced to support efficient retraction of the default knowledge. Combined, these techniques enable a robust and efficient generation of domain and range constraints which will result in inference of additional facts and improved performance for a number of Semantic Web applications.
Tom’s dissertation advisor is Professor Yun Peng.
April 28th, 2008, by Tim Finin, posted in OWL, Semantic Web
In this week’s ebiquity group meeting, Palani Kodeswaran will talk about his research in developing protocols to govern how network routers implement the Border Gateway Protocol. here’s the aabstract.
“Policies in BGP are implemented as routing configurations that determine how route information is shared among neighbors to control traffic flows across networks. This process is generally template driven, device centric, limited in its expressibility, time consuming and error prone which can lead to configurations where policies are violated or there are unintended consequences that are difficult to detect and resolve. In this work, we propose an alternate mechanism for policy based networking that relies on using additional semantic information associated with routes expressed in an OWL ontology. Policies are expressed using SWRL to provide fine-grained control where by the routers can reason over their routes and determine how they need to be exchanged. In this paper, we focus on security related BGP policies and show how our framework can be used in implementing them. Additional contextual information such as affiliations and route restrictions are incorporated into our policy specifications which can then be reasoned over to infer the correct configurations that need to be applied, resulting in a process which is easy to deploy, manage and verify for consistency.”
Our meetings are open to anyone who wants to come, so drop in if you are interested. (10am Tuesday 29 April 2008, room 325 ITE building)
February 2nd, 2008, by Tim Finin, posted in NLP, OWL, RDF, Semantic Web, Social media, Web, Web 2.0
Reuters has released an API for its Calais Web service. The free service discovers entities, events and relations in text and returns the results in the form of RDF data. The services use information extraction technology from ClearForest, which Reuters acquired in April 2007.
“The Calais web service automatically attaches rich semantic metadata to the content you submit â€“ in well under a second. Using natural language processing, machine learning and other methods, Calais categorizes and links your document with entities (people, places, organizations, etc.), facts (person â€˜xâ€™ works for company â€˜yâ€™), and events (person â€˜zâ€™ was appointed chairman of company â€˜yâ€™ on date â€˜xâ€™). The metadata results are stored centrally and returned to you as industry-standard RDF constructs accompanied by a Globally Unique Identifier (GUID). Using the Calais GUID, any downstream consumer is able to retrieve this metadata via a simple call to Calais.” (link)
The semantic types it recognizes and uses in its annotations are a basic set typical of information extraction systems and include entities, facts, events and categories. See, for example, the description of the person entity type. The brief API documentation describes how to call the web services and interpret the results. As an example of the semantic metadata types supported by Calais, a preprocessed a sample content set of about 350 Business and Economic news articles from WikiNews for the year 2007 is available.
The service is free for both commercial and non-commercial purposes with a limit, but a generous one, on the number of service calls a registered developer can make in a day. A sample Java application is available that reads input from STDIN, writes output to STDOUT and takes processing parameters from a configuration file.
updates: The sample application requires Java 6 to run! Here’s an example of input and the RDF output.
Making such a service freely available on the Web has the potential to be a disruptive move. Reuters will sponsor “a number of contests and bounties for applications developed using the Calais API.” An initial “bounty” of $5,000 is offered for “A highly configurable plugin for WordPress that enriches a blog with several capabilities” based on OpenCalais.
The kind of content extraction that Calias does falls considerably short of full language understanding. However, it does represent the state of the art in scalable, domain-independent information extraction, is immediately useful, and an important step toward the ultimate goal of full NLP.
January 18th, 2008, by Tim Finin, posted in GENERAL, OWL, RDF, Semantic Web, Social media
ReadWriteWeb reports that Project10X has released a 400 page report entitled Semantic Wave 2008 Report: Industry Roadmap to Web 3.0 and Multibillion Dollar Market Opportunities. The full report will set you back $3,495, but you can get a free 27 page executive summary, a $235 value. Project10X describes their Semantic Wave report as follows.
“It is the first comprehensive industry study of the next stage of internet evolution â€” Web 3.0. This landmark 400-page report is written for executives, developers, designers, entrepreneurs, investors, and others who want to better understand semantic technologies, the business opportunities they present, and the ways Web 3.0 will change how we use and experience the internet. The semantic wave is a â€œlong waveâ€ of innovation and investment that will bring fundamental shifts in paradigm, technology, and economics. Over the next decade semantic technologies will drive trillion dollar global economic expansions, transforming industries as well as our experience of the internet. ”
The report also includes a supplier directory with more than 270 companies that are researching and developing semantic technology products and services and an annotated bibliography.
February 9th, 2006, by Tim Finin, posted in GENERAL, OWL, RDF, Semantic Web, Web
Peter Patel-Schneider gave a talk on the Semantic Web at Google several weeks ago and you can see the video here. The abstract:
“The Semantic Web has been attracting considerable attention the last few years. From the point of view of Knowledge Representation, the Semantic Web affords opportunities for both research and application. However, several aspects of the Semantic Web, as it has been envisioned, cause problems from the Knowledge Representation viewpoint. Overcoming some of these problems has resulted in a more formal basis for the Semantic Web and an increase in expressive power in Semantic Web languages. Other of these problems still remain and need a new vision of the Semantic Web from a Knowledge Representation viewpoint.”
Spotted on the SWIG Scratchpad.
February 6th, 2006, by Tim Finin, posted in OWL, RDF, Semantic Web, Swoogle, Web
Sometime today the UMBC Swoogle Semantic Web search engine discovered and indexed its millionth document. Of these, about 77% are valid RDF documents, 15% HTML documents with embedded RDF and 8% appear to be RDF documents but can not be parsed.