January 30th, 2014
Today’s online meeting (Jan 30, 12:30-2:30 EST) in the 2014 Ontology Summit series is part of the Tools, Services, and Techniques track and features presentations by
- Dr. ChrisWelty (IBM Research) on “Inside the Mind of Watson – a Natural Language Question Answering Service Powered by the Web of Data and Ontologies”
- Prof. AlanRector (U. Manchester) on “Axioms & Templates: Distinctions and Transformations amongst Ontologies, Frames, & Information Models
- Professor TillMossakowski (U. Magdeburg) on “Challenges in Scaling Tools for Ontologies to the Semantic Web: Experiences with Hets and OntoHub”
Audio via phone (206-402-0100) or Skype. See the session page for details and access to slides.
January 23rd, 2014
The first online session of the 2014 Ontology Summit on “Big Data and Semantic Web Meet Applied Ontology” takes place today (Thurday January 23) from 12:30pm to 2:30pm (EST, UTC-5) with topic Common Reusable Semantic Content — The Problems and Efforts to Address Them. The session will include four presentations:
followed by discussion.
Audio connection is via phone (206-402-0100, 141184#) or Skype with a shared screen and participant chatroom. See the session page for more details.
January 18th, 2014
A free PDF version of the new second edition of Mining of Massive Datasets by Anand Rajaraman, Jure Leskovec and Jeffey Ullman is available. New chapters on mining large graphs, dimensionality reduction, and machine learning have been added. Related material from Professor Leskovec’s recent Stanford course on Mining Massive Data Sets is also available.
January 14th, 2014
The ninth Ontology Summit starts on Thursday, January 16 with the theme “Big Data and Semantic Web Meet Applied Ontology.” The event kicks off a three month series of weekly online meetings on Thursdays that feature presentations from expert panels and discussions with all of the participants. The series will culminate with a two day symposium on April 28-29 in Arlington VA. The sessions are free and open to all, including researchers, practitioners and students.
The first virtual meeting will be held 12:30-
2:00 2:30 (EST) on Thursday, January 16 and will introduce the nine different topical tracks in the series, their goals and organizers. Audio connection is via phone (206-402-0100, 141184#) or Skype with a shared screen and participant chatroom. See the session page for more details.
This year’s Ontology Summit is an opportunity for building bridges between the Semantic Web, Linked Data, Big Data, and Applied Ontology communities. On the one hand, the Semantic Web, Linked Data, and Big Data communities can bring a wide array of real problems (such as performance and scalability challenges and the variety problem in Big Data) and technologies (automated reasoning tools) that can make use of ontologies. On the other hand, the Applied Ontology community can bring a large body of common reusable content (ontologies) and ontological analysis techniques. Identifying and overcoming ontology engineering bottlenecks is critical for all communities.
The 2014 Ontology Summit is chaired by Michael Gruninger and Leo Obrst.
January 9th, 2014
Computer Science and Electrical Engineering
University of Maryland, Baltimore County
Ph.D. Dissertation Proposal
Functional Reference Ontology Development:
a Design Pattern Approach
1:00pm Friday, January 10, 2014, ITE325b, UMBC
The next generation of smart manufacturing systems will be developed by composing advanced manufacturing components and IT services introducing new technologies. These new technologies can lead to dramatic improvements in the ability to monitor, control, and optimize all aspects of manufacturing. The ability to compose advanced manufacturing components and IT services enhances agility, resiliency, and productivity of a manufacturing system. In order to make the composition possible, functional knowledge of manufacturing components and IT services should be captured and shared explicitly. Recent researches have shown that a semantically precise and rich reference functional ontology enables effective composition. However, since domains of factories and production networks are large, evolving, and heterogeneous, developing a reference functional ontology is a challenging task. Specifically, conceptual functionality modeling that characterizes various features of manufacturing components and IT services at different levels of abstraction is a difficult task. Even if the reference functional ontology is developed successfully, there will certainly be interoperability issues between the reference functional ontology and local proprietary information models. Firstly, the conceptual conflict issues may arise primarily from the fact that the reference functional ontology does not reflect actual users’ or providers’ conceptualizations. Secondly, structural conflict issues may arise from diverse modeling choices in local, proprietary information models.
The objective of our research is to assess utility of design patterns in addressing the issues in the reference functional ontology development, specifically OWL ontology design patterns (ODPs). To achieve the objective, we will assess inductive approaches to identifying the ODPs, and explore development of a methodology for resolving structural differences between the reference functional ontology and local proprietary information models. The key potential contributions of this work include 1) new method to identify information patterns of functionalities in manufacturing components and IT services, 2) new inductive ODP development process which starts with the pattern definition of the specific functionality concepts, with subsequent grouping of these patterns into more general patterns, and 3) ODP-based ontology transformation to resolve structural conflicts between the reference functional ontology and local proprietary information models.
Committee: Drs. Yun Peng (chair), Tim Finin, Yelena Yesha, Milton Halem, Nenad Ivezic (NIST) and Boonserm Kulvatunyou (NIST)
January 1st, 2014
“The app uses browser’s geolocation feature to find user’s location and displays a map of interesting objects that can be found nearby (within 50 000 ft). It uses the Freebase Search API to find relevant objects. When user clicks on one of the markers, the app calls the Freebase Topic API to fetch more information about that object. Once the information is retrieved, it populates a purejs template to display a knowledge card for the user.”
This sort of application has been done many times before with RDF and the Google approach can be adapted to query an arbitrary RDF resource for custom knowledge bases.