Semantic Integration

AI Magazine

Sharing data across disparate sources requires solving many problems of semantic integration, such as matching ontologies or schemas, detecting duplicate tuples, reconciling inconsistent data values, modeling complex relations between concepts in different sources, and reasoning with semantic mappings. This issue of AI Magazine includes papers that discuss various methods on establishing mappings between ontology elements or data fragments. The collection includes papers that discuss semantic-integration issues in such contexts as data integration and web services. The issue also includes a brief survey of semantic-integration research in the database community.


Three Semantics for the Core of the Distributed Ontology Language (Extended Abstract)

AAAI Conferences

The Distributed Ontology Language DOL, currently being standardized as ISO WD 17347 within the OntoIOp (Ontology Integration and Interoperability) activity of ISO/TC 37, provides a unified framework for (1) ontologies formalized in heterogeneous logics, (2) modular ontologies, (3) links between ontologies, and (4) ontology annotation. A DOL ontology consists of modules formalized in languages such as OWL or Common Logic, serialized in the existing syntaxes of these languages. On top, DOL’s meta level allows for expressing heterogeneous ontologies and links between ontologies, including (heterogeneous) imports and alignments, conservative extensions, and theory interpretations. We present the abstract syntax of these meta-level constructs, with three alternative semantics: direct, translational, and collapsed semantics.


Evolving Use of Distributed Semantics to Achieve Net-centricity

AAAI Conferences

For the US Department of Defense (DoD)'s efforts to achieve net-centricity, more intelligent ways of handling information must be pursued, in particular using machineinterpretable semantic models, i.e., ontologies. One approach, which we've adopted in current and emerging research projects, is to combine Semantic Web technologies with logic programming, thereby utilizing standards-based ontologies and rules and yet ensuring that the runtime automated reasoning over these is efficient. In this paper, we discuss our current Semantic Environment for Enterprise Reasoning (SEER) architecture, which combines an Enterprise Service Bus (ESB) with our Semantic Web Ontologies and Rules for Interoperability with Efficient Reasoning (SWORIER) system. SWORIER converts OWL ontologies and SWRL rules into logic programming, thereby enabling efficient runtime reasoning using Prolog. We also briefly discuss potential enhancements to such an environment, including the use of constraint logic, metareasoning, and hybrid logic.


Special Track on

AAAI Conferences

By recognizing the need for large domain-independent ontologies, different groups of collaborators from the fields of engineering, philosophy and information science have come to work together to upper-ontologies like CyC. They suggested upper merged ontology or linguistic ontologies as SUMO, DOLCE, and GOLD. These ontologies give a formalized account of the most basic categories and relations used in the scientific description of human language. What are the specific relations between the semantic web and ontologies? What is an ontology of a domain?


Windows Continuum: What happened when I used a Windows 10 phone as my PC

PCWorld

I'm sitting at my desk on a Monday afternoon,ready to smash something. I've spent the past four hours trying to finish a task that usually takes less than half that time. It's the first day in a week where I vowed to work exclusively in Windows 10 Mobile's desktop Continuum mode via my Lumia 950 instead of on my proper PC. Why did I sign up for this again? Because Continuum offers an interesting premise: Instead of toting around a laptop, just plug a phone into an external mouse, keyboard, and monitor to switch to a desktop-like experience.