2,879 research outputs found
How to Find Suitable Ontologies Using an Ontology-based WWW Broker
Knowledge reuse by means of outologies now faces three important problems: (1) there are no standardized identifying features that characterize ontologies from the user point of view; (2) there are no web sites using the same logical organization, presenting relevant information about ontologies; and (3) the search for appropriate ontologies is hard, time-consuming and usually fruitless. To solve the above problems, we present: (1) a living set of features that allow us to characterize ontologies from the user point of view and have the same logical organization; (2) a living domain ontology about ontologies (called ReferenceOntology) that gathers, describes and has links to existing ontologies; and (3) (ONTO)2Agent, the ontology-based www broker about ontologies that uses the Reference Ontology as a source of its knowledge and retrieves descriptions of ontologies that satisfy a given set of constraints. (ONTO)~Agent is available at http://delicias.dia.fi.upm.es/REFERENCE ONTOLOGY
Knowledge-infused and Consistent Complex Event Processing over Real-time and Persistent Streams
Emerging applications in Internet of Things (IoT) and Cyber-Physical Systems
(CPS) present novel challenges to Big Data platforms for performing online
analytics. Ubiquitous sensors from IoT deployments are able to generate data
streams at high velocity, that include information from a variety of domains,
and accumulate to large volumes on disk. Complex Event Processing (CEP) is
recognized as an important real-time computing paradigm for analyzing
continuous data streams. However, existing work on CEP is largely limited to
relational query processing, exposing two distinctive gaps for query
specification and execution: (1) infusing the relational query model with
higher level knowledge semantics, and (2) seamless query evaluation across
temporal spaces that span past, present and future events. These allow
accessible analytics over data streams having properties from different
disciplines, and help span the velocity (real-time) and volume (persistent)
dimensions. In this article, we introduce a Knowledge-infused CEP (X-CEP)
framework that provides domain-aware knowledge query constructs along with
temporal operators that allow end-to-end queries to span across real-time and
persistent streams. We translate this query model to efficient query execution
over online and offline data streams, proposing several optimizations to
mitigate the overheads introduced by evaluating semantic predicates and in
accessing high-volume historic data streams. The proposed X-CEP query model and
execution approaches are implemented in our prototype semantic CEP engine,
SCEPter. We validate our query model using domain-aware CEP queries from a
real-world Smart Power Grid application, and experimentally analyze the
benefits of our optimizations for executing these queries, using event streams
from a campus-microgrid IoT deployment.Comment: 34 pages, 16 figures, accepted in Future Generation Computer Systems,
October 27, 201
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