23,467 research outputs found
Recommended from our members
Investigating the use of background knowledge for assessing the relevance of statements to an ontology in ontology evolution
The tasks of learning and enriching ontologies with new concepts and relations have attracted a lot of attention in the research community, leading to a number of tools facilitating the process of building and updating ontologies. These tools often discover new elements of information to be included in the considered ontology from external data sources such as text documents or databases, transforming these elements into ontology compatible statements or axioms. While some techniques are used to make sure that statements to be added are compatible with the ontology (e.g. through conflict detection), such tools generally pay little attention to the relevance of the statement in question. It is either assumed that any statement extracted from a data source is relevant, or that the user will assess whether a statement adds value to the ontology. In this paper, we investigate the use of background knowledge about the context where statements appear to assess their relevance. We devise a methodology to extract such a context from ontologies available online, to map it to the considered ontology and to visualize this mapping in a way that allows to study the intersection and complementarity of the two sources of knowledge. By applying this methodology on several examples, we identified an initial set of patterns giving strong indications concerning the relevance of a statement, as well as interesting issues to be considered when applying such techniques
Using Ontologies for the Design of Data Warehouses
Obtaining an implementation of a data warehouse is a complex task that forces
designers to acquire wide knowledge of the domain, thus requiring a high level
of expertise and becoming it a prone-to-fail task. Based on our experience, we
have detected a set of situations we have faced up with in real-world projects
in which we believe that the use of ontologies will improve several aspects of
the design of data warehouses. The aim of this article is to describe several
shortcomings of current data warehouse design approaches and discuss the
benefit of using ontologies to overcome them. This work is a starting point for
discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure
Context for Ubiquitous Data Management
In response to the advance of ubiquitous computing technologies, we believe that for computer systems to be ubiquitous, they must be context-aware. In this paper, we address the impact of context-awareness on ubiquitous data management. To do this, we overview different characteristics of context in order to develop a clear understanding of context, as well as its implications and requirements for context-aware data management. References to recent research activities and applicable techniques are also provided
A lightweight web video model with content and context descriptions for integration with linked data
The rapid increase of video data on the Web has warranted an urgent need for effective representation, management and retrieval of web videos. Recently, many studies have been carried out for ontological representation of videos, either using domain dependent or generic schemas such as MPEG-7, MPEG-4, and COMM. In spite of their extensive coverage and sound theoretical grounding, they are yet to be widely used by users. Two main possible reasons are the complexities involved and a lack of tool support. We propose a lightweight video content model for content-context description and integration. The uniqueness of the model is that it tries to model the emerging social context to describe and interpret the video. Our approach is grounded on exploiting easily extractable evolving contextual metadata and on the availability of existing data on the Web. This enables representational homogeneity and a firm basis for information integration among semantically-enabled data sources. The model uses many existing schemas to describe various ontology classes and shows the scope of interlinking with the Linked Data cloud
New program with new approach for spectral data analysis
This article presents a high-throughput computer program, called EasyDD, for
batch processing, analyzing and visualizing of spectral data; particularly
those related to the new generation of synchrotron detectors and X-ray powder
diffraction applications. This computing tool is designed for the treatment of
large volumes of data in reasonable time with affordable computational
resources. A case study in which this program was used to process and analyze
powder diffraction data obtained from the ESRF synchrotron on an alumina-based
nickel nanoparticle catalysis system is also presented for demonstration. The
development of this computing tool, with the associated protocols, is inspired
by a novel approach in spectral data analysis.Comment: 20 pages and 4 figure
Red Queen Coevolution on Fitness Landscapes
Species do not merely evolve, they also coevolve with other organisms.
Coevolution is a major force driving interacting species to continuously evolve
ex- ploring their fitness landscapes. Coevolution involves the coupling of
species fit- ness landscapes, linking species genetic changes with their
inter-specific ecological interactions. Here we first introduce the Red Queen
hypothesis of evolution com- menting on some theoretical aspects and empirical
evidences. As an introduction to the fitness landscape concept, we review key
issues on evolution on simple and rugged fitness landscapes. Then we present
key modeling examples of coevolution on different fitness landscapes at
different scales, from RNA viruses to complex ecosystems and macroevolution.Comment: 40 pages, 12 figures. To appear in "Recent Advances in the Theory and
Application of Fitness Landscapes" (H. Richter and A. Engelbrecht, eds.).
Springer Series in Emergence, Complexity, and Computation, 201
- …