1,457 research outputs found
Collaboration in the Semantic Grid: a Basis for e-Learning
The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning
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J-Park Simulator: An ontology-based platform for cross-domain scenarios in process industry
The J-Park Simulator (JPS) acts as a continuously growing platform for integrating real-time data, knowledge, models, and tools related to process industry. It aims at simulation and optimization in cross-domain and multi-level scenarios and relies heavily on ontologies and semantic technologies. In this paper, we demonstrate the interoperability between different applications in JPS, introduce new domain ontologies into the JPS, and integrate live data. For this, we utilize a knowledge graph to store and link semantically described data and models and create agents wrapping the applications and updating the data in the knowledge graph dynamically. We present a comprehensive industrial air pollution scenario, which has been implemented as part of the JPS, to show how knowledge graphs and modular domain ontologies support the interoperability between agents. We show that the architecture of JPS increases the interoperability and flexibility in cross-domain scenarios and conclude that the potential of ontologies outweighs additional wrapping efforts.National Research Foundation (NRF)Accepted versionThis project is funded by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. MK gratefully acknowledges the support of the Alexander von Humboldt foundation
GELCO: Gamified Educational Learning Contents Ontology
Higher education students and teachers lack the necessary information to monitor and analyse student performance with respect to the learning experience and autonomous work during the semester. This research is based on the need for continuous improvement of student learning monitoring for students and teachers. It aims to combine ontologies with a monitoring platform, creating new ways of structuring and visualizing the elements of a course unit, of mapping and visualizing the dependencies between taught concepts and coursework, enabling the inference of new knowledge. The Gamified Educational Learning Contents Ontology (GELCO) was designed to define educational concepts and respective relations. A Syllabus Content Mindmap was developed within the Learning Scorecard, an academic performance management platform based on Business Intelligence and Gamification, taking advantage of the knowledge from GELCO. The ontology was successfully evaluated with competency questions, and students found the mindmap visualization useful and valuable for their academic performance monitoring
VOSD: a general-purpose virtual observatory over semantic databases
E-Science relies heavily on manipulating massive amounts of data for research purposes. Researchers should be able to contribute their own data and methods, thus making their results accessible and reproducible by others worldwide. They need an environment which they can use anytime and anywhere to perform data-intensive computations. Virtual observatories serve this purpose. With the advance of the Semantic Web, more and more data is available in Resource Description Framework based databases. It is often desirable to have the ability to link data from local sources to these public data sets. We present a prototype system, which satisfies the requirements of a virtual observatory over semantic databases, such as user roles, data import, query execution, visualization, exporting result, etc. The system has special features which facilitate working with semantic data: visual query editor, use of ontologies, knowledge inference, querying remote endpoints, linking remote data with local data, extracting data from web pages
Modeling an ontology on accessible evacuation routes for emergencies
Providing alert communication in emergency situations is vital to reduce the number of victims. However, this is a challenging goal for researchers and professionals due to the diverse pool of prospective users, e.g. people with disabilities as well as other vulnerable groups. Moreover, in the event of an emergency situation, many people could become vulnerable because of exceptional circumstances such as stress, an unknown environment or even visual impairment (e.g. fire causing smoke). Within this scope, a crucial activity is to notify affected people about safe places and available evacuation routes. In order to address this need, we propose to extend an ontology, called SEMA4A (Simple EMergency Alert 4 [for] All), developed in a previous work for managing knowledge about accessibility guidelines, emergency situations and communication technologies. In this paper, we introduce a semi-automatic technique for knowledge acquisition and modeling on accessible evacuation routes. We introduce a use case to show applications of the ontology and conclude with an evaluation involving several experts in evacuation procedures. © 2014 Elsevier Ltd. All rights reserved
Cyber-Virtual Systems: Simulation, Validation & Visualization
We describe our ongoing work and view on simulation, validation and
visualization of cyber-physical systems in industrial automation during
development, operation and maintenance. System models may represent an existing
physical part - for example an existing robot installation - and a software
simulated part - for example a possible future extension. We call such systems
cyber-virtual systems.
In this paper, we present the existing VITELab infrastructure for
visualization tasks in industrial automation. The new methodology for
simulation and validation motivated in this paper integrates this
infrastructure. We are targeting scenarios, where industrial sites which may be
in remote locations are modeled and visualized from different sites anywhere in
the world.
Complementing the visualization work, here, we are also concentrating on
software modeling challenges related to cyber-virtual systems and simulation,
testing, validation and verification techniques for them. Software models of
industrial sites require behavioural models of the components of the industrial
sites such as models for tools, robots, workpieces and other machinery as well
as communication and sensor facilities. Furthermore, collaboration between
sites is an important goal of our work.Comment: Preprint, 9th International Conference on Evaluation of Novel
Approaches to Software Engineering (ENASE 2014
Smart Intrusion Detection System for DMZ
Prediction of network attacks and machine understandable security vulnerabilities are complex tasks for current available Intrusion Detection System [IDS]. IDS software is important for an enterprise network. It logs security information occurred in the network. In addition, IDSs are useful in recognizing malicious hack attempts, and protecting it without the need for change to
client‟s software. Several researches in the field of machine learning have been applied to make these IDSs better a d smarter. In our work, we propose approach for making IDSs more analytical, using semantic technology. We made a useful semantic connection between IDSs and National Vulnerability Databases [NVDs], to make the system semantically analyzed each attack logged, so it can perform prediction about incoming attacks or services that might be in danger. We built our ontology skeleton based on standard network security. Furthermore, we added useful classes and relations that are specific for DMZ network services. In addition, we made an option to mallow the user to update the ontology skeleton automatically according to the network needs. Our work is evaluated and validated using four different methods: we presented a prototype that works over the web. Also, we applied KDDCup99 dataset to the prototype. Furthermore,we modeled our system using queuing model, and simulated it using Anylogic simulator. Validating the system using KDDCup99 benchmark shows good results law false positive attacks prediction. Modeling the system in a queuing model allows us to predict the behavior of the system in a multi-users system for heavy network traffic
Visualization for Biological Models, Simulation, and Ontologies
In this dissertation, I present three browsers that I have developed for the purpose
of exploring, understanding, and analyzing models, simulations, and ontologies in
biology and medicine. The first browser visualizes multidimensional simulation data
as an animation. The second browser visualizes the equations of a complex model as
a network and puts structure and organization on top of equations and variables. The
third browser is an ontology viewer and editor, directly intended for the Foundational
Model of Anatomy (FMA), but applicable to other ontologies as well. This browser
has two contributions. First, it is a lightweight deliverable that lets someone easily
dabble with the FMA. Second, it lets the user edit an ontology to create a view of
it. For the ontology browser, I also conduct user studies to refine and evaluate the
software
District data management, modelling and visualization via interoperability
Data management has been one of the most interesting research fields within the smart city framework over the last years, with the aim of optimizing energy saving at district level. This topic involves the creation of a 3D city model considering heterogeneous datasets, such as Building Information Models (BIMs), Geographical Information Systems (GISs) and System Information Models (SIMs), taking into account both buildings and the energy network. Through the creation of a common platform, the data sharing was allowed starting from the needs of the users, such as the public administrator, the building manager and the energy professional. For this reason, the development of a District Information Modelling (DIM) methodology for the data management, related to the energy saving and CO2 emission, is considered the focus of this paper. It also presents a specific tool developed for the comparison of energy data in a selected district: the Benchmarking Tool
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