A Novel Approach to Construct Semantic Mashup using Patterns

2017 ◽  
Vol 12 (1) ◽  
pp. 19-36
Author(s):  
Khayra Bencherif ◽  
Djamel Amar Bensaber ◽  
Mimoun Malki
Keyword(s):  
User Interface ◽  
Data Integration ◽  
Web 2.0 ◽  
Travel Agency ◽  
Use Case ◽  
Web Resources ◽  
Single Interface ◽  
Automatic Integration ◽  
Novel Approach ◽  
Automatic Matching

With the coming of Web 2.0, several technologies are developed to facilitate creating, sharing and reusing of web resources. In this context, the mashup is a novel approach that allows the user to aggregate multiples services to create a single one with a new user interface. However, a key limitation of existing mashups applications is the need to compute semantic and syntactic similarities between data in different services and create or modify workflows in applications mashups without enlisting the talents of the original developers or vendor. In fact, automatic matching tools help users to facilitate automatic integration of both data and APIs without knowing their structure and semantics. In this paper, the authors suggest a novel approach which consists in building a semantic mashup using a matching tool, domain ontology and a set of patterns to facilitate and automate services and data integration. As a study use case, they develop a semantic mashup application for a travel agency that provides a single interface to users.

Integrating Heterogeneous Services for Semantic Mashup Construction

2018 ◽  
pp. 362-386
Author(s):  
Khayra Bencherif ◽  
Djamel Amar Bensaber ◽  
Mimoun Malki
Keyword(s):  
User Interface ◽  
Data Integration ◽  
User Interfaces ◽  
Domain Ontology ◽  
Travel Agency ◽  
Use Case ◽  
Data Services ◽  
Matching Methods ◽  
Heterogeneous Services

Semantic mashup applications allow automating the process of services and data integration to create a composite application with a new user interface. Nevertheless, existing mashup applications need to improve the matching methods for discovering semantic services. Moreover, they have to create or modify workflows in mashup applications without the assistance of the original developers. Automating the combination of user interfaces is another challenge in the context of semantic mashups construction. In this chapter, the authors propose an approach that allows automating the combination of data, services, and user interfaces to provide a composite application with an enhanced user interface. The construction of the semantic mashup application is based on the use of domain ontology, a matching tool, and a collection of patterns. In order to demonstrate the effectiveness of this proposal, the authors present a use case to construct a semantic mashup application for a travel agency.

scholarly journals MuSA: a graphical user interface for multi-OMICs data integration in radiogenomic studies

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mario Zanfardino ◽  
Rossana Castaldo ◽  
Katia Pane ◽  
Ornella Affinito ◽  
Marco Aiello ◽  
...  
Keyword(s):  
User Interface ◽  
Data Integration ◽  
Graphical User Interface ◽  
Data Science ◽  
Heterogeneous Data ◽  
Biological Information ◽  
Omics Data ◽  
Correlation Clustering ◽  
Downstream Analysis ◽  
Omics Data Integration

AbstractAnalysis of large-scale omics data along with biomedical images has gaining a huge interest in predicting phenotypic conditions towards personalized medicine. Multiple layers of investigations such as genomics, transcriptomics and proteomics, have led to high dimensionality and heterogeneity of data. Multi-omics data integration can provide meaningful contribution to early diagnosis and an accurate estimate of prognosis and treatment in cancer. Some multi-layer data structures have been developed to integrate multi-omics biological information, but none of these has been developed and evaluated to include radiomic data. We proposed to use MultiAssayExperiment (MAE) as an integrated data structure to combine multi-omics data facilitating the exploration of heterogeneous data. We improved the usability of the MAE, developing a Multi-omics Statistical Approaches (MuSA) tool that uses a Shiny graphical user interface, able to simplify the management and the analysis of radiogenomic datasets. The capabilities of MuSA were shown using public breast cancer datasets from TCGA-TCIA databases. MuSA architecture is modular and can be divided in Pre-processing and Downstream analysis. The pre-processing section allows data filtering and normalization. The downstream analysis section contains modules for data science such as correlation, clustering (i.e., heatmap) and feature selection methods. The results are dynamically shown in MuSA. MuSA tool provides an easy-to-use way to create, manage and analyze radiogenomic data. The application is specifically designed to guide no-programmer researchers through different computational steps. Integration analysis is implemented in a modular structure, making MuSA an easily expansible open-source software.

scholarly journals Leveraging Graphical User Interface Automation for Generic Robot Programming

Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Tudor B. Ionescu
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Programming Models ◽  
Shop Floor ◽  
Robot Programming ◽  
User Interactions ◽  
Programming Environments ◽  
Automated Generation ◽  
Novel Approach ◽  
Block Based

A novel approach to generic (or generalized) robot programming and a novel simplified, block-based programming environment, called “Assembly”, are introduced. The approach leverages the newest graphical user interface automation tools and techniques to generate programs in various proprietary robot programming environments by emulating user interactions in those environments. The “Assembly” tool is used to generate robot-independent intermediary program models, which are translated into robot-specific programs using a graphical user interface automation toolchain. The generalizability of the approach to list, tree, and block-based programming is assessed using three different robot programming environments, two of which are proprietary. The results of this evaluation suggest that the proposed approach is feasible for an entire range of programming models and thus enables the generation of programs in various proprietary robot programming environments. In educational settings, the automated generation of programs fosters learning different robot programming models by example. For experts, the proposed approach provides a means for generating program (or task) templates, which can be adjusted to the needs of the application at hand on the shop floor.

Bubble Journey: Multimodal Input Tools Design to Augment Sense Experience in Computer Game

2010 ◽  
Vol 102-104 ◽  
pp. 326-330
Author(s):  
Fang Tian Ying ◽  
Peng Cheng Zhu ◽  
Mi Lan Ye ◽  
Jing Chang Chen ◽  
Zhao He ◽  
...  
Keyword(s):  
User Interface ◽  
Daily Life ◽  
Computer Game ◽  
Tangible User Interface ◽  
Digital Signals ◽  
Sense Experience ◽  
Digital World ◽  
Input Design ◽  
Novel Approach ◽  
Five Senses

In this paper, we discuss a novel approach to multimodal input design in Tangible User Interface (TUI). We present a prototype Bubble Journey, a game platform where users control the avatar in flash game by blowing a real handle. This computer game was combined multimodal input tool embedded sensor, which augment experience of user’s (children’s) five senses and body into game’s digital world with previous experience in daily life. Sensor embodied in multimodal input tool can convert data of sounds and movements produced by users (children) into digital signals to manipulate the virtual characters’ performance in the game.

A NOVEL APPROACH FOR SEMANTIC WEB APPLICATION IN ONLINE EDUCATION BASED ON STEGANOGRAPHY

2022 ◽  
Vol 17 (4) ◽  
pp. 0-0
Keyword(s):  
Online Education ◽  
Semantic Web ◽  
Web 2.0 ◽  
Language Processing ◽  
Web Application ◽  
Information Needs ◽  
Extensive Literature ◽  
Web 3.0 ◽  
Novel Approach ◽  
Current Concerns

Semantic Web technology is not new as most of us contemplate; it has evolved over the years. Linked Data web terminology is the name set recently to the Semantic Web. Semantic Web is a continuation of Web 2.0 and it is to replace existing technologies. It is built on Natural Language processing and provides solutions to most of the prevailing issues. Web 3.0 is the version of Semantic Web caters to the information needs of half of the population on earth. This paper links two important current concerns, the security of information and enforced online education due to COVID-19 with Semantic Web. The Steganography requirement for the Semantic web is discussed elaborately, even though encryption is applied which is inadequate in providing protection. Web 2.0 issues concerning online education and semantic Web solutions have been discussed. An extensive literature survey has been conducted related to the architecture of Web 3.0, detailed history of online education, and Security architecture. Finally, Semantic Web is here to stay and data hiding along with encryption makes it robust.

scholarly journals Linking temporal medical records using non-protected health information data

2017 ◽  
Vol 27 (11) ◽  
pp. 3304-3324 ◽  
Author(s):  
Luca Bonomi ◽  
Xiaoqian Jiang
Keyword(s):  
Data Integration ◽  
Health Information ◽  
Record Linkage ◽  
Medical Records ◽  
Data Reuse ◽  
Patient Records ◽  
Protected Health Information ◽  
Integration Process ◽  
Unique Identifier ◽  
Novel Approach

Modern medical research relies on multi-institutional collaborations which enhance the knowledge discovery and data reuse. While these collaborations allow researchers to perform analytics otherwise impossible on individual datasets, they often pose significant challenges in the data integration process. Due to the lack of a unique identifier, data integration solutions often have to rely on patient’s protected health information (PHI). In many situations, such information cannot leave the institutions or must be strictly protected. Furthermore, the presence of noisy values for these attributes may result in poor overall utility. While much research has been done to address these challenges, most of the current solutions are designed for a static setting without considering the temporal information of the data (e.g. EHR). In this work, we propose a novel approach that uses non-PHI for linking patient longitudinal data. Specifically, our technique captures the diagnosis dependencies using patterns which are shown to provide important indications for linking patient records. Our solution can be used as a standalone technique to perform temporal record linkage using non-protected health information data or it can be combined with Privacy Preserving Record Linkage solutions (PPRL) when protected health information is available. In this case, our approach can solve ambiguities in results. Experimental evaluations on real datasets demonstrate the effectiveness of our technique.

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