A novel approach to provenance management for privacy preservation

2019 ◽  
Vol 46 (2) ◽  
pp. 147-160
Author(s):  
Ozgu Can ◽  
Dilek Yilmazer
Keyword(s):  
Privacy Preservation ◽  
Quality Of Data ◽  
Semantic Web Technologies ◽  
Provenance Information ◽  
Web Technologies ◽  
Provenance Management ◽  
Novel Approach ◽  
Provenance Data ◽  
Domain Independent

Provenance determines the origin of the data by tracing and recording the actions that are performed on the data. Therefore, provenance is used in many fields to ensure the reliability and quality of data. In this work, provenance information is used to meet the security needs in information systems. For this purpose, a domain-independent provenance model is proposed. The proposed provenance model is based on the Open Provenance Model and Semantic Web technologies. The goal of the proposed provenance model is to integrate the provenance and security concepts in order to detect privacy violations by querying the provenance data. In order to evaluate the proposed provenance model, we illustrated our domain-independent model by integrating it with an infectious disease domain and implemented the Healthcare Provenance Information System.

Semantic Web Technologies in the Service of Personalization Tools

2010 ◽  
pp. 68-87 ◽  
Author(s):  
Yolanda Blanco-Fernández ◽  
José J. Pazos-Arias ◽  
Alberto Gil-Solla
Keyword(s):  
Semantic Web ◽  
Recommender Systems ◽  
Information Overload ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Manual Search ◽  
Novel Approach ◽  
Search Processes ◽  
Matching Techniques

The so-called recommender systems have become assistance tools indispensable to the users in domains where the information overload hampers manual search processes. In literature, diverse personalization paradigms have been proposed to match automatically the preferences of each user (which are previously modelled in personal profiles) against the available items. All these paradigms are laid down on a common substratum that uses syntactic matching techniques, which greatly limit the quality of the offered recommendations due to their inflexible nature. To fight these limitations, this chapter explores a novel approach based on reasoning about the semantics of both the users’ preferences and considered items, by resorting to less rigid inference mechanisms borrowed from the Semantic Web.

Ontology Alignment Quality

2011 ◽  
Vol 2 (3) ◽  
pp. 1-23 ◽  
Author(s):  
Jennifer Sampson ◽  
John Krogstie ◽  
Csaba Veres
Keyword(s):  
Semantic Web ◽  
Promising Result ◽  
Heterogeneous Data ◽  
Ontology Alignment ◽  
Alignment Quality ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Automated Tools ◽  
Tools And Techniques

Recently semantic web technologies, such as ontologies, have been proposed as key enablers for integrating heterogeneous data schemas in business and governmental systems. Algorithms designed to align different but related ontologies have become necessary as differing ontologies proliferate. The process of ontology alignment seeks to find corresponding entities in a second ontology with the same or the closest meaning for each entity in a single ontology. This research is motivated by the need to provide tools and techniques to support the task of validating ontology alignment statements, since it cannot be guaranteed that the results from automated tools are accurate. The authors present a framework for understanding ontology alignment quality and describe how AlViz, a tool for visual ontology alignment, may be used to improve the quality of alignment results. An experiment was undertaken to test the claim that AlViz supports the task of validating ontology alignments. A promising result found that the tool has potential for identifying missing alignments and for rejecting false alignments.

Ontology Alignment Quality

2013 ◽  
pp. 99-122
Author(s):  
Jennifer Sampson ◽  
John Krogstie ◽  
Csaba Veres
Keyword(s):  
Semantic Web ◽  
Promising Result ◽  
Heterogeneous Data ◽  
Ontology Alignment ◽  
Alignment Quality ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Automated Tools ◽  
Tools And Techniques

Recently semantic web technologies, such as ontologies, have been proposed as key enablers for integrating heterogeneous data schemas in business and governmental systems. Algorithms designed to align different but related ontologies have become necessary as differing ontologies proliferate. The process of ontology alignment seeks to find corresponding entities in a second ontology with the same or the closest meaning for each entity in a single ontology. This research is motivated by the need to provide tools and techniques to support the task of validating ontology alignment statements, since it cannot be guaranteed that the results from automated tools are accurate. The authors present a framework for understanding ontology alignment quality and describe how AlViz, a tool for visual ontology alignment, may be used to improve the quality of alignment results. An experiment was undertaken to test the claim that AlViz supports the task of validating ontology alignments. A promising result found that the tool has potential for identifying missing alignments and for rejecting false alignments.

A semantic-based approach for querying linked data using natural language

2016 ◽  
Vol 42 (6) ◽  
pp. 851-862 ◽  
Author(s):  
Mario Andrés Paredes-Valverde ◽  
Rafael Valencia-García ◽  
Miguel Ángel Rodríguez-García ◽  
Ricardo Colomo-Palacios ◽  
Giner Alor-Hernández
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Knowledge Bases ◽  
Semantic Knowledge ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Natural Language Interface ◽  
High Quality Information ◽  
Domain Independent

The semantic Web aims to provide to Web information with a well-defined meaning and make it understandable not only by humans but also by computers, thus allowing the automation, integration and reuse of high-quality information across different applications. However, current information retrieval mechanisms for semantic knowledge bases are intended to be only used by expert users. In this work, we propose a natural language interface that allows non-expert users the access to this kind of information through formulating queries in natural language. The present approach uses a domain-independent ontology model to represent the question’s structure and context. Also, this model allows determination of the answer type expected by the user based on a proposed question classification. To prove the effectiveness of our approach, we have conducted an evaluation in the music domain using LinkedBrainz, an effort to provide the MusicBrainz information as structured data on the Web by means of Semantic Web technologies. Our proposal obtained encouraging results based on the F-measure metric, ranging from 0.74 to 0.82 for a corpus of questions generated by a group of real-world end users.

scholarly journals Information-Balance-Aware Approximated Summarization of Data Provenance

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Jisheng Pei ◽  
Xiaojun Ye
Keyword(s):  
Case Studies ◽  
Data Provenance ◽  
User Requirements ◽  
Provenance Information ◽  
Useful Knowledge ◽  
Amount Of Information ◽  
Provenance Data ◽  
Intended Use ◽  
Balance Index

Extracting useful knowledge from data provenance information has been challenging because provenance information is often overwhelmingly enormous for users to understand. Recently, it has been proposed that we may summarize data provenance items by grouping semantically related provenance annotations so as to achieve concise provenance representation. Users may provide their intended use of the provenance data in terms of provisioning, and the quality of provenance summarization could be optimized for smaller size and closer distance between the provisioning results derived from the summarization and those from the original provenance. However, apart from the intended provisioning use, we notice that more dedicated and diverse user requirements can be expressed and considered in the summarization process by assigning importance weights to provenance elements. Moreover, we introduce information balance index (IBI), an entropy based measurement, to dynamically evaluate the amount of information retained by the summary to check how it suits user requirements. An alternative provenance summarization algorithm that supports manipulation of information balance is presented. Case studies and experiments show that, in summarization process, information balance can be effectively steered towards user-defined goals and requirement-driven variants of the provenance summarizations can be achieved to support a series of interesting scenarios.

scholarly journals Qualitative Collaborative Sensing In Smart Phone Based Wireless Sensor Networks

2019 ◽  
Vol 8 (3S2) ◽  
pp. 476-479
Keyword(s):  
Data Collection ◽  
Qualitative Data ◽  
Smart Phone ◽  
Estimation Algorithm ◽  
Quality Of Data ◽  
Anomalous Data ◽  
Novel Approach ◽  
Collaborative Sensing ◽  
Human Participants

Collaborative sensing has become a novel approach for smart phone based data collection. In this process individuals contributes to the participatory data collection by sharing the data collected using their smart phone sensors. Since the data is gathered by human participants it is difficult to guarantee the Quality of the data received. Mobility of the participant and accuracy of the sensor also matters for the quality of data shared in such environment. If the data shared by such participants are of low quality the purpose of collaborative sensing fails. So there must be approach to gather good quality of data from participants. In this paper we propose a Truth Estimation Algorithm (TEA) to identify the truth value of the data received and filter out anomalous data items to improve the quality of data. To encourage the participants to share quality information we also propose an Incentive Allocation Algorithm (IAA) for qualitative data collection.

LAS

2018 ◽  
pp. 56-93 ◽  
Author(s):  
Alessandro Fiori ◽  
Alberto Grand ◽  
Emanuele Geda ◽  
Domenico Schioppa ◽  
Francesco G. Brundu ◽  
...  
Keyword(s):  
Biological Samples ◽  
Tumor Development ◽  
Clinical History ◽  
Heterogeneous Data ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Genomic Annotation ◽  
Insight Into ◽  
Support Decision Making

Rapid technological evolution is providing biomedical research laboratories with huge amounts of complex and heterogeneous data. The LIMS project Laboratory Assistant Suite (LAS), started by our Institution, aims to assist researchers throughout all of their laboratory activities, providing graphical tools to support decision-making tasks and building complex analyses on integrated data. Thanks to a clinical data management module, linking biological samples analysed by translational research with the originating patients and their clinical history, it can effectively provide insight into tumor development. Furthermore, the LAS tracks molecular experiments and allows automatic annotation of biological samples with their molecular results. A genomic annotation module makes use of semantic web technologies to represent relevant concepts from the genomic domain. The LAS system has helped improve the overall quality of the data and broadened the spectrum of interconnections among the data, offering novel perspectives to the biomedical analyst.

PINATA

2015 ◽  
pp. 664-687
Author(s):  
Alexiei Dingli ◽  
Charlie Abela ◽  
Ilenia D'Ambrogio
Keyword(s):  
Medical Staff ◽  
Ambient Intelligence ◽  
Quality Of Healthcare ◽  
Healthcare Services ◽  
Handheld Devices ◽  
Semantic Web Technologies ◽  
Camera System ◽  
Web Technologies ◽  
Quality In Healthcare

Owing to growing population health needs, the proportion of medical staff to patients keeps diminishing; yet, the quality in healthcare services is likely to increase. Through the amalgamation of Ambient Intelligence (AmI) and Semantic Web technologies, PINATA seeks to deal with this issue. To perk up the quality of healthcare services, PINATA utilises pervasive devices to help doctors and nurses to concentrate on the patient. The movement of medical staff and patients is tracked by means of Wi-Fi sensors whilst an automated camera system monitors the interaction of people within their environment. The system operates autonomously in response to particular situations by guiding medical staff towards emergencies in a timely manner and providing them with the information they require on their handheld devices. This assures that patients are given the best possible attention on a 24/7 basis especially when the medical staff is not nearby.

Disability vs. Smart Environments

2010 ◽  
pp. 190-213
Author(s):  
Rachid Kadouche ◽  
Bessam Abdulrazak
Keyword(s):  
Description Logic ◽  
Smart Environments ◽  
Environment Interaction ◽  
Semantic Matching ◽  
Smart Environment ◽  
Semantic Web Technologies ◽  
Human Environment ◽  
Web Technologies ◽  
Daily Life Activities ◽  
Novel Approach

This chapter discusses a novel approach to manage the human environment interaction in case of disability. It provides accessible services to the user in smart environment. This approach is based on the user limitation capabilities (“handicap situations”) in smart environment. It is built upon formalisms based on S??T(?) Description logic (DL) named Semantic Matching Framework (SMF). The architecture of SMF is designed in a way that Human-Environment Interaction (HEI) is generated online to identify and compensate the handicap situation occurring in the course of daily life activities. The SMF architecture is based on modules and implemented using semantic web technologies and integrated into a demonstrator, which has been used to validate the concept in laboratory conditions. The chapter includes the time response and the scalability analysis of SMF.

scholarly journals Personalized Recommendation of Learning Objects Through Bio-inspired Algorithms and Semantic Web Technologies: an Experimental Analysis

2020 ◽  
Author(s):  
Cleon Pereira Júnior ◽  
Clarivando Francisco Belizário Júnior ◽  
Rafael D. Araújo ◽  
Fabiano A. Dorça
Keyword(s):  
Semantic Web ◽  
Experimental Analysis ◽  
Automatic Generation ◽  
Learning Objects ◽  
Personalized Recommendation ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Web Resources ◽  
The Web

The emerging need to explore the Web as a learning source allied with the purpose of providing personalized recommendations is a tough task. Considering this scenario, this work presents an approach that combines Semantic Web technologies and bio-inspired algorithms to perform personalized recommendation of Learning Objects (LOs) using local repositories and Web resources. Web resources are retrieved and structured as LOs, which allows for the automatic generation of metadata, minimizing course tutors' work. Experiments were performed to verify which bio-inspired evolutionary algorithm would be most appropriate in this context. Also, discussions regarding the quality of recommendations considering local repositories and Web have been made. Initial experiments evaluating the efficiency of the proposed approach have shown promising results.

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