Ioana Ciuciu

Vrije Universiteit Brussel, Computer Science, Post-Doc

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Bill Hefley

University of Texas at Dallas

Beat Signer

Vrije Universiteit Brussel

Armando Marques-Guedes

UNL - New University of Lisbon

Fausto Fraisopi

Aix-Marseille University

John Sutton

Macquarie University

Sebastian Heath

New York University

Emre San

Istanbul 29 Mayis University

Roshan Chitrakar

Nepal College of Information Technology

Lev Manovich

Graduate Center of the City University of New York

Hatice ŞİRİN

Ege University

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Papers by Ioana Ciuciu

Assessing the User Satisfaction with an Ontology Engineering Tool Based on Social Processes

Lecture Notes in Computer Science, 2012

This study discusses one of the three measures defined within the usability testing, namely the u... more This study discusses one of the three measures defined within the usability testing, namely the user satisfaction, when evaluating an ontology engineering tool based on social processes. The motivation of our focus lays in the fact that being driven by communities through social interactions, the ontology engineering process depends on what the user does, sees and feels when using the system. The evaluation criteria proposed here are therefore developed by looking at the people involved, the processes and their outcomes, mostly taking into account the user experience, in an approach that goes beyond usability. The paper identifies the problems the users encounter when using the system, both at a technical level and psychometric level. A set of recommendations is proposed in order to overcome these problems and to improve the user experience with the system.

PC Med Learner: a personalised and collaborative e-learning materials recommendation system using an ontology-based data matching strategy

International Journal of Knowledge and Learning, 2014

ABSTRACT It is important, in collaborative learning environments, to understand and assess the in... more ABSTRACT It is important, in collaborative learning environments, to understand and assess the intrinsic knowledge of a learner and to share the knowledge within a learning community, in order to improve the learning process. This paper illustrates a framework and a method to recommend learning materials based on the learner&#39;s competencies and a domain ontology, in a collaborative setting. The approach is demonstrated in a learning scenario from medical organisations, when training their prentices. It aims at improving the learning processes by making personalised suggestions on the learning materials. The implementation of the system, the Personal and Collaborative Medical Learner (PC Med Learner) contains three main components: 1) a collaborative knowledge base; 2) an information visualisation tool; 3) an ontology-based data matching strategy, providing the evaluation methodology. Our approach can be adapted by corporate and educational organisations from various application domains, although we select the medical domain for the paper demonstration.

Semantic Decision Support Models for Energy Efficiency in Smart-Metered Homes

A promising approach to Smart Energy Grids is to empower communities of consumers with a novel ro... more A promising approach to Smart Energy Grids is to empower communities of consumers with a novel role in the management of their electricity by sharing excess electricity and therefore becoming energy producers (prosumers). We achieve it using a framework to connect dynamic, context-aware, heterogeneous virtual and real entities on the Internet of Smart Meters (IoSM). We transform the smart electricity meters into fully-fledged intelligent computers on the IoSM and enable them to securely collect data from heterogeneous meters and sensors, detect smart meters with similar goals, exchange and aggregate data from multiple autonomous physical or virtual meters, and manage the actual energy demand and ensure the achievement of demand response for the community involved. Domain ontologies are used to store the semantics of the collected data from IoSM. A problem we have encountered is how our framework can use ontologies for community-grounded decision rules, which need to be consistent based on aggregation of collected data and contexts. We use Semantic Decision Table (SDT), which is a decision table enhanced with ontology technologies, to tackle the problem. This paper records our efforts in 1) the general design of the framework; 2) decision support models, namely SDTs, for fulfilling this requirement; 3) an algorithm of creating invocational SDTs; 4) the implementation of visualizing invocational SDTs.

Social Network of Smart-Metered Homes and SMEs for Grid-based Renewable Energy Exchange

This paper proposes a revolutionary approach to Smart Energy Grids which empowers communities of ... more This paper proposes a revolutionary approach to
Smart Energy Grids which empowers communities of consumers
as first-class citizens with a novel role in the management of their electricity by sharing excess electricity and therefore becoming energy producers (prosumers). The approach makes innovations on smart technologies and processes by building a demandresponse decision support system on top of smart metering and social web technologies. This is achieved using a framework to connect dynamic, context-aware, heterogeneous virtual and real entities on the Internet of Smart Meters (IoSM) and by studying the behavior of communities on it. The smart electricity meters are transformed into fully-fledged intelligent computers on the IoSM, enabled to (i) securely collect data from heterogeneous meters and sensors and actuators, (ii) detect smart meters with similar goals, (iii) exchange and aggregate data from multiple autonomous physical or virtual meters, and (iv) manage the actual energy demand and ensure the achievement of demand response for the community involved. The approach is centered on the community and its respective DSOs, where each prosumer is represented as a node on the IoSM through their electricity meters, sensors and actuators. This allows for rational energy exchange between technical and non-technical participants by expressing their goals in a standardized language through hybrid
ontologies.

Towards Evaluating an Ontology-based Data Matching Strategy for Retrieval and Recommendation of Security Annotations for Busines

In the Trusted Architecture for Securely Shared Services (TAS3) EC FP7 project we have developed ... more In the Trusted Architecture for Securely Shared Services (TAS3) EC FP7 project we have developed a method to provide semantic support to the process modeler during the design of secure business process models. Its supporting tool, called Knowledge Annotator (KA), is using ontology-based data matching algorithms and strategy in order to infer the recommendations the best fitted to the user design intent, from a dedicated knowledge base. The paper illustrates how the strategy is used to perform the similarity (matching) check in order to retrieve the best design recommendation. We select the security and privacy domain for trust policy specification for the concept illustration. Finally, the paper discusses the evaluation of the results using the Ontology-based Data Matching Framework evaluation benchmark.

Ontology-Based Matching of Security Attributes for Personal Data Access in e-Health

This paper discusses an interoperability solution (tool) for the internal management of a policy ... more This paper discusses an interoperability solution (tool) for the internal management of a policy decision engine located at the level of the authorization layer of a service oriented environment. The tool aims to support federated access control in the context of distributed architectures, in which a local authorization policy is not able to recognize all the attributes in the authorization decision requests. The approach is based on an ontology-based interoperation service (OBIS) whose role is to translate security attributes (name-value pairs) from local security vocabularies into the attributes recognized by the central (Master Policy Decision Point) vocabulary based on a security ontology and its domain-specific extensions which provides semantic reasoning services. The approach is validated in an e-Health scenario for the access of patient data for diabetes patient monitoring and disease management.

Ioana Ciuciu

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