Regina Motz

Managing source schema evolution in web warehouses

Web Data Warehouses have been introduced to enable the analysis of integrated Web data. One of the main challenges in these systems is to deal with the volatile and dynamic nature of Web sources. In this work we address the effects of adding/removing/changing Web sources and data items to the Data Warehouse (DW) schema. By managing source evolution we mean the automatic propagation of these changes to the DW. The proposed approach is based on a wrapper/mediator architecture, which reduces the impact of Web source changes on the DW schema. This paper presents this architecture and analyses some selected evolution cases in the context of Web DW.

Enriching Adaptation in E-Learning Systems through a Situation-Aware Ontology Network

Purpose – The broader adoption of the internet along with web‐based systems has defined a new way of exchanging information. That advance added by the multiplication of mobile devices has required systems to be even more flexible and personalized. Maybe because of that, the traditional teaching‐controlled learning style has given up space to a new way of learning, which is more flexible and adequate to the learners needs. The purpose of this research is to go further into the semantic modeling of adaptive web based learning systems. Particularly, the paper focuses on those learning systems that consider in their definition the awareness of students context in order to properly react to the student needs.Design/methodology/approach – In this paper the authors introduce a semantic model of the student context in terms of an ontology network. This semantic model is explored in order to detect the “current situation” of students when they are navigating into e‐learning environments. The final objective is to...

Towards an adaptive cultural e-learning system

This work proposes the inclusion of multicultural aspects management into an e-learning system in order to guide the automatic adaptability of presentation and content of electronic-materials. To this end, we define an ontology of cultural aspects in OWL that provides a sound specification of the diverse cultural aspects.

Learning to Get the Value of Quality from Web Data

The quality of data used in an information system is highly influenced by the quality of data extracted from the sources that the system uses. This feature is particularly sensitive when the sources provide data coming from the web. These web data are extremely dynamic and heterogeneous and they generally lack from a direct responsible about their quality. This work addresses this problem by presenting a proposal to get the values of quality factors from data coming from the web. One important contribution of this paper is the specification of a generic and flexible Quality Factor Ontology (QF-Ontology) able to model quality factors depending not only on the specific application domain but also on the different types of web sources. Moreover, this paper shows how using SWRL the QF-Ontology is exploited to calculate the metrics associated to each quality factor.

A Digital Ecosystem for the Collaborative Production of Open Textbooks: The LATIn Methodology

Access to books in higher education is an issue to be addressed, especially in the context of un-derdeveloped countries, such as those in Latin America. More than just financial issues, cultural aspects and need for adaptation must be considered. The present conceptual paper proposes a methodology framework that would support collaborative open textbook initiatives. This meth-odology intends to be the main guideline for a digital ecosystem for the collaborative production of open textbooks and has the potential to solve standing methodological problems of current ini-tiatives, such as Wikibooks and Connexions. The systems architecture and construction will be guided by six collaborative writing di-mensions: process, roles, timing, con-trolling, granularity, and writing groups. Each dimension will coordinate an as-pect of the collaborative work and is detailed in the methodology proposed in this paper. This paper is divided in the following parts: the first part introduces the sub-ject, being followed by an analysis of related works about collaboration and Computer-Supported Cooperative Work; in this section, some authors, ideas, and methodological aspects of collaborative writing are also discussed. Next, the paper shows the proposal of a Digital Ecosystem for the collaborative creation of open text-books, the six dimensions of this Ecosystem, and its respective descriptions. The work finishes with some conclusions about the proposal and the next steps needed to implement it in the real world.

The description logic SHIQ with a flexible meta-modelling hierarchy

This work is motivated by a real-world case study where it is necessary to integrate and relate existing ontologies through meta-modelling. For this, we introduce the Description Logic SHIQM which is obtained from SHIQ by adding statements that equate individuals to concepts in a knowledge base. In this new extension, concepts can be individuals of another concept (called meta-concept) which itself can be an individual of yet another concept (called meta-meta-concept) and so on. We define an algorithm that checks consistency of SHIQM by modifying the Tableau algorithm for SHIQ . From the practical point of view, this has the advantage that we can reuse the code of existing OWL reasoners. From the theoretical point of view, it has a similar advantage of reuse. We make use of the existing results and proofs that lead to correctness of the algorithm for SHIQ in order to prove correctness of the algorithm for SHIQM .

Modelling a web site quality‐based recommendation system

Purpose – Web site recommendation systems help to get high quality information. The modelling of recommendation systems involves the combination of many features: metrics of quality, quality criteria, recommendation criteria, user profile, and specific domain concepts, among others. At the moment of the specification of a recommendation system it must be guaranteed a right interrelation of all of these features. The purpose of this paper is to model a web site quality‐based recommendation system by an ontology network.Design/methodology/approach – In this paper, the authors propose an ontology network based process for web site recommendation modelling. The ontology network conceptualizes the different domains (web site domain, quality assurance domain, user context domain, recommendation criteria domain, specific domain) in a set of interrelated ontologies. Particularly, this approach is illustrated for the health domain.Findings – Basically, this work introduces the semantic relationships that were used...

Ontology-Based Process for Recommending Health WebSites

Website content quality is particularly relevant in the health domain. A common user needs to retrieve health information that is precise, reliable and relevant to his/her profile. Website recommendation systems are an aid to get high quality health-related web sites according to the user’s needs. However, in practice, it is not always evident how to describe recommendation criteria for health website. The goal of this paper is to describe, by an ontology network, the criteria used by a health website recommendation process. This ontology network conceptualizes the different domains that are involved in the Salus Recommendation Project as a set of interrelated ontologies.

Recommendations Given from Socially-Connected People

This paper presents how relationships among members of a social network can be used to explicitly specify the relevant features of a friendsourcing recommendation algorithm. One important contribution is to show how to conceptualize previous evaluations of items made by socially-connected users and the different features involved in this kind of algorithms, in a set of criteria for similarity between users in a social network. The paper presents how these specified criteria are used by the proposed friendsourcing recommendation algorithm and shows how the recommendation algorithm is integrated into a real recommender system to be used in a healthcare social network for the medical service of a university. Moreover, the work shows preliminary results which indicate that the information contained in social networks, processed with the proposed algorithm, is relevant for the generation of personalized recommendations.

Modeling a web site quality-based recommendation system

Web site recommendation systems help to get high quality information. The modeling of recommendation system involves the combination of many features: metrics of quality, quality criteria, recommendation criteria, user profile, specific domain concepts, among others. At the moment of the specification of a recommendation system it must be guaranteed a right interrelation of all of these features. In this paper, we propose an ontology network based process for web site recommendation modeling. The ontology network conceptualizes the different domains (web site domain, quality assurance domain, user context domain, recommendation criteria domain, specific domain) in a set of interrelated ontologies. Basically, this work introduces the semantic relationships that were used to construct this ontology network. Moreover, it shows the usefulness of this ontology network for the detection of possible inconsistencies when specifying recommendation criteria. Particularly, this approach is illustrated for the health domain.