Marina Riga

Designing for Inconsistency – The Dependency-Based PERICLES Approach

The rise of the Semantic Web has provided cultural heritage researchers and practitioners with several tools for ensuring semantic-rich representations and interoperability of cultural heritage collections. Although indeed offering a lot of advantages, these tools, which come mostly in the form of ontologies and related vocabularies, do not provide a conceptual model for capturing contextual and environmental dependencies contributing to long-term digital preservation. This paper presents one of the key outcomes of the PERICLES FP7 project, the Linked Resource Model, for modelling dependencies as a set of evolving linked resources. The proposed model is evaluated via a domain-specific representation involving digital video art.

User-Driven Ontology Population from Linked Data Sources

In order for ontology-based applications to be deployed in real-life scenarios, significant volumes of data are required to populate the underlying models. Populating ontologies manually is a time-consuming and error-prone task and, thus, research has shifted its attention to automatic ontology population methodologies. However, the majority of the proposed approaches and tools focus on analysing natural language text and often neglect other more appropriate sources of information, such as the already structured and semantically rich sets of Linked Data. The paper presents PROPheT, a novel ontology population tool for retrieving instances from Linked Data sources and subsequently inserting them into an OWL ontology. The tool, to the best of our knowledge, offers entirely novel ontology population functionality to a great extent and has already been positively received according to user evaluation.

Presentation and Dissemination of Pollen Information

The aim of this chapter is to describe the ways that pollen information is being presented and disseminated to the general public, in various European countries and elsewhere, with the aid of information and communication systems and methods. For this purpose, the chapter firstly addresses the legal framework concerning the dissemination of environmental information and especially information concerning the quality of the atmospheric environment. In the next section, the production of pollen related information via monitoring systems and with the aid of appropriate models is addressed. Then, the chapter presents and analyses pollen information dissemination, including internet technologies as well as participatory sensing. Furthermore, on-line pollen information systems are investigated, and pollen information presentation as well as communication means are analysed. On the basis of the aforementioned investigations, the chapter then addresses the area of electronic information systems and services for quality of life. Such services are suggested as appropriate for disseminating environmental quality information related to pollen levels. Lastly, conclusions are drawn concerning information services that would include pollen related data and knowledge.

Development and Evaluation of Data Mining Models for Air Quality Prediction in Athens, Greece

Air pollution is a major problem in the world today, causing undesirable effects on both the environment and human health and, at the same time, stressing the need for effective simulation and forecasting models of atmospheric quality. Targeting this adverse situation, our current work focuses on investigating the potential of data mining algorithms in air pollution modeling and short-term forecasting problems. In this direction, various data mining methods are adopted for the qualitative forecasting of concentration levels of air pollutants or the quantitative prediction of their values (through the development of different classification and regression models respectively) in five locations of the greater Athens area. An additional aim of this work is the systematic assessment of the quality of experimental results, in order to discover the best performing algorithm (or set of algorithms) that can be proved to be significantly different from its rivals. Obtained experimental results are deemed satisfactory in terms of the aforementioned goals of the investigation, as high percentages of correct classifications are achieved in the set of monitoring stations and clear conclusions are drawn, as far as the determination of significantly best performing algorithms is concerned, for the development of air quality (AQ) prediction models.

An Ontology-Based Decision Support Framework for Personalized Quality of Life Recommendations

As urban atmospheric conditions are tightly connected to citizens’ quality of life, the concept of efficient environmental decision support systems becomes highly relevant. However, the scale and heterogeneity of the involved data, together with the need for associating environmental information with physical reality, increase the complexity of the problem. In this work, we capitalize on the semantic expressiveness of ontologies to build a framework that uniformly covers all phases of the decision making process: from structuring and integration of data, to inference of new knowledge. We define a simplified ontology schema for representing the status of the environment and its impact on citizens’ health and actions. We also implement a novel ontology- and rule-based reasoning mechanism for generating personalized recommendations, capable of treating differently individuals with diverse levels of vulnerability under poor air quality conditions. The overall framework is easily adaptable to new sources and needs.

The SemaDrift Protégé Plugin to Measure Semantic Drift in Ontologies: Lessons Learned

Semantic drift is an active research field, which aims to identify and measure changes in ontologies across time and versions. Yet, only few practical methods have emerged that are directly applicable to Semantic Web constructs, while the lack of relevant applications and tools is even greater. This paper presents the findings, current limitations and lessons learned throughout the development and the application of a novel software tool, developed in the context of the PERICLES FP7 project, which integrates currently investigated methods, such as text and structural similarity, into the popular ontology authoring platform, Protege. The graphical user interface provides knowledge engineers and domain experts with access to methods and results without prior programming knowledge. Its applicability and usefulness are validated through two proof-of-concept scenarios in the domains of Web Services and Digital Preservation; especially the latter is a field where such long-term insights are crucial.

Dependency modelling for inconsistency management in Digital Preservation – The PERICLES approach

The rise of the Semantic Web has provided cultural heritage researchers and practitioners with several tools for providing semantically rich representations and interoperability of cultural heritage collections. Although indeed offering a lot of advantages, these tools, which come mostly in the form of ontologies and related vocabularies, do not provide a conceptual model for capturing contextual and environmental dependencies, contributing to long-term digital preservation. This paper presents one of the key outcomes of the PERICLES FP7 project, the Linked Resource Model, for modelling dependencies as a set of evolving linked resources. The adoption of the proposed model and the consistency of its representation are evaluated via a specific instantiation involving the domain of digital video art.

PROPheT – Ontology Population and Semantic Enrichment from Linked Data Sources

Ontologies are a rapidly emerging paradigm for knowledge representation, with a growing number of applications in various domains. However, populating ontologies with massive volumes of data is an extremely challenging task. The field of ontology population offers a wide array of approaches for populating ontologies in an automated or semi-automated way. Nevertheless, most of the related tools typically analyse natural language text, while sources of more structured information like Linked Open Data would arguably be more appropriate. The paper presents PROPheT, a novel software tool for ontology population and enrichment. PROPheT can populate a local ontology model with instances retrieved from diverse Linked Data sources served by SPARQL endpoints. To the best of our knowledge, no existing tool can offer PROPheT’s diverse extent of functionality.

PERICLES – Digital Preservation through Management of Change in Evolving Ecosystems

Management of change is essential to ensure the long-term reusabilityof digital assets. Change can be brought about in many ways, includingthrough technological, user community and policy factors. ...

A Framework for Automatic Detection of Lumen-Endothelium Border in Intracoronary OCT Image Sequences

Intracoronary optical coherence tomography (OCT) is increasingly being used for real-time visualization of coronary arteries aiming to help in the identification of high-risk atherosclerotic plaques associated with geometrical and morphological features of the arterial wall. This paper presents a framework towards the automatic detection of the inner wall of the coronary artery (lumen-endothelium border) in intracoronary OCT image sequences by employing a multi-step image processing method. The major focus of this work was to address difficult cases that are frequently met in intracoronary OCT, e.g. images with small/big branches, multiple branches, blood presence, calcifications, artifacts, etc. We present each step employed and the results obtained both in qualitative and quantitative terms. The proposed segmentation algorithm has been proven very efficient in the majority of the examined cases.