Fayçal Hamdi

Alignment-based Partitioning of Large-scale Ontologies

Ontology alignment is an important task for information integration systems that can make different resources, described by various and heterogeneous ontologies, interoperate. However very large ontologies have been built in some domains such as medicine or agronomy and the challenge now lays in scaling up alignment techniques that often perform complex tasks. In this paper, we propose two partitioning methods which have been designed to take the alignment objective into account in the partitioning process as soon as possible. These methods transform the two ontologies to be aligned into two sets of blocks of a limited size. Furthermore, the elements of the two ontologies that might be aligned are grouped in a minimal set of blocks and the comparison is then enacted upon these blocks. Results of experiments performed by the two methods on various pairs of ontologies are promising.

Pattern-based mapping refinement

Semantic alignment between ontologies is a crucial task for information integration. There are many ongoing efforts to develop matching systems implementing various alignment techniques but it is impossible to predict what strategy is most successful for an application domain or a given pair of ontologies. Very often the quality of the results could be improved by considering the specificities of the ontologies to be aligned. In this paper, we propose a pattern-based approach implemented in the TaxoMap Framework helping an engineer to refine mappings to take into account specific conventions used in ontologies. Experiments in the topographic field within the ANR (The French National Research Agency) project GeOnto show the usefulness of such an environment both for a domain expert and an engineer, especially when the number of mappings is very large.

PersonLink: An Ontology Representing Family Relationships for the CAPTAIN MEMO Memory Prosthesis

In the context of the CAPTAIN MEMO memory prosthesis for elderly, we propose the PersonLink ontology for modeling, storing and reasoning on “family relationships” links. Rules are provided to infer new links and/or check inconsistencies in the inputs. On the one hand PersonLink is as generic as possible and is integrated in the linked data formalisms; on the other hand a prosthesis has to be adaptable to users. Thus the PersonLink ontology defines rigorously and precisely family relationships, and takes into account the differences that may exist between cultures/languages, including new relationships emerging in our societies nowadays. The transition from one culture/language to another one cannot be solved with a simple translation of terms, but refers to a meta-ontology and associated mechanisms.

Visualizing Large-scale Linked Data with Memo Graph

Abstract Many studies, in the literature, have affirmed a low level of user satisfaction concerning the understandability and readability of large-scale Linked Data visualizations offered by current available tools. This issue is especially problematic for inexperienced users. To address these requirements, we have extended our previous work Memo Graph, an ontology visualization tool, to provide a user-centered interactive solution for extracting and visualizing Linked Data. It takes aim to provide comprehensible and legible visualization. To manage scalability, it is built on an incremental approach to extract descriptive summarization from a given Linked Data endpoint where it becomes possible to generate a “summary graph” from the most important data (middle-out navigation approach). It offers user interfaces that reduce task complexity for users, especially the inexperienced ones. We tested Memo Graph on a number of Linked Data datasets with encouraging results. We discuss the promising results derived from an empirical evaluation, which affirmed that Memo Graph is useful in visualizing Linked Data and usable.

PersonLink: A Multilingual and Multicultural Ontology Representing Family Relationships

Many existing open linked datasets include descriptions of real world persons, with the relationships between them. For some traditional and/or emerging relationships, existing ontologies do not provide the adequate links. This paper represents PersonLink, an ontology that defines rigorously and precisely family relationships, and takes into account the differences that may exist between cultures, including new relationships emerging in our societies nowadays. Moreover, the transition from one culture/language to another one cannot be solved with a simple translation of terms, especially when concepts do not intersect in different languages; thus our solution refers to a multicultural meta-ontology of concepts and associated mechanisms. A validation has been performed on two linked datasets DBpedia and Freebase.

Assessing the Completeness Evolution of DBpedia: A Case Study

RDF web datasets, thanks to their semantic richness, variety and fine granularity, are increasingly adopted by both researchers’ and business communities. However, as anyone can publish data, this leads to sparse and heterogeneous data descriptions with undeniably an impact on quality. Consequently, there is an increasing effort dedicated to Web data quality improvement. We are interested in data quality and precisely in completeness quality evolution over time. The paper presents a set of experiments aiming to analyze the evolution of completeness quality values over several versions of DBpedia.

HuMa: A Multi-layer Framework for Threat Analysis in a Heterogeneous Log Environment

The advent of massive and highly heterogeneous information systems poses major challenges to professionals responsible for IT security. The huge amount of monitoring data currently being generated means that no human being or group of human beings can cope with their analysis. Furthermore, fully automated tools still lack the ability to track the associated events in a fine-grained and reliable way. Here, we propose the HuMa framework for detailed and reliable analysis of large amounts of data for security purposes. HuMa uses a multi-analysis approach to study complex security events in a large set of logs. It is organized around three layers: the event layer, the context and attack pattern layer, and the assessment layer. We describe the framework components and the set of complementary algorithms for security assessment. We also provide an evaluation of the contribution of the context and attack pattern layer to security investigation.

A Fuzzy-Based Approach for Representing and Reasoning on Imprecise Time Intervals in Fuzzy-OWL 2 Ontology

Representing and reasoning on imprecise temporal information is a common requirement in the field of Semantic Web. Many works exist to represent and reason on precise temporal information in OWL; however, to the best of our knowledge, none of these works is devoted to represent and reason on imprecise time intervals. To address this problem, we propose a fuzzy-based approach for representing and reasoning on imprecise time intervals in ontology. Our approach is based on fuzzy sets theory and fuzzy tools and is modeled in Fuzzy-OWL 2. The 4D-fluents approach is extended, with new fuzzy components, in order to represent imprecise time intervals and qualitative fuzzy interval relations. The Allen’s interval algebra is extended in order to compare imprecise time intervals in a fuzzy gradual personalized way. Inferences are done via a set of Mamdani IF-THEN rules.

Representing Imprecise Time Intervals in OWL 2

Representing and reasoning on imprecise temporal information is a common requirement in the field of Semantic Web. Many works exist to represent and reason on precise temporal information in OWL; however, to the best of our knowledge, none of these works is devoted to imprecise temporal time intervals. To address this problem, we propose two approaches: a crisp-based approach and a fuzzy-based approach. (1) The first approach uses only crisp standards and tools and is modelled in OWL 2. We extend the 4D-fluents model, with new crisp components, to represent imprecise time intervals and qualitative crisp interval relations. Then, we extend the Allen’s interval algebra to compare imprecise time intervals in a crisp way and inferences are done via a set of SWRL rules. (2) The second approach is based on fuzzy sets theory and fuzzy tools and is modelled in Fuzzy-OWL 2. The 4D-fluents approach is extended, with new fuzzy components, in order to represent imprecise time intervals and qualitative fuzzy interval relations. The Allen’s interval algebra is extended in order to compare imprecise time intervals in a fuzzy gradual personalized way. Inferences are done via a set of Mamdani IF-THEN rules.

A Semantic Representation of Time Intervals in OWL 2.

Representing time over the Semantic Web has always been a challenging issue that many scientific works were interested to address. To the best of our knowledge, the most important ones focused on models, whereas Semantic Web and especially OWL 2 offers semantics that can be efficiently used to describe qualitative diachronic information (i.e. information evolving in time and which start and/or end time is unknown). In this work, we show the relationship between the OWL 2 semantics and the representation of time intervals; then we introduce a qualitative representation of temporal information based on a set of SWRL rules, that allows a sound and complete reasoning mechanism.