Community detection applied on big linked data

The Linked Open Data (LOD) Cloud has more than tripled its sources in just six years (from 295 sources in 2011 to 1163 datasets in 2017). The actual Web of Data contains more then 150 Billions of triples. We are assisting at a staggering growth in the production and consumption of LOD and the generation of increasingly large datasets. In this scenario, providing researchers, domain experts, but also businessmen and citizens with visual representations and intuitive interactions can significantly aid the exploration and understanding of the domains and knowledge represented by Linked Data. Various tools and web applications have been developed to enable the navigation, and browsing of the Web of Data. However, these tools lack in producing high level representations for large datasets, and in supporting users in the exploration and querying of these big sources. Following this trend, we devised a new method and a tool called H-BOLD (High level visualizations on Big Open Linked Data). H-BOLD enables the exploratory search and multilevel analysis of Linked Open Data. It offers different levels of abstraction on Big Linked Data. Through the user interaction and the dynamic adaptation of the graph representing the dataset, it will be possible to perform an effective exploration of the dataset, starting from a set of few classes and adding new ones. Performance and portability of H-BOLD have been evaluated on the SPARQL endpoint listed on SPARQL ENDPOINT STATUS. The effectiveness of H-BOLD as a visualization tool is described through a user study

Social semantic search : a case study on web 2.0 for science

When researchers formulate search queries to find relevant content on the Web, those queries typically consist of keywords that can only be matched in the content or its metadata. The Web of Data extends this functionality by bringing structure and giving well-defined meaning to the content and it enables humans and machines to work together using controlled vocabularies. Due the high degree of mismatches between the structure of the content and the vocabularies in different sources, searching over multiple heterogeneous repositories of structured data is considered challenging. Therefore, the authors present a semantic search engine for researchers facilitating search in research related Linked Data. To facilitate high-precision interactive search, they annotated and interlinked structured research data with ontologies from various repositories in an effective semantic model. Furthermore, the authors' system is adaptive as researchers can synchronize using new social media accounts and efficiently explore new datasets

Steps Towards Interactive Formal Concept Analysis with LatViz

International audienceWith the increase in Web of Data (WOD) many new challenges regarding exploration, interaction, analysis and discovery have surfaced. One of the basic building blocks of data analysis is classification. Many studies have been conducted concerning Formal Concept Analysis (FCA) and its variants over WOD. But one fundamental question is, after these concept lattices are obtained on top of WOD, how the user can interactively explore and analyze this data through concept lattices. To achieve this goal, we introduce a new tool called LatViz, which implements several algorithms for constructing concept lattices and allows further navigation over lattice structure. LatViz proposes some remarkable improvements over existing tools and introduces various new functionalities such as interaction with expert, visualization of Pattern Structures, AOC posets, concept annotations, filtering concept lattice based on several criteria and finally, an intuitive visualization of implications. This way the user can effectively perform an interactive exploration over a concept lattice which is a basis for a strong user interaction with WOD for data analysis

Barry Smith an sich

Festschrift in Honor of Barry Smith on the occasion of his 65th Birthday. Published as issue 4:4 of the journal Cosmos + Taxis: Studies in Emergent Order and Organization. Includes contributions by Wolfgang Grassl, Nicola Guarino, John T. Kearns, Rudolf Lüthe, Luc Schneider, Peter Simons, Wojciech Żełaniec, and Jan Woleński

LatViz: A New Practical Tool for Performing Interactive Exploration over Concept Lattices

International audienceWith the increase in Web of Data (WOD) many new challenges regarding exploration, interaction, analysis and discovery have surfaced. One of the basic building blocks of data analysis is classification. Many studies have been conducted concerning Formal Concept Analysis (FCA) and its variants over WOD. But one fundamental question is, after these concept lattices are obtained on top of WOD, how the user can interactively explore and analyze this data through concept lattices. To achieve this goal, we introduce a new tool called as LatViz, which allows the construction of concept lattices and their navigation. LatViz proposes some remarkable improvements over existing tools and introduces various new functionalities such as interaction with expert, visualization of Pattern Structures, AOC posets, concept annotations, filtering concept lattice based on several criteria and finally, an intuitive visualization of implications. This way the user can effectively perform an interactive exploration over a concept lattice which is a basis for a strong user interaction with WOD for data analysis

Scholarly Music Editions as Graph: Semantic Modelling of the Anton Webern Gesamtausgabe

This paper presents a first draft of the ongoing research at the Anton Webern Gesamt- ausgabe (Basel, CH) to apply RDF-based semantic models for the purpose of a scholarly digital music edition. A brief overview of different historical positions to approach music from a graph-theoretical perspective is followed by a list of music- related and other RDF vocabularies that may support this goal, such as MusicOWL, DoReMus, CIDOC CRMinf, or the NIE-INE ontologies. Using the example of some of Webern’s sketches for two drafted Goethe settings (M306 & M307), a preliminary graph-based model for philological knowledge and processes is envisioned, which incorporates existing ontologies from the context of cultural heritage and music. Finally, possible use-cases, and the consequences of such an approach to scholarly music editions, are discussed

Scholarly Music Editions as Graph: Semantic Modelling of the Anton Webern Gesamtausgabe

This paper presents a first draft of the ongoing research at the Anton Webern Gesamtausgabe (Basel, CH) to apply RDF-based semantic models for the purpose of a scholarly digital music edition. A brief overview of different historical positions to approach music from a graph-theoretical perspective is followed by a list of music-related and other RDF vocabularies that may support this goal, such as MusicOWL, DoReMus, CIDOC CRMinf, or the NIE-INE ontologies. Using the example of some of Webern's sketches for two drafted Goethe settings (M306 & M307), a preliminary graph-based model for philological knowledge and processes is envisioned, which incorporates existing ontologies from the context of cultural heritage and music. Finally, possible use-cases, and the consequences of such an approach to scholarly music editions, are discussed

Towards Dynamic Composition of Question Answering Pipelines

Question answering (QA) over knowledge graphs has gained significant momentum over the past five years due to the increasing availability of large knowledge graphs and the rising importance of question answering for user interaction. DBpedia has been the most prominently used knowledge graph in this setting. QA systems implement a pipeline connecting a sequence of QA components for translating an input question into its corresponding formal query (e.g. SPARQL); this query will be executed over a knowledge graph in order to produce the answer of the question. Recent empirical studies have revealed that albeit overall effective, the performance of QA systems and QA components depends heavily on the features of input questions, and not even the combination of the best performing QA systems or individual QA components retrieves complete and correct answers. Furthermore, these QA systems cannot be easily reused, extended, and results cannot be easily reproduced since the systems are mostly implemented in a monolithic fashion, lack standardised interfaces and are often not open source or available as Web services. All these drawbacks of the state of the art that prevents many of these approaches to be employed in real-world applications. In this thesis, we tackle the problem of QA over knowledge graph and propose a generic approach to promote reusability and build question answering systems in a collaborative effort. Firstly, we define qa vocabulary and Qanary methodology to develop an abstraction level on existing QA systems and components. Qanary relies on qa vocabulary to establish guidelines for semantically describing the knowledge exchange between the components of a QA system. We implement a component-based modular framework called "Qanary Ecosystem" utilising the Qanary methodology to integrate several heterogeneous QA components in a single platform. We further present Qaestro framework that provides an approach to semantically describing question answering components and effectively enumerates QA pipelines based on a QA developer requirements. Qaestro provides all valid combinations of available QA components respecting the input-output requirement of each component to build QA pipelines. Finally, we address the scalability of QA components within a framework and propose a novel approach that chooses the best component per task to automatically build QA pipeline for each input question. We implement this model within FRANKENSTEIN, a framework able to select QA components and compose pipelines. FRANKENSTEIN extends Qanary ecosystem and utilises qa vocabulary for data exchange. It has 29 independent QA components implementing five QA tasks resulting 360 unique QA pipelines. Each approach proposed in this thesis (Qanary methodology, Qaestro, and FRANKENSTEIN) is supported by extensive evaluation to demonstrate their effectiveness. Our contributions target a broader research agenda of offering the QA community an efficient way of applying their research to a research field which is driven by many different fields, consequently requiring a collaborative approach to achieve significant progress in the domain of question answering

Breaking rules: taking Complex Ontology Alignment beyond rule­based approaches

Tese de mestrado, Ciência de Dados, Universidade de Lisboa, Faculdade de Ciências, 2021As ontologies are developed in an uncoordinated manner, differences in scope and design compromise interoperability. Ontology matching is critical to address this semantic heterogeneity problem, as it finds correspondences that enable integrating data across the Semantic Web. One of the biggest challenges in this field is that ontology schemas often differ conceptually, and therefore reconciling many real¬world ontology pairs (e.g., in geography or biomedicine) involves establishing complex mappings that contain multiple entities from each ontology. Yet, for the most part, ontology matching algorithms are restricted to finding simple equivalence mappings between ontology entities. This work presents novel algorithms for Complex Ontology Alignment based on Association Rule Mining over a set of shared instances between two ontologies. Its strategy relies on a targeted search for known complex patterns in instance and schema data, reducing the search space. This allows the application of semantic¬based filtering algorithms tailored to each kind of pattern, to select and refine the most relevant mappings. The algorithms were evaluated in OAEI Complex track datasets under two automated approaches: OAEI’s entity¬based approach and a novel element¬overlap–based approach which was developed in the context of this work. The algorithms were able to find mappings spanning eight distinct complex patterns, as well as combinations of patterns through disjunction and conjunction. They were able to efficiently reduce the search space and showed competitive performance results comparing to the State of the Art of complex alignment systems. As for the comparative analysis of evaluation methodologies, the proposed element¬overlap–based evaluation strategy was shown to be more accurate and interpretable than the reference-based automatic alternative, although none of the existing strategies fully address the challenges discussed in the literature. For future work, it would be interesting to extend the algorithms to cover more complex patterns and combine them with lexical approaches