67 research outputs found
Interactive Exploration over RDF Data using Formal Concept Analysis
International audienceWith an increased interest in machine processable data, many datasets are now published in RDF (Resource Description Framework) format in Linked Data Cloud. These data are distributed over independent resources which need to be centralized and explored for domain specific applications. This paper proposes a new approach based on interactive data exploration paradigm using Pattern Structures, an extension of Formal Concept Analysis, to provide exploration and navigation over Linked Data through concept lattices. It takes RDF triples and RDF Schema based on user requirements and provides one navigation space resulting from several RDF resources. This navigation space allows user to navigate and search only the part of data that is interesting for her
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
Multilayer Networks
In most natural and engineered systems, a set of entities interact with each
other in complicated patterns that can encompass multiple types of
relationships, change in time, and include other types of complications. Such
systems include multiple subsystems and layers of connectivity, and it is
important to take such "multilayer" features into account to try to improve our
understanding of complex systems. Consequently, it is necessary to generalize
"traditional" network theory by developing (and validating) a framework and
associated tools to study multilayer systems in a comprehensive fashion. The
origins of such efforts date back several decades and arose in multiple
disciplines, and now the study of multilayer networks has become one of the
most important directions in network science. In this paper, we discuss the
history of multilayer networks (and related concepts) and review the exploding
body of work on such networks. To unify the disparate terminology in the large
body of recent work, we discuss a general framework for multilayer networks,
construct a dictionary of terminology to relate the numerous existing concepts
to each other, and provide a thorough discussion that compares, contrasts, and
translates between related notions such as multilayer networks, multiplex
networks, interdependent networks, networks of networks, and many others. We
also survey and discuss existing data sets that can be represented as
multilayer networks. We review attempts to generalize single-layer-network
diagnostics to multilayer networks. We also discuss the rapidly expanding
research on multilayer-network models and notions like community structure,
connected components, tensor decompositions, and various types of dynamical
processes on multilayer networks. We conclude with a summary and an outlook.Comment: Working paper; 59 pages, 8 figure
Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019
One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge
Graphs: New Directions for Knowledge Representation on the Semantic Web" and
described in its report is that of a: "Public FAIR Knowledge Graph of
Everything: We increasingly see the creation of knowledge graphs that capture
information about the entirety of a class of entities. [...] This grand
challenge extends this further by asking if we can create a knowledge graph of
"everything" ranging from common sense concepts to location based entities.
This knowledge graph should be "open to the public" in a FAIR manner
democratizing this mass amount of knowledge." Although linked open data (LOD)
is one knowledge graph, it is the closest realisation (and probably the only
one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides
a unique testbed for experimenting and evaluating research hypotheses on open
and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing
evolution and long term preservation. We want to investigate this problem, that
is to understand what preserving and supporting the evolution of KGs means and
how these problems can be addressed. Clearly, the problem can be approached
from different perspectives and may require the development of different
approaches, including new theories, ontologies, metrics, strategies,
procedures, etc. This document reports a collaborative effort performed by 9
teams of students, each guided by a senior researcher as their mentor,
attending the International Semantic Web Research School (ISWS 2019). Each team
provides a different perspective to the problem of knowledge graph evolution
substantiated by a set of research questions as the main subject of their
investigation. In addition, they provide their working definition for KG
preservation and evolution
Results of the Ontology Alignment Evaluation Initiative 2009
euzenat2009cInternational audienceOntology matching consists of finding correspondences between on- tology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modal- ities, e.g., blind evaluation, open evaluation, consensus. OAEI-2009 builds over previous campaigns by having 5 tracks with 11 test cases followed by 16 partici- pants. This paper is an overall presentation of the OAEI 2009 campaign
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