Towards Scalable Visual Exploration of Very Large RDF Graphs

In this paper, we outline our work on developing a disk-based infrastructure for efficient visualization and graph exploration operations over very large graphs. The proposed platform, called graphVizdb, is based on a novel technique for indexing and storing the graph. Particularly, the graph layout is indexed with a spatial data structure, i.e., an R-tree, and stored in a database. In runtime, user operations are translated into efficient spatial operations (i.e., window queries) in the backend.Comment: 12th Extended Semantic Web Conference (ESWC 2015

Visualization of typed links in linked data

The main subject of the work is the visualization of typed links in Linked Data. The academic subjects relevant to the paper in general are the Semantic Web, the Web of Data and information visualization. The Semantic Web, invented by Tim Berners-Lee in 2001, was announced as an extension to the World Wide Web (Web 2.0). The actual area of investigation concerns the connectivity of information on the World Wide Web. To be able to explore such interconnections, visualizations are critical requirements as well as a major part of processing data in themselves. In the context of the Semantic Web, representation of information interrelations can be achieved using graphs. The aim of the article is to primarily describe the arrangement of Linked Data visualization concepts by establishing their principles in a theoretical approach. Putting design restrictions into context leads to practical guidelines. By describing the creation of two alternative visualizations of a commonly used web application representing Linked Data as network visualization, their compatibility was tested. The application-oriented part treats the design phase, its results, and future requirements of the project that can be derived from this test

Melody: A Platform for Linked Open Data Visualisation and Curated Storytelling

Data visualisation and storytelling techniques help experts highlight relations between data and share complex information with a broad audience. However, existing solutions targeted to Linked Open Data visualisation have several restrictions and lack the narrative element. In this article we present MELODY, a web interface for authoring data stories based on Linked Open Data. MELODY has been designed using a novel methodology that harmonises existing Ontology Design and User Experience methodologies (eXtreme Design and Design Thinking), and provides reusable User Interface components to create and publish web-ready article-alike documents based on data retrievable from any SPARQL endpoint. We evaluate the software by comparing it with existing solutions, and we show its potential impact in projects where data dissemination is crucial

Visualización basada en semántica

Esta línea de investigación tiene como objetivo crear un modelo de visualización que considere la semántica de los datos, del contexto y de las etapas del “Modelo Unificado de Visualización” (MUV) para poder asistir al usuario en el seteo de los parámetros de la visualización logrando así una mejor representación visual. Este modelo deberá formalizar el modelo de referencia mediante una Ontología de Visualización, incorporar una Ontología de Datos e incorporar una capa de inferencia que le permita derivar nueva información, a partir de la ya conocida. Esta línea también busca introducir el uso de semántica y razonamiento semántico en diferentes aspectos del proceso de visualización.Eje: Computación Gráfica, Imágenes y Visualización.Red de Universidades con Carreras en Informática (RedUNCI

Next Generation of Spatial Data Infrastructure: Lessons from Linked Data implementations across Europe

The need for integration of geospatial data across national borders poses questions on how to overcome technical and organizational barriers between national mapping agencies. Existing National Spatial Data Infrastructures (NSDIs) inherited heterogeneous technology stacks and user cultures. Example integration solutions are based on cascading data services on the Web using open standards. However, this approach is often cumbersome since it requires substantial efforts aimed at harmonisation of data structures and semantics of the content between NSDIs. In contrast, the Linked Data technology as an innovative approach for publishing heterogeneous data sources on the Web is able to transcend the traditional confines of separate databases, as well as, the confines of separate institutions - keeping existing infrastructures intact. Moreover, exposing national data as Linked Data on the Web makes it a part of the Semantic Web. This allows shifting focus from collection and dissemination of data to meaningful data consumption. Here, we present and discuss the results of the Open European Location Services project, a collaboration between the national mapping agencies of Finland, the Netherlands, Norway, and Spain which is aimed at demonstrating the capabilities of Linked Data technology in the context of Pan-European geospatial data provision

Development and Validation of a Proof-of-Concept Prototype for Analytics-based Malicious Cybersecurity Insider Threat in a Real-Time Identification System

Insider threat has continued to be one of the most difficult cybersecurity threat vectors detectable by contemporary technologies. Most organizations apply standard technology-based practices to detect unusual network activity. While there have been significant advances in intrusion detection systems (IDS) as well as security incident and event management solutions (SIEM), these technologies fail to take into consideration the human aspects of personality and emotion in computer use and network activity, since insider threats are human-initiated. External influencers impact how an end-user interacts with both colleagues and organizational resources. Taking into consideration external influencers, such as personality, changes in organizational polices and structure, along with unusual technical activity analysis, would be an improvement over contemporary detection tools used for identifying at-risk employees. This would allow upper management or other organizational units to intervene before a malicious cybersecurity insider threat event occurs, or mitigate it quickly, once initiated. The main goal of this research study was to design, develop, and validate a proof-of-concept prototype for a malicious cybersecurity insider threat alerting system that will assist in the rapid detection and prediction of human-centric precursors to malicious cybersecurity insider threat activity. Disgruntled employees or end-users wishing to cause harm to the organization may do so by abusing the trust given to them in their access to available network and organizational resources. Reports on malicious insider threat actions indicated that insider threat attacks make up roughly 23% of all cybercrime incidents, resulting in $2.9 trillion in employee fraud losses globally. The damage and negative impact that insider threats cause was reported to be higher than that of outsider or other types of cybercrime incidents. Consequently, this study utilized weighted indicators to measure and correlate simulated user activity to possible precursors to malicious cybersecurity insider threat attacks. This study consisted of a mixed method approach utilizing an expert panel, developmental research, and quantitative data analysis using the developed tool on simulated data set. To assure validity and reliability of the indicators, a panel of subject matter experts (SMEs) reviewed the indicators and indicator categorizations that were collected from prior literature following the Delphi technique. The SMEs’ responses were incorporated into the development of a proof-of-concept prototype. Once the proof-of-concept prototype was completed and fully tested, an empirical simulation research study was conducted utilizing simulated user activity within a 16-month time frame. The results of the empirical simulation study were analyzed and presented. Recommendations resulting from the study also be provided