A Visual Analytics Framework Case Study: Understanding Colombia’s National Administrative Department of Statistics Datasets

In a world filled with data, it is expected for a nation to take decisions informed by data. However, countries need to first collect and publish such data in a way meaningful for both citizens and policy makers. A good thematic classification could be instrumental in helping users to navigate and find the right resources on a rich data repository, such as the one collected by the DANE (Departamento Administrativo Nacional de Estadística, i.e. the Colombia’s National Administrative Department of Statistics). The Visual Analytics Framework is a methodology for conducting visual analysis developed by T. Munzner et al.1 that could help with this task. This paper presents a case study applying such framework conducted to help the DANE to better visualize their data repository, and also to understand it better by using another classification extracted from its metadata. It describes the three main analysis tasks identified and the proposed solutions. Usability testing results during the process helped to correct the visualizations and make them adapted to decision-making. Finally, we explained the collection of insights generated from them

Atrioventricular and interventricular delay optimization in cardiac resynchronization therapy: physiological principles and overview of available methods

In this review, the physiological rationale for atrioventricular and interventricular delay optimization of cardiac resynchronization therapy is discussed including the influence of exercise and long-term cardiac resynchronization therapy. The broad spectrum of both invasive and non-invasive optimization methods is reviewed with critical appraisal of the literature. Although the spectrum of both invasive and non-invasive optimization methods is broad, no single method can be recommend for standard practice as large-scale studies using hard endpoints are lacking. Current efforts mainly investigate optimization during resting conditions; however, there is a need to develop automated algorithms to implement dynamic optimization in order to adapt to physiological alterations during exercise and after anatomical remodeling

GenomeSnip: Fragmenting the Genomic Wheel to augment discovery in cancer research

Conference paperCancer genomics researchers have greatly benefited from high-throughput technologies for the characterization of genomic alterations in patients. These voluminous genomics datasets when supplemented with the appropriate computational tools have led towards the identification of \u27oncogenes\u27 and cancer pathways. However, if a researcher wishes to exploit the datasets in conjunction with this extracted knowledge his cognitive abilities need to be augmented through advanced visualizations. In this paper, we present GenomeSnip, a visual analytics platform, which facilitates the intuitive exploration of the human genome and displays the relationships between different genomic features. Knowledge, pertaining to the hierarchical categorization of the human genome, oncogenes and abstract, co-occurring relations, has been retrieved from multiple data sources and transformed a priori. We demonstrate how cancer experts could use this platform to interactively isolate genes or relations of interest and perform a comparative analysis on the 20.4 billion triples Linked Cancer Genome Atlas (TCGA) datasets

Analysis of Term Reuse, Term Overlap and Extracted Mappings across AgroPortal Semantic Resources

International audienceOntologies in agronomy facilitate data integration, information exchange, search and query of agronomic data, and other knowledge-intensive tasks. We have developed AgroPortal, an open community-based repository of agronomy and related domains semantic resources. From a corpus of ontologies, terminologies, and thesauri taken from Agro-Portal, we have generated, extracted and analyzed more than 400,000 mappings between concepts based on: (i) reuse of the same URI between concepts in different resources-term reuse; (ii) lexical similarity of concept names and synonyms-term overlap; and (iii) declared map-pings properties between concepts-extracted mappings. We developed an interactive visualization of each mapping construct separately and combined which helps users identify most prominent ontologies, relevant thematic clusters, areas of a domain that are not well covered, and pertinent ontologies as background knowledge. By comparing the size of the semantic resources to the number of their mappings, we found that most of them have under 5% of their terms mapped. Our results show the need of an ontology alignment framework in AgroPortal where map-pings between semantic resources will be assembled, compared, analysed and automatically updated when semantic resources evolve

A Framework to Conduct and Report on Empirical User Studies in Semantic Web Contexts

Semantic Web technologies are being applied to increasingly diverse areas where user involvement is crucial. While a number of user interfaces for Semantic Web systems have become available in the past years, their evaluation and reporting often still suffer from weaknesses. Empirical evaluations are essential to compare different approaches, demonstrate their benefits and reveal their drawbacks, and thus to facilitate further adoption of Semantic Web technologies. In this paper, we review empirical user studies of user interfaces, visualizations and interaction techniques recently published at relevant Semantic Web venues, assessing both the user studies themselves and their reporting. We then chart the design space of available methods for user studies in Semantic Web contexts. Finally, we propose a framework for their comprehensive reporting, taking into consideration user expertise, experimental setup, task design, experimental procedures and results analysis

GraFa: Scalable faceted browsing for RDF graphs

Faceted browsing has become a popular paradigm for user interfaces on the Web and has also been investigated in the context of RDF graphs. However, current faceted browsers for RDF graphs encounter performance issues when faced with two challenges: scale, where large datasets generate many results, and heterogeneity, where large numbers of properties and classes generate many facets. To address these challenges, we propose GraFa: a faceted browsing system for heterogeneous large-scale RDF graphs based on a materialisation strategy that performs an offline analysis of the input graph in order to identify a subset of the exponential number of possible facet combinations that are candidates for indexing. In experiments over Wikidata, we demonstrate that materialisation allows for displaying (exact) faceted views over millions of diverse results in under a second while keeping index sizes relatively small. We also present initial usability studies over GraFa