Toward automatic comparison of visualization techniques: Application to graph visualization

Many end-user evaluations of data visualization techniques have been run during the last decades. Their results are cornerstones to build efficient visualization systems. However, designing such an evaluation is always complex and time-consuming and may end in a lack of statistical evidence and reproducibility. We believe that modern and efficient computer vision techniques, such as deep convolutional neural networks (CNNs), may help visualization researchers to build and/or adjust their evaluation hypothesis. The basis of our idea is to train machine learning models on several visualization techniques to solve a specific task. Our assumption is that it is possible to compare the efficiency of visualization techniques based on the performance of their corresponding model. As current machine learning models are not able to strictly reflect human capabilities, including their imperfections, such results should be interpreted with caution. However, we think that using machine learning-based pre-evaluation, as a pre-process of standard user evaluations, should help researchers to perform a more exhaustive study of their design space. Thus, it should improve their final user evaluation by providing it better test cases. In this paper, we present the results of two experiments we have conducted to assess how correlated the performance of users and computer vision techniques can be. That study compares two mainstream graph visualization techniques: node-link (\NL) and adjacency-matrix (\MD) diagrams. Using two well-known deep convolutional neural networks, we partially reproduced user evaluations from Ghoniem \textit{et al.} and from Okoe \textit{et al.}. These experiments showed that some user evaluation results can be reproduced automatically.Comment: 35 pages, 6 figures, 4 table

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

Beats There a Heart

Beats there a heart on earth sincere?A heart where guileless love is knownNo purer gem this breast would wearNo dearer treasure own!Where shall I turn? Ah!This cabin the prize I search for at length conceal?Rests unknown is such a casketThat one pearl rank could ne\u27er reveal. I rov\u27d in vain through the gilded haremPlanets of beauty have dazzled my eyesBut women all some vain, some ungratefull,And doubting , still this bosom sighsAh! Beats there a heart on earth sincere?A heart where guileless love is knownNo purer gem this breast would wearNo dearer richer treasure own

TULIP 5

International audienceTulip is an information visualization framework dedicated to the analysis and visualization of relational data. Based on more than 16 years of research and development, Tulip is built on a suite of tools and techniques, that can be used to address a large variety of domain-specific problems. With \tulip, we aim to provide Python and/or C++ developers a complete library, supporting the design of interactive information visualization applications for relational data, that can be customized to address a wide range of visualization problems. In its current iteration, \tulip enables the development of algorithms, visual encodings, interaction techniques, data models, and domain-specific visualizations. This development pipeline makes the framework efficient for creating research prototypes as well as developing end-user applications. The recent addition of a complete Python programming layer wraps up Tulip as an ideal tool for fast prototyping and treatment automation, allowing to focus on problem solving, and as a great system for teaching purposes at all education levels

Interspecific differences in environmental response blur trait dynamics in classic statistical analyses

Trait-based ecology strives to better understand how species, through their bio-ecological traits, respond to environmental changes, and influence ecosystem functioning. Identifying which traits are most responsive to environmental changes can provide insight for understanding community structuring and developing sustainable management practices. However, misinterpretations are possible, because standard statistical methods (e.g., principal component analysis and linear regression) for identifying and ranking the responses of different traits to environmental changes ignore interspecific differences. Here, using both artificial data and real-world examples from marine fish communities, we show how considering species-specific responses can lead to drastically different results than standard community-level methods. By demonstrating the potential impacts of interspecific differences on trait dynamics, we illuminate a major, yet rarely discussed issue, highlighting how analytical misinterpretations can confound our basic understanding of trait responses, which could have important consequences for biodiversity conservation

Characteristics and management of congenital esophageal stenosis: findings from a multicenter study.

BACKGROUND: Congenital esophageal stenosis (CES) is a rare condition frequently associated with esophageal atresia (EA). There are limited data from small series about the presentation, treatment, and outcomes of CES. METHODS: Medical records of all patients with CES included in the French Network on Esophageal Malformations and Congenital Diseases were reviewed retrospectively with regard to diagnosis, treatment, and outcome. RESULTS: Over 18 years, 61 patients (30 boys) had CES, and 29 (47%) of these patients also had EA. The mean age at diagnosis was 24 months (1 day to 14 years) and was younger in patients with CES and EA than in those with isolated CES (7 vs. 126 months, p < 0.05). Twenty-one of the 61 patients with CES had no clinical symptoms: in three patients, the findings were incidental, and in 18 of the 29 patients with associated EA, CES was diagnosed at the time of surgical repair of EA or during a postoperative systematic esophageal barium study. In the 40 other patients, at diagnosis, 50% presented with dysphasia, 40% with vomiting, 50% with food impaction, and 42% with respiratory symptoms. Diagnosis of CES was confirmed by esophageal barium study (56/61) and/or esophageal endoscopy (50/61). Sixteen patients had tracheobronchial remnants (TBR), 40 had fibromuscular stenosis (FMS), and five had membrane stenosis (MS). Thirty-four patients (56%) were treated by dilation only (13/34 remained asymptomatic at follow-up); 15 patients were treated by dilation but required later surgery because of failure (4/15 remained asymptomatic at follow-up); and nine patients had a primary surgical intervention (4/9 were asymptomatic at follow-up). Dilation was complicated by esophageal perforation in two patients (3.4%). At follow-up, dysphagia remained in 36% (21/58) of patients, but the incidence did not differ between the EA and the isolated CS groups (10/29 vs. 7/32, p = 0.27). CONCLUSIONS: CS diagnosis can be delayed when associated with EA. Dilation may be effective for treating patients with FMS and MS, but surgical repair is often required for those with TBR. Our results show clearly that, regardless of the therapeutic option, dysphagia occurs frequently, and patients with CES should be followed over the long term

Establishment of a consensus protocol to explore the brain pathobiome in patients with mild cognitive impairment and Alzheimer\u27s disease: Research outline and call for collaboration.

Microbial infections of the brain can lead to dementia, and for many decades microbial infections have been implicated in Alzheimer\u27s disease (AD) pathology. However, a causal role for infection in AD remains contentious, and the lack of standardized detection methodologies has led to inconsistent detection/identification of microbes in AD brains. There is a need for a consensus methodology; the Alzheimer\u27s Pathobiome Initiative aims to perform comparative molecular analyses of microbes in post mortem brains versus cerebrospinal fluid, blood, olfactory neuroepithelium, oral/nasopharyngeal tissue, bronchoalveolar, urinary, and gut/stool samples. Diverse extraction methodologies, polymerase chain reaction and sequencing techniques, and bioinformatic tools will be evaluated, in addition to direct microbial culture and metabolomic techniques. The goal is to provide a roadmap for detecting infectious agents in patients with mild cognitive impairment or AD. Positive findings would then prompt tailoring of antimicrobial treatments that might attenuate or remit mounting clinical deficits in a subset of patients

Revisited experimental comparison of node-link and matrix representations

Visualizing network data is applicable in domains such as biology, engineering, and social sciences. We report the results of a study comparing the effectiveness of the two primary techniques for showing network data: node-link diagrams and adjacency matrices. Specifically, an evaluation with a large number of online participants revealed statistically significant differences between the two visualizations. Our work adds to existing research in several ways. First, we explore a broad spectrum of network tasks, many of which had not been previously evaluated. Second, our study uses a large dataset, typical of many real-life networks not explored by previous studies. Third, we leverage crowdsourcing to evaluate many tasks with many participants

A new method for 2D gel spot alignment: application to the analysis of large sample sets in clinical proteomics

<p>Abstract</p> <p>Background</p> <p>In current comparative proteomics studies, the large number of images generated by 2D gels is currently compared using spot matching algorithms. Unfortunately, differences in gel migration and sample variability make efficient spot alignment very difficult to obtain, and, as consequence most of the software alignments return noisy gel matching which needs to be manually adjusted by the user.</p> <p>Results</p> <p>We present Sili2DGel an algorithm for automatic spot alignment that uses data from recursive gel matching and returns meaningful Spot Alignment Positions (SAP) for a given set of gels. In the algorithm, the data are represented by a graph and SAP by specific subgraphs. The results are returned under various forms (clickable synthetic gel, text file, etc.). We have applied Sili2DGel to study the variability of the urinary proteome from 20 healthy subjects.</p> <p>Conclusion</p> <p>Sili2DGel performs noiseless automatic spot alignment for variability studies (as well as classical differential expression studies) of biological samples. It is very useful for typical clinical proteomic studies with large number of experiments.</p