A System for Interactive Spatial Analysis via Potential Maps

International audienceThis paper presents a new cartographic tool for spatial analysis of social data, using the potential smoothing method. The purpose of this method is to view the spreading of a phenomenon (demographic, economical, social, etc.) in a continuous way, at a macroscopic scale, from data sampled on administrative areas. We aim to offer an interactive tool, accessible through the Web, but guarantying the confidentiality of data. The biggest difficulty is induced by the high complexity of the calculus, dealing with a great amount of data. A distributed architecture is proposed: map computation is made on server-side, using particular optimization techniques, whereas map visualization and parameterisation of the analysis are done on a web-based client, the two parts communicating through a Web protocol

Making Data Accessible: An Overview of Interactive Data Visualization Using D3.js as Applied to a Scientific Dataset : Making a Static Visualization Interactive

Technology is moving at a very fast pace, but data is still represented as tables, static graphs and infographics that do not create an impact on the population at large. Excluding the scientific and educational communities, to the common individual information should be displayed in an entertaining manner. This project set out to fulfill this goal by using known technologies from D3js, design guidelines, CSS3 animations, and HTML5 elements to real scientific data from the United States National Climate Data Center. The final product is a one page web application displaying 3,000,000 years of global temperatures in a visual format. The data was plotted using D3js, made interactive with JavaScript and laid out using Twitter Bootstrap. What can be concluded is that it is possible to create interactive content with current technologies, but the process is still only achievable after extensive study of the technologies involved. Further development has to be made for data interactive tools to become easier to use and to produce large-scale interactive web applications involving data display and analysis. The advancement of interactive visualizations are also relevant as studies have shown that engaging lectures lead to a statistically significant higher average on unit exams compared with traditional didactic lectures. This could be hypothesized to be the same for interactive data and this was confirmed by a small questionnaire

A Web-GIS Online Vector Data Editing Method Based on Multi-scale Representation Data Structure

From analysis of the factors affecting the service quality of Web GIS, the key factor in the efficiency of online vector data interactive editing is to control the size of the relevant data set. This paper puts forward an online vector data editing method based on the multi-scale representation data structure DBLG-tree. It designs WindowingQuery for large geometric features. Combined with SimplifyQuery, it can effectively control the vertex scale of the geometric features. At the same time, the sub-feature resulting from WindowingQuery retains the connection with the original feature and can be merged and updated. It provides DownsizeQuery which can directly control the volume of query result from the data set, so as to adapt to the performance of different browsers and mobile devices. Research shows that the execution time of DownsizeQuery under the support of multi-scale representation data structure is stable, and the size of the queried and updated data set is also stable. The upper bounded query time and query results ensure the response time of online interactive visualization and updating of the vector features

{EpiExplorer}: {Live} Exploration and Global Analysis of Large Epigenomic Datasets

ABSTRACT: Epigenome mapping consortia are generating resources of tremendous value for studying epigenetic regulation. To maximize their utility and impact, new tools are needed that facilitate interactive analysis of epigenome datasets. Here we describe EpiExplorer, a web tool for exploring genome and epigenome data on a genomic scale. We demonstrate EpiExplorer's utility by describing a hypothesis-generating analysis of DNA hydroxymethylation in relation to public reference maps of the human epigenome. All EpiExplorer analyses are performed dynamically within seconds, using an efficient and versatile text indexing scheme that we introduce to bioinformatics. EpiExplorer is available at http://epiexplorer.mpi-inf.mpg.de

Analyzing a 35-Year Hourly Data Record: Why So Difficult?

At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data