LEGENDiary: web 2.0 y app móvil

LEGENDiary es un geoportal 2.0 que permite compartir y explorar las leyendas y cuentos característicos de las ciudades de una manera dinámica y colaborativa. Muchas veces las leyendas forman parte de la historia y cultura de nuestros pueblos o ciudades, LEGENDiary nos permite conocerlas según el territorio donde se ubican. La iniciativa promueve nuevas formas de conocer y explorar el territorio, en general, y las leyendas y cuentos de nuestros pueblos y ciudades, en particular. Un proyecto que permite a los usuarios interactuar y ser protagonistas de esta experiencia. El proyecto parte inicialmente de un contexto español, y se trata de un proyecto hecho a medida de todas aquellas personas interesadas y con curiosidad en compartir, conocer y explorar las leyendas en el territorio. La combinación de las Tecnologías de la Información Geográfica y las Tecnologías 2.0 es el escenario donde surge LEGENDiary, aportando la componente geográfica a las leyendas y cuentos de los pueblos y ciudades en un contexto colaborativo. La iniciativa se lanza el día 16 de noviembre de 2011 en formato concurso con motivo del Día Internacional de los Sistemas de Información Geográfica (GISDay). Para llevar a cabo la aplicación se han utilizado dos librerías Javascript (Leaflet y jQuery) de código abierto y gratuito que permiten crear de forma rápida y ligera aplicaciones de mapas interactivos a través de navegadores web (de escritorio y móvil). Como mapa base se ha utilizado Open Street Map.LEGENDiary es una iniciativa del Servicio de SIG y Teledetección (SIGTE) de la Universidad de Girona en colaboración con el Departamento de Geografía y la Facultad de Turismo de la misma universidad, y con elapoyo del Hotel Llegendes de Girona

Student's watcher : comparison between ASP.NET and PHP+CSS

"Student’s Watcher” is a small Web application which wants to show in a visual, simple and fast way, the evolution of the students. The main project table displays such things as marks and comments about students. We can add a comment for each mark to explain why this mark. The objective is to be able to know if some student has a problem, how is going his year, marks in other courses, or even, to know if he has a bad week in a different subjects. We can see the evolution of students in past years to do an objective comparison. It also allows inserting global comments of student, we have a list of these, and all professors can add new ones, where we can see more general valuations. “Student’s Watcher” was begun in ASP.net, but finally my project would be developed in PHP, HTML and CSS. This project wants to be a comparison between two of most important languages used nowadays, ASPX and PHP

Servicio Web 3D (W3DS) en Geoserver

Vamos a presentar la primera implementación de código abierto de un servicio W3DS. Esta implementación se realiza a través de Geoserver. El servicio W3DS va a cambiar nuestra forma de manipular los datos en 3D. La visualización de los datos en 3D emitido por el 3DWS se pueden hacer en el navegador, ya que el soporte WebGL ya existe en navegadores recientes. En esta presentación describiremos la propuesta OGC, centrándose principalmente en la operación GetScene, se discute la implementación de dicho servicio, el formato X3D y el estado actual do soporte X3D DOM. También vamos a hablar de soporte 3D en PostGIS 2.0. Demostramos el servicio con los datos de varias ciudades, que muestra cómo importar y publicar datos en 3D. Por último, se mostrará una pequeña biblioteca Javascript OL3 para tomar ventaja de lo servivio W3DS para desarrollar aplicaciones web 3D

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

Validation of ocean model syntheses against hydrography using a new web application

Results are presented from a new web application called OceanDIVA - Ocean Data Intercomparison and Visualization Application. This tool reads hydrographic profiles and ocean model output and presents the data on either depth levels or isotherms for viewing in Google Earth, or as probability density functions (PDFs) of regional model-data misfits. As part of the CLIVAR Global Synthesis and Observations Panel, an intercomparison of water mass properties of various ocean syntheses has been undertaken using OceanDIVA. Analysis of model-data misfits reveals significant differences between the water mass properties of the syntheses, such as the ability to capture mode water properties.

The ICGA on the Web

The ICGA and its members can now communicate with each other and a wider public, as never before. The ICGA website ICGA_W, www.icga.org, will complement the ICGA Journal, providing more space and access to an evolving and wider range of items including both topical news and definitive reference material.

3-5-man chess: Maximals and mzugs

This article reports the combined results of several initiatives in creating and surveying complete suites of endgame tables (EGTs) to the Depth to Mate (DTM) and Depth to Conversion (DTC) metrics. Data on percentage results, maximals and mutual zugzwangs, mzugs, has been filed and made available on the web, as have the DTM EGTs.

GIS in the cloud: implementing a web map service on Google App Engine

Many producers of geographic information are now disseminating their data using open web service protocols, notably those published by the Open Geospatial Consortium. There are many challenges inherent in running robust and reliable services at reasonable cost. Cloud computing provides a new kind of scalable infrastructure that could address many of these challenges. In this study we implement a Web Map Service for raster imagery within the Google App Engine environment. We discuss the challenges of developing GIS applications within this framework and the performance characteristics of the implementation. Results show that the application scales well to multiple simultaneous users and performance will be adequate for many applications, although concerns remain over issues such as latency spikes. We discuss the feasibility of implementing services within the free usage quotas of Google App Engine and the possibility of extending the approaches in this paper to other GIS applications.

xhRank: ranking entities on the Semantic Web

In general, ranking entities (resources) on the Semantic Web (SW) is subject to importance, relevance, and query length. Few existing SW search systems cover all of these aspects. Moreover, many existing efforts simply reuse the technologies from conventional Information Retrieval (IR), which are not designed for SW data. This paper proposes a ranking mechanism, which includes all three categories of rankings and are tailored to SW data.

A lightweight supercomputing web portal for inferring phylogenetic trees

In this paper we describe a lightweight Web portal developed for running computational jobs on a IBM JS21 Bladecenter cluster, ThamesBlue, for inferring and analyzing evolutionary histories. We first discuss the need for leveraging HPC as a enabler for molecular phylogenetics research. We go on to describe how the portal is designed to interface with existing open-source software that is typical of a HPC resource configuration, and how by design this portal is generic enough to be portable to other similarly configured compute clusters, and for other applications.