Hydrological Models as Web Services: An Implementation using OGC Standards

<p>Presentation for the HIC 2012 - 10th International Conference on Hydroinformatics. "Understanding Changing Climate and Environment and Finding Solutions" Hamburg, Germany July 14-18, 2012</p> <p> </p

Data infrastructures and spatial models for biodiversity assessment and analysis: applications to vertebrate communities.

In conservation biology the computation of biodiversity maps, based on statistical models is a central concern. These maps, produced with objective and repeatable methods are an essential tool for conservation and monitoring programs as well as for landuse planning. Since the computation of biodiversity maps requires complex and time consuming procedures for data processing and analysis, it is necessary to design methods for homogeneous, scalable and repeatable data management and analysis. Moreover, the huge volume of data used in ecological modelling requires suitable software architectures to store, analyze, retrieve and distribute information in order to support research and management actions in due time. First of all we developed an analysis system (SOS - Species Open Spreader) providing statistical and mathematical models to predict species distribution in relation to a set of predictive environmental and geographical variables The system is composed of a module for data input/output toward and from the GIS and of a package of scripts for the application of different modelling techniques. At present, three statistical techniques are integrated in SOS: Logistic Regression Analysis (LRA), Environmental Niche Factor Analysis (ENFA) and flexible Discriminant Analysis with method BRUTO. Furthermore, two empirical spatial methods of analysis are available within SOS: Habitat Suitability Index (HSI) and Spatial Overlay. The system is designed to work with the GIS (Geographical Information System) soft-ware GRASS and the statistical environment R, coupled together through the SPGRASS6 library. Three different outputs are expected: text and graphical outputs with statistical results and suitability maps. Second, we tested the use of spatial Database Management Systems (Spatial DBMS) to handle wildlife and socio-economic data and we developed a web database application to provide facilities for database access. The information system was built for the Meru district (Tanzania) in the context of an Italian cooperation project of land use planning in Maasai rural areas. We tested two di_erent solutions: SpatiaLite and PostgreSQL-PostGIS; they both offer advanced technical facilities and spatial extensions to analyze spatial data. SpatiaLite is a new solution and offers the main advantages to consist of a unique file and to present a user-friendly interface, which make it the best solution for many applications. in spite of this we used PostgreSQL-PostGIS since it represents a well-established information system supported by libraries for web applications development. We applied SOS to three case studies at different spatial scale: Brescia plain (small scale), Mount Meru region - Tanzania (medium scale) and Lombardy region (big scale) in order to produce maps of species potential distribution and biodiversity maps for planning and management. We applied logistic regression analyses to compute models and ROC analysis for classification performance evaluation. The automation of processes through SOS gave us the possibility to build models for a large number of vertebrate species. The analysis produced very reliable results at middle and big scale while regression methods did not converge at small scale. This is probably due to habitat homogeneity and to the use of environmental variables with an insufficient level of detail. The potential distribution and biodiversity maps produced also had in all cases an applicative use in fact we used mammal species models computed for Mt. Meru region to produce a map of biodiversity within the area: this map represents an informative base for land use planning at village level within a cooperation project for Maasai economic development and environmental redemption. Amphibians and reptiles models, computed for Lombardy, represent a good informative base for planning management actions in the region

Models of technology and change in higher education: an international comparative survey on the current and future use of ICT in higher education

The aim of this study is to investigate which scenarios are emerging with respect to the use of ICT in higher education and how future developments can be predicted and strategic choices can be based on that. It seeks to answer the following questions:\ud What strategic responses do institutions make with respect to the use of ICT; Which external conditions and developments influence these choices; Which external and internal conditions and measures are taken in order to achievestrategic targets; What are the implications for technology use, teaching and learning processes and staff? \ud The study applies an international comparative methodology and is carried out in the Netherlands, Germany, Norway, the United Kingdom, Australia, Finland and the USA. Data were collected through Web-based questionnaires tailored to three different response groups: decision makers, support staff and instructors. In total 693 persons responded to the questionnaire. This implies that between 20 and 50 percent of the institutions in the various countries responded (institutional data were also gathered), with the exception of the USA where the response was much lower

Observation Centric Sensor Data Model

Management of sensor data requires metadata to understand the semantics of observations. While e-science researchers have high demands on metadata, they are selective in entering metadata. The claim in this paper is to focus on the essentials, i.e., the actual observations being described by location, time, owner, instrument, and measurement. The applicability of this approach is demonstrated in two very different case studies

1st INCF Workshop on Sustainability of Neuroscience Databases

The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability