The Open Navigation Surface Project

Many hydrographic and oceanographic agencies have moved or are moving towards gridded bathymetric products. However, there is no accepted format to allow these grids to be exchanged while maintaining data and metadata integrity. This paper describes the Open Navigation Surface (ONS) Project, which aims to fill this gap. The ONS Project is an open-source software project designed to provide a freely available, portable source-code library to encapsulate gridded bathymetric surfaces with associated uncertainty values. The data file format is called a Bathymetric Attributed Grid (BAG). The BAG is developed and maintained by the ONS Working Group (ONSWG), and the source code is available via the ONS websit

On-line data archives

©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Digital libraries and other large archives of electronically retrievable and manipulable material are becoming widespread in both commercial and scientific arenas. Advances in networking technologies have led to a greater proliferation of wide-area distributed data warehousing with associated data management challenges. We review tools and technologies for supporting distributed on-line data archives and explain our key concept of active data archives, in which data can be, processed on-demand before delivery. We are developing wide-area data warehousing software infrastructure for geographically distributed archives of large scientific data sets, such as satellite image data, that are stored hierarchically on disk arrays and tape silos and are accessed by a variety of scientific and decision support applications. Interoperability is a major issue for distributed data archives and requires standards for server interfaces and metadata. We review present activities and our contributions in developing such standards for different application areas.K. Hawick, P. Coddington, H. James, C. Patte

Decision Support System for facility location problems in fleet management

Businesses that are growing by providing more services, reaching more customers or improving their business strategy, might need to create or relocate a facility location to expand the geographical coverage and improve their services. This decision is complex, and it is crucial to analyse their client locations, journeys and be aware of the factors that may affect their geographical decision. These organisations must weigh all these factors, such as security levels, taxes or costs due to the importance and impact that they can have in the short and long term business strategy. Therefore, the decision-maker needs to ensure that the location is the most profitable site according to the business scope and future perspectives. To help the businesses on this complex decision, this dissertation details the development of a Decision Support System (DSS) capable of providing facility location suggestions based on the existing journeys and the factors that the decision-maker considers more relevant to the company. The developed DSS has three main components: (1) Decision Support System; (2) Geospatial Analysis System; and (3) Facility Location Factors System. The Decision Support System is responsible for producing ordered facility location suggestions by performing the multicriteria decision analysis (MCDA) that implements the TOPSIS algorithm. The Geospatial Analysis System, through the use of the DBSCAN algorithm, is responsible for retrieving the alternatives by identifying the geospatial clusters based on the existing journeys. Lastly, the Facility Location Factors System is responsible for retrieving the criterion by gathering the data from external sources according to the chosen factors. The evaluation analysis shows that the perspective of the users about the assistance of the system by helping them choose appropriate facility location is favourable. This analysis showed that the users agree about the accuracy and the value of the facility location suggestions. The output helps the business managers to make better decisions by returning facility locations that have potential to maximise the company’s profit by reducing transportation and fuel costs and maximise the number of covered customers by expanding their territorial coverage. This project handles data provided by Fonix Telematics from their United Kingdom clients that have relevance to the study, such as a high number of assets, journeys and geographical coverage.As empresas em crescimento por via da disponibilização de mais serviços, do aumento do seu leque de clientes ou da melhoria da sua estratégia, podem pretender criar ou realocar um centro de operações de modo a expandir a sua cobertura geográfica e, consequentemente, melhorar os seus serviços. Esta decisão é complexa e é fundamental analisar vários aspetos, assim como, a localização dos seus clientes, as viagens recorrentes e, acima de tudo, estar consciente dos fatores que podem afetar a sua decisão geográfica. As organizações devem pesar todos esses fatores, assim como níveis de segurança, impostos ou custos, devido à importância e ao impacto que podem ter na estratégia da empresa a curto e a longo prazo. Portanto, o decisor necessita de garantir que o local é rentável e que capta o âmbito do negócio e as perspetivas futuras. De modo a auxiliar as empresas nesta complexa decisão, esta dissertação detalha o processo de desenvolvimento de um Sistema de Apoio à Decisão (SAD) capaz de fornecer um conjunto de sugestões com os locais mais indicados para a criação de um centro de operações com base nas viagens efetuadas e nos fatores que o decisor considera mais relevantes para a organização. O SAD desenvolvido possui três componentes: (1) Decision Support System; (2) Geospatial Analysis System; e (3) Facility Location Factors System. O Decision Support System é responsável por produzir as sugestões geoespaciais, através da Análise de Decisão Multicritério (MCDA) que por sua vez implementa o algoritmo TOPSIS. O Geospatial Analysis System, através da utilização do algoritmo DBSCAN, é responsável por retornar as alternativas através da identificação dos clusters geográficos com base nas viagens existentes. Por último, o Facility Location Factors System é responsável por retornar os critérios, que são compostos por dados recolhidos através de fontes externas de acordo com os fatores previamente selecionados. A avaliação da solução demonstra que a perspetiva dos utilizadores sobre o sistema é positiva e que, de facto, os auxilia na decisão do local mais indicado para as suas instalações. A análise indica ainda que os utilizadores estão de acordo com a precisão e com locais sugeridos para os centros de operações. Estas sugestões auxiliam os decisores a tomarem decisões mais sustentadas, visto que os locais sugeridos possuem potencial para maximizar a rentabilidade da empresa, reduzir os custos de transporte e combustível, assim como maximizar a cobertura de clientes através do posicionamento geográfico. Este trabalho utiliza dados de clientes da Fonix Telematics que atuam no Reino Unido e que possuem relevância para o estudo, como um número significativo de veículos, viagens e cobertura geográfica

GIS-based Decision Support System (DSS) for Recommending Retail Outlet Locations

Many Information Technology (IT) tools play a vital role in the business world due to their wider applicability. Extremely competitive retail environment necessitates retailers to choose new store locations strategically. GIS with its capability to manage, display and analyze business information spatially, is emerging as one of the powerful location intelligence IT tool.  The purpose of this paper is to explore the possibility of strategic retail outlet location through online Decision Support System (DSS) in Hyderabad Metropolitan city, India. The procedure makes use of data, information and software from Web-based Geographical Information Systems (GIS) to generate online analysis, mapping and visualization systems. These procedures are integrated and synchronized with appropriate data layers (multi data layer system) to arrive at better decisions.  This DSS combines different data layers through spatial methodological analysis to arrive at possible solution for ideal retail store location. Keywords: Retail store site selection; spatial data layers; open source web GIS; DSS

Probe-based visual analysis of geospatial simulations

This work documents the design, development, refinement, and evaluation of probes as an interaction technique for expanding both the usefulness and usability of geospatial visualizations, specifically those of simulations. Existing applications that allow the visualization of, and interaction with, geospatial simulations and their results generally present views of the data that restrict the user to a single perspective. When zoomed out, local trends and anomalies become suppressed and lost; when zoomed in, spatial awareness and comparison between regions become limited. The probe-based interaction model integrates coordinated visualizations within individual probe interfaces, which depict the local data in user-defined regions-of-interest. It is especially useful when dealing with complex simulations or analyses where behavior in various localities differs from other localities and from the system as a whole. The technique has been incorporated into a number of geospatial simulations and visualization tools. In each of these applications, and in general, probe-based interaction enhances spatial awareness, improves inspection and comparison capabilities, expands the range of scopes, and facilitates collaboration among multiple users. The great freedom afforded to users in defining regions-of-interest can cause modifiable areal unit problems to affect the reliability of analyses without the user’s knowledge, leading to misleading results. However, by automatically alerting the user to these potential issues, and providing them tools to help adjust their selections, these unforeseen problems can be revealed, and even corrected

Geospatial Data Modeling to Support Energy Pipeline Integrity Management

Several hundred thousand miles of energy pipelines span the whole of North America -- responsible for carrying the natural gas and liquid petroleum that power the continent\u27s homes and economies. These pipelines, so crucial to everyday goings-on, are closely monitored by various operating companies to ensure they perform safely and smoothly. Happenings like earthquakes, erosion, and extreme weather, however -- and human factors like vehicle traffic and construction -- all pose threats to pipeline integrity. As such, there is a tremendous need to measure and indicate useful, actionable data for each region of interest, and operators often use computer-based decision support systems (DSS) to analyze and allocate resources for active and potential hazards. We designed and implemented a geospatial data service, REST API for Pipeline Integrity Data (RAPID) to improve the amount and quality of data available to DSS. More specifically, RAPID -- built with a spatial database and the Django web framework -- allows third-party software to manage and query an arbitrary number of geographic data sources through one centralized REST API. Here, we focus on the process and peculiarities of creating RAPID\u27s model and query interface for pipeline integrity management; this contribution describes the design, implementation, and validation of that model, which builds on existing geospatial standards