Search improvement within the geospatial web in the context of spatial data infrastructures

El trabajo desarrollado en esta tesis doctoral demuestra que es posible mejorar la búsqueda en el contexto de las Infraestructuras de Datos Espaciales mediante la aplicación de técnicas y buenas prácticas de otras comunidades científicas, especialmente de las comunidades de la Web y de la Web Semántica (por ejemplo, Linked Data). El uso de las descripciones semánticas y las aproximaciones basadas en el contenido publicado por la comunidad geoespacial pueden ayudar en la búsqueda de información sobre los fenómenos geográficos, y en la búsqueda de recursos geoespaciales en general. El trabajo comienza con un análisis de una aproximación para mejorar la búsqueda de las entidades geoespaciales desde la perspectiva de geocodificación tradicional. La arquitectura de geocodificación compuesta propuesta en este trabajo asegura una mejora de los resultados de geocodificación gracias a la utilización de diferentes proveedores de información geográfica. En este enfoque, el uso de patrones estructurales de diseño y ontologías en esta aproximación permite una arquitectura avanzada en términos de extensibilidad, flexibilidad y adaptabilidad. Además, una arquitectura basada en la selección de servicio de geocodificación permite el desarrollo de una metodología de la georreferenciación de diversos tipos de información geográfica (por ejemplo, direcciones o puntos de interés). A continuación, se presentan dos aplicaciones representativas que requieren una caracterización semántica adicional de los recursos geoespaciales. El enfoque propuesto en este trabajo utiliza contenidos basados en heurísticas para el muestreo de un conjunto de recursos geopesaciales. La primera parte se dedica a la idea de la abstracción de un fenómeno geográfico de su definición espacial. La investigación muestra que las buenas prácticas de la Web Semántica se puede reutilizar en el ámbito de una Infraestructura de Datos Espaciales para describir los servicios geoespaciales estandarizados por Open Geospatial Consortium por medio de geoidentificadores (es decir, por medio de las entidades de una ontología geográfica). La segunda parte de este capítulo desglosa la aquitectura y componentes de un servicio de geoprocesamiento para la identificación automática de ortoimágenes ofrecidas a través de un servicio estándar de publicación de mapas (es decir, los servicios que siguen la especificación OGC Web Map Service). Como resultado de este trabajo se ha propuesto un método para la identificación de los mapas ofrecidos por un Web Map Service que son ortoimágenes. A continuación, el trabajo se dedica al análisis de cuestiones relacionadas con la creación de los metadatos de recursos de la Web en el contexto del dominio geográfico. Este trabajo propone una arquitectura para la generación automática de conocimiento geográfico de los recursos Web. Ha sido necesario desarrollar un método para la estimación de la cobertura geográfica de las páginas Web. Las heurísticas propuestas están basadas en el contenido publicado por os proveedores de información geográfica. El prototipo desarrollado es capaz de generar metadatos. El modelo generado contiene el conjunto mínimo recomendado de elementos requeridos por un catálogo que sigue especificación OGC Catalogue Service for the Web, el estandar recomendado por deiferentes Infraestructuras de Datos Espaciales (por ejemplo, the Infrastructure for Spatial Information in the European Community (INSPIRE)). Además, este estudio determina algunas características de la Web Geoespacial actual. En primer lugar, ofrece algunas características del mercado de los proveedores de los recursos Web de la información geográfica. Este estudio revela algunas prácticas de la comunidad geoespacial en la producción de metadatos de las páginas Web, en particular, la falta de metadatos geográficos. Todo lo anterior es la base del estudio de la cuestión del apoyo a los usuarios no expertos en la búsqueda de recursos de la Web Geoespacial. El motor de búsqueda dedicado a la Web Geoespacial propuesto en este trabajo es capaz de usar como base un motor de búsqueda existente. Por otro lado, da soporte a la búsqueda exploratoria de los recursos geoespaciales descubiertos en la Web. El experimento sobre la precisión y la recuperación ha demostrado que el prototipo desarrollado en este trabajo es al menos tan bueno como el motor de búsqueda remoto. Un estudio dedicado a la utilidad del sistema indica que incluso los no expertos pueden realizar una tarea de búsqueda con resultados satisfactorios

Exploring multi-granular documentation strategies for the representation, discovery and use of geographic information

This thesis explores how digital representations of geography and Geographic Information (GI) may be described, and how these descriptions facilitate the use of the resources they depict. More specifically, it critically examines existing geospatial documentation practices and aims to identify opportunities for refinement therein, whether when used to signpost those data assets documented, for managing and maintaining information assets, or to assist in resource interpretation and discrimination. Documentation of GI can therefore facilitate its utilisation; it can be reasonably expected that by refining documentation practices, GI hold the potential for being better exploited. The underpinning theme connecting the individual papers of the thesis is one of multi-granular documentation. GI may be recorded at varying degrees of granularity, and yet traditional documentation efforts have predominantly focussed on a solitary level (that of the geospatial data layer). Developing documentation practices to account for other granularities permits the description of GI at different levels of detail and can further assist in realising its potential through better discovery, interpretation and use. One of the aims of the current work is to establish the merit of such multi-granular practices. Over the course of four research papers and a short research article, proprietary as well as open source software approaches are accordingly presented and provide proof-of-concept and conceptual solutions that aim to enhance GI utilisation through improved documentation practices. Presented in the context of an existing body of research, the proposed approaches focus on the technological infrastructure supporting data discovery, the automation of documentation processes and the implications of describing geospatial information resources of varying granularity. Each paper successively contributes to the notion that geospatial resources are potentially better exploited when documentation practices account for the multi-granular aspects of GI, and the varying ways in which such documentation may be used. In establishing the merit of multi-granular documentation, it is nevertheless recognised in the current work that instituting a comprehensive documentation strategy at several granularities may be unrealistic for some geospatial applications. Pragmatically, the level of effort required would be excessive, making universal adoption impractical. Considering however the ever-expanding volumes of geospatial data gathered and the demand for ways of managing and maintaining the usefulness of potentially unwieldy repositories, improved documentation practices are required. A system of hierarchical documentation, of self-documenting information, would provide for information discovery and retrieval from such expanding resource pools at multiple granularities, improve the accessibility of GI and ultimately, its utilisation

HYDROSEEK: an ontology-aided data discovery system for hydrologic sciences

Search engines have made considerable contributions to the overall web experience. However locating scientific data remains a problem since databases are not readily accessible by search engine bots. Considering different temporal, spatial and thematic coverage of different scientific data repositories, especially for interdisciplinary research it is typically necessary to work with multiple data sources. Today integration of hydrologic data sources are mostly at the level of content aggregation by providing links to several data providers on a web page. However being able to query multiple databases simultaneously is a feature that has been sought after since the first data repositories; USGS’ National Water Information System (NWIS) and EPA’s Storage and Retrieval System (EPA STORET) came online. This study examines the current state of hydrologic data availability and dissemination in the US. It identifies the data accessibility problem and suggests a data discovery mechanism named Hydroseek as a solution. Hydroseek enables querying multiple hydrologic data repositories through a single interface and effectively combines spatial, temporal and thematic aspects of search in order to make it possible to discover more of the desired data in less time. It provides a unified view despite heterogeneity issues within and among data repositories, allows data discovery using keywords which eliminates the need to know source specific parameter codes, improves data browsing capabilities by incorporating data classification based on conceptual hierarchy and has an interface design capable of providing access to a large data inventory without overwhelming the user. System’s performance was evaluated based on statistical analysis of a user study in which users were asked to perform a certain data retrieval task using currently available systems and Hydroseek.Ph.D., Civil Engineering -- Drexel University, 200

Strategies and Approaches for Exploiting the Value of Open Data

Data is increasingly permeating into all dimensions of our society and has become an indispensable commodity that serves as a basis for many products and services. Traditional sectors, such as health, transport, retail, are all benefiting from digital developments. In recent years, governments have also started to participate in the open data venture, usually with the motivation of increasing transparency. In fact, governments are one of the largest producers and collectors of data in many different domains. As the increasing amount of open data and open government data initiatives show, it is becoming more and more vital to identify the means and methods how to exploit the value of this data that ultimately affects various dimensions. In this thesis we therefore focus on researching how open data can be exploited to its highest value potential, and how we can enable stakeholders to create value upon data accordingly. Albeit the radical advances in technology enabling data and knowledge sharing, and the lowering of barriers to information access, raw data was given only recently the attention and relevance it merits. Moreover, even though the publishing of data is increasing at an enormously fast rate, there are many challenges that hinder its exploitation and consumption. Technical issues hinder the re-use of data, whilst policy, economic, organisational and cultural issues hinder entities from participating or collaborating in open data initiatives. Our focus is thus to contribute to the topic by researching current approaches towards the use of open data. We explore methods for creating value upon open (government) data, and identify the strengths and weaknesses that subsequently influence the success of an open data initiative. This research then acts as a baseline for the value creation guidelines, methodologies, and approaches that we propose. Our contribution is based on the premise that if stakeholders are provided with adequate means and models to follow, then they will be encouraged to create value and exploit data products. Our subsequent contribution in this thesis therefore enables stakeholders to easily access and consume open data, as the first step towards creating value. Thereafter we proceed to identify and model the various value creation processes through the definition of a Data Value Network, and also provide a concrete implementation that allows stakeholders to create value. Ultimately, by creating value on data products, stakeholders participate in the global data economy and impact not only the economic dimension, but also other dimensions including technical, societal and political