Discovery and retrieval of Geographic data using Google


Autoria(s): Casanova, Carlos Abargues
Contribuinte(s)

Llavori, Rafael Berlanga

Data(s)

26/01/2010

26/01/2010

06/03/2009

Resumo

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

The growth of content in the Internet makes the existence of effective ways to retrieve the desired information fundamental. Search engines represent applications that fulfil this need. In these last years it has been clearly increased the number of services and tools to add and use the geographic component of the content published on the World Wide Web, what represents a clear trend towards the so called GeoWeb. This web paradigm promotes the search of content based also in their geographical component. Here is presented a study about the possibilities of using the different services and tools that Google offers to discover and retrieve geographic information. The study is based in the use of Keyhole Markup Language files (KML) to express geographic data and the analysis of their discovery and indexing. This discovery process is done by crawlers and the study tried to obtain objective measures about the time and effectiveness of the process simulating a real case scenario. In the other side the different KML elements that could allocate information and metadata were analyzed. In order to better understand which of these elements are effectively used in the indexing process a test data set composed by KML files containing information in these elements were launched and the obtained results analyzed and commented. With the experiment’s results the use of these services and tools are analyzed as a general solution for Geographic Information Retrieval. Finally some considerations about future studies that could improve these tools usage are exposed.

Identificador

http://hdl.handle.net/10362/2536

Idioma(s)

eng

Relação

Master of Science in Geospatial Technologies;TGEO0011

Direitos

openAccess

Palavras-Chave #Geographic information systems #Google #Geographic information retrieval #Keyhole markup language #Metadata
Tipo

masterThesis