Creating a Public Space for Georeferencing Sanborn Maps: A Louisiana Case Study

As institutional archives digitize their historical map collections and make them publicly available online, new methods for engaging with these materials emerge. Georeferencing the maps transforms their content from static images to dynamic map overlays, and allows for the extraction of geographic data like building footprints or place name coordinates. Many organizations have turned to crowdsourcing to georeference their large holdings, and this thesis approaches crowdsourced georeferencing from the perspective of participatory heritage, taking much inspiration from the idea of the archival commons. To test these ideas, a new extension was created for GeoNode—an open source geospatial content management system—that allows users to georeference map documents in a web browser. Further augmentation facilitated direct ingestion of digital content from the Library of Congress Sanborn Map collection, and a pilot project was conducted to engage the public in georeferencing maps of towns and cities across Louisiana. By the end of the project, 66 participants—from within Louisiana and without—had georeferenced all or a portion of 267 different Sanborn map volumes, creating over 1,500 new layers. These layers combine to create mosaics of 138 different communities across the state, including comprehensive coverage of the city of New Orleans in the years between 1885 and 1893—an especially valuable dataset in its own right. Seamless mosaics will be made from these layers and published via the LSU Atlas data portal for long-term public access. This experience led to new ideas for how to better engage citizens with historical maps of their communities, while the underlying construction of the georeferencing system itself provided insight into how users participated in the work. Ultimately, this thesis lays a conceptual foundation for future efforts of a similar nature, whether they pursue exactly the same technological approach or not

A geo-temporal information extraction service for processing descriptive metadata in digital libraries

In the context of digital map libraries, resources are usually described according to metadata records that define the relevant subject, location, time-span, format and keywords. On what concerns locations and time-spans, metadata records are often incomplete or they provide information in a way that is not machine-understandable (e.g. textual descriptions). This paper presents techniques for extracting geotemporal information from text, using relatively simple text mining methods that leverage on a Web gazetteer service. The idea is to go from human-made geotemporal referencing (i.e. using place and period names in textual expressions) into geo-spatial coordinates and time-spans. A prototype system, implementing the proposed methods, is described in detail. Experimental results demonstrate the efficiency and accuracy of the proposed approaches

Exploring place through user-generated content: Using Flickr tags to describe city cores

Terms used to describe city centers, such as Downtown, are key concepts in everyday or vernacular language. Here, we explore such language by harvesting georeferenced and tagged metadata associated with 8 million Flickr images and thus consider how large numbers of people name city core areas. The nature of errors and imprecision in tagging and georeferencing are quantified, and automatically generated precision measures appear to mirror errors in the positioning of images. Users seek to ascribe appropriate semantics to images, though bulk-uploading and bulk-tagging may introduce bias. Between 0.5--2% of tags associated with georeferenced images analyzed describe city core areas generically, while 70% of all georeferenced images analyzed include specific place name tags, with place names at the granularity of city names being by far the most common. Using Flickr metadata, it is possible not only to describe the use of the term Downtown across the USA, but also to explore the borders of city center neighborhoods at the level of individual cities, whilst accounting for bias by the use of tag profiles

The Integrated System for Public Health Monitoring of West Nile Virus (ISPHM-WNV): a real-time GIS for surveillance and decision-making

BACKGROUND: After its first detection in North America in New York in 1999, West Nile virus was detected for the first time in 2002 in the province of Quebec, Canada. This situation forced the Government of Quebec to adopt a public health protection plan against the virus. The plan comprises several fields of intervention including the monitoring of human cases, Corvidae and mosquitoes in order to ensure the early detection of the presence of the virus in a particular area. To help support the monitoring activities, the Integrated System for Public Health Monitoring of West Nile Virus (ISPHM-WNV) has been developed. RESULTS: The ISPHM-WNV is a real-time geographic information system for public health surveillance of West Nile virus and includes information on Corvidae, mosquitoes, humans, horses, climate, and preventive larvicide interventions. It has been in operation in the province of Quebec, Canada, since May 2003. The ISPHM-WNV facilitates the collection, localization, management and analysis of monitoring data; it also allows for the display of the results of analyses on maps, tables and statistical diagrams. CONCLUSION: The system is very helpful for field workers in all regions of the province, as well as for central authorities. It represents the common authoritative source of data for analysis, exchange and decision-making

APREGOAR: Development of a geospatial database applied to local news in Lisbon

Project Work presented as the partial requirement for obtaining a Master's degree in Geographic Information Systems and ScienceHá informações valiosas em formato de texto não estruturado sobre a localização, calendarização e a essências dos eventos disponíveis no conteúdo de notícias digitais. Vários trabalhos em curso já tentam extrair detalhes de eventos de fontes de notícias digitais, mas muitas vezes não com a nuance necssária para representar com precisão onde as coisas realmente acontecem. Alternativamente, os jornalistas poderiam associar manualmente atributos a eventos descritos nos seus artigos enquanto publicam, melhorando a exatidão e a confiança nestes atributos espaciais e temporais. Estes atributos poderiam então estar imediatamente disponíveis para avaliar a cobertura temática, temporal e espacial do conteúdo de uma agência, bem como melhorar a experiência do utilizador na exploração do conteúdo, fornecendo dimensões adicionais que podem ser filtradas. Embora a tecnologia de atribuição de dimensões geoespaciais e temporais para o emprego de aplicaçãoes voltadas para o consumidor não seja novidade, tem ainda de ser aplicada à escala das notícias. Além disso, a maioria dos sistemas existentes suporta apenas uma definição pontual da localização dos artigos, que pode não representar bem o(s) local(is) real(ais) dos eventos descritos. Este trabalho define uma aplicação web de código aberto e uma base de dados espacial subjacente que suporta i) a associação de múltiplos polígonos a representar o local onde cada evento ocorre, os prazos associados aos eventos, em linha com os atributos temáticos tradicionais associados aos artigos de notícias; ii) a contextualização de cada artigo através da adição de mapas de eventos em linha para esclarecer aos leitores onde os eventos do artigo ocorrem; e iii) a exploração dos corpora adicionados através de filtros temáticos, espaciais e temporais que exibem os resultados em mapas de cobertura interactivos e listas de artigos e eventos. O projeto foi aplicado na área da grande Lisboa de Portugal. Para além da funcionalidade acima referida, este projeto constroi gazetteers progressivos que podem ser reutilizados como associações de lugares, ou para uma meta-análise mais aprofundada do lugar, tal como é percebido coloquialmente. Demonstra a facilidade com que estas dimensões adicionais podem ser incorporadas com grade confiança na precisão da definição, geridas, e alavancadas para melhorar a gestão de conteúdo das agências noticiosas, a compreensão dos leitores, a exploração dos investigadores, ou extraídas para combinação com outros conjuntos dos dados para fornecer conhecimentos adicionais.There is valuable information in unstructured text format about the location, timing, and nature of events available in digital news content. Several ongoing efforts already attempt to extract event details from digital news sources, but often not with the nuance needed to accurately represent the where things actually happen. Alternatively, journalists could manually associate attributes to events described in their articles while publishing, improving accuracy and confidence in these spatial and temporal attributes. These attributes could then be immediately available for evaluating thematic, temporal, and spatial coverage of an agency’s content, as well as improve the user experience of content exploration by providing additional dimensions that can be filtered. Though the technology of assigning geospatial and temporal dimensions for the employ of consumer-facing applications is not novel, it has yet to be applied at scale to the news. Additionally, most existing systems only support a single point definition of article locations, which may not well represent the actual place(s) of events described within. This work defines an open source web application and underlying spatial database that supports i) the association of multiple polygons representing where each event occurs, time frames associated with the events, inline with the traditional thematic attributes associated with news articles; ii) the contextualization of each article via the addition of inline event maps to clarify to readers where the events of the article occur; and iii) the exploration of the added corpora via thematic, spatial, and temporal filters that display results in interactive coverage maps and lists of articles and events. The project was applied to the greater Lisbon area of Portugal. In addition to the above functionality, this project builds progressive gazetteers that can be reused as place associations, or for further meta analysis of place as it is colloquially understood. It demonstrates the ease of which these additional dimensions may be incorporated with a high confidence in definition accuracy, managed, and leveraged to improve news agency content management, reader understanding, researcher exploration, or extracted for combination with other datasets to provide additional insights