Historical collaborative geocoding

The latest developments in digital have provided large data sets that can increasingly easily be accessed and used. These data sets often contain indirect localisation information, such as historical addresses. Historical geocoding is the process of transforming the indirect localisation information to direct localisation that can be placed on a map, which enables spatial analysis and cross-referencing. Many efficient geocoders exist for current addresses, but they do not deal with the temporal aspect and are based on a strict hierarchy (..., city, street, house number) that is hard or impossible to use with historical data. Indeed historical data are full of uncertainties (temporal aspect, semantic aspect, spatial precision, confidence in historical source, ...) that can not be resolved, as there is no way to go back in time to check. We propose an open source, open data, extensible solution for geocoding that is based on the building of gazetteers composed of geohistorical objects extracted from historical topographical maps. Once the gazetteers are available, geocoding an historical address is a matter of finding the geohistorical object in the gazetteers that is the best match to the historical address. The matching criteriae are customisable and include several dimensions (fuzzy semantic, fuzzy temporal, scale, spatial precision ...). As the goal is to facilitate historical work, we also propose web-based user interfaces that help geocode (one address or batch mode) and display over current or historical topographical maps, so that they can be checked and collaboratively edited. The system is tested on Paris city for the 19-20th centuries, shows high returns rate and is fast enough to be used interactively.Comment: WORKING PAPE

Technology Integration around the Geographic Information: A State of the Art

One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented

Interpreting Spatial Language in Image Captions

The map as a tool for accessing data has become very popular in recent years, but a lot of data do not have the necessary spatial meta-data to allow for that. Some data such as photographs however have spatial information in their captions and if this could be extracted, then they could be made available via map-based interfaces. Towards this goal, we introduce a model and spatio-linguistic reasoner for interpreting the spatial information in image captions that is based upon quantitative data about spatial language use acquired directly from people. Spatial language is inherently vague, and both the model and reasoner have been designed to incorporate this vagueness at the quantitative level and not only qualitatively

A Decentralised Location-Based Reputation Management System in the IoT using Blockchain

Weerapanpisit, P., Trilles, S., Huerta, J., & Painho, M. (2022). A Decentralised Location-Based Reputation Management System in the IoT using Blockchain. IEEE Internet of Things Journal. [Advanced online publication on 31 January 2022]. https://doi.org/10.1109/JIOT.2022.3147478 ------------------------- Funding: This study was supported by the TRUST4IoE project of the Programa Estatal de Proyectos de I+D de Generaci´on de Conocimiento of the Spanish government (grant number PID2019-104065GA-I00). Sergio Trilles has been funded by the postdoctoral Juan de la Cierva fellowship programme of the Spanish Ministry for Science and Innovation (IJC2018- 035017-I).The Internet of Things allows an object to connect to the Internet and observe or interact with a physical phenomenon. The communication technologies allow one IoT device to discover and communicate with another in order to exchange services, in a similar way to what humans do in their social networks. Knowing the reputation of another device is important to consider whether it is trustworthy before establishing a new connection and thus avoid possible unexpected behaviours as a consequence. Trustworthiness, as a property of a device, can be affected by different factors including its geographical location. Hence, this research work proposes an architecture to manage reputation values of end devices in an IoT system based on the area where they are located. A cloud-fog-edge architecture is proposed, where the fog layer uses the Blockchain technology to keep the reputation management system consistent and fault-tolerant across different nodes. The location-based part of the system was done by storing geographical areas in Smart Contracts (coined as Geospatial Smart Contracts) and making the reputation values subject to different regions depending on the geographical location of the device. To reduce the complexity of the spatial computation, the geographical data are geocoded by either one of two different spatial indexing techniques. This work also introduced two different structures for storing geocoded areas based on either cell-list or tree-structure. Finally, three experiments to test the proposed architecture are presented, to deploy the architecture in IoT devices, and to compare the two geocoding techniques in Smart Contracts.authorsversionepub_ahead_of_prin

Decentralised location-based reputation management system in IOT using blockchain

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesInternet of Things (IoT) allows an object to connect to the internet network and observe or interact with a physical phenomenon. The communication technologies allow an IoT device to discover and communicate with another one to exchange services like humans do in their social network. Knowing the reputation of another device is important to consider if it will trust before establishing a new connection to avoid an unexpected behaviour. The reputation of a device can also be varied depending on its geographical location. Thus, this thesis proposed an architecture to manage reputation values of end devices in an IoT system, based on their located area. To avoid a hard workload of the system in the cloud layer, the proposed architecture follows the cloud-fog-edge concept by adding an intermediate layer called a fog layer. In this layer, multiple smaller devices are distributed, so it used the Blockchain technology to keep the reputation management to be consistent and fault-tolerant across di erent nodes in the layer. Ethereum, which is a Blockchain implementation, was used in this work to ease the management functionalities, because it allows the Blockchain network to run a decentralised application through the Smart Contracts. The location-based part of the system was done by storing geographical areas in the Smart Contracts, and make the reputation values to be subjected to di erent regions depending on device geographical location. To reduce the spatial computation complexity in the Smart Contracts, the geographical data are geocoded by either one of two di erent spatial indexing techniques called Geohash and S2. This work introduced three experiments to test the proposed architecture, to deploy the architecture in IoT devices, and to compare the two geocoding techniques in the Smart Contracts. It also additionally proposed a compression algorithm of the geocoded data. The results showed that the proposed architecture is able to serve the objective of managing the reputation values based on location in a decentralised way. The test case scenario also demonstrated that the IoT devices were able to work as a Blockchain node. They also were able to discover the service providers in an area and obtain their reputation values by querying through the fog layer. Lastly, the comparison experiment results showed that Geohash performed better inside the developed Smart Contracts, while S2 encoded the data much faster outside the Smart Contracts. The proposed compression algorithm of geocoded data resulted in a signi cant size reduction, but it was computationally heavier in the developed Smart Contracts

Towards place-based exploration of Instagram: Using co-design to develop an interdisciplinary geovisualization prototype

An abundance of geographic information is hidden within texts and multimedia objects that has the potential to enrich our knowledge about the relationship between people and places. One such example is the geographic information embedded within user-generated content collected and curated by the social media giants. Such geographic data can be encoded either explicitly as geotags or implicitly as geographical references expressed as texts that comprise part of a title or image caption. To use such data for knowledge building there is a need for new mapping interfaces. These interfaces should support both data integration and visualization, and geographical exploration with open-ended discovery. Based on a user scenario on the Via Francigena (a significant European cultural route), we set out to adapt an existing humanities interface to support social and spatial exploration of how the route is perceived. Our dataset was derived from Instagram. We adopted a thinking by doing approach to co-design an interdisciplinary prototype and discuss the six stages of activity, beginning with the definition of the use case and ending in experimentation with a working technology prototype. Through reflection on the process of tool modification and an in-depth exploration of the data encoding, we were better able to understand the strengths and limitations of the data, the tool, and the underlying workflows. This in-depth knowledge helped us to define a set of requirements for tools and data that will serve as a valuable contribution for those engaged in the design of deep mapping interfaces for place-based research

Geographic Knowledge Graph Summarization

Geographic knowledge graphs play a significant role in the geospatial semantics paradigm for fulfilling the interoperability, the accessibility, and the conceptualization demands in geographic information science. However, due to the immense quantity of information accompanying and the enormous diversity of geographic knowledge graphs, there are many challenges that hinder the applicability and mass adoption of such useful structured knowledge. In order to tackle these challenges, this dissertation focuses on devising ways in which geographic knowledge graphs can be digested and summarized. Such a summarization task, on the one hand lifts the burden of information overload for end users, on the other hand facilitates the reduction of data storage, speeds up queries, and helps eliminate noise. The main contribution of this dissertation is that it introduces the general concept of geospatial inductive bias and explains different ways this idea can be used in the geographic knowledge graph summarization task. By decomposing the task into separate but related components, this dissertation is based upon three peer-reviewed articles which focus on the hierarchical place type structure, multimedia leaf nodes, and general relation and entity components respectively. A spatial knowledge map interface that illustrates the effectiveness of summarizing geographic knowledge graphs is presented. Throughout the dissertation, top-down knowledge engineering and bottom-up knowledge learning methods are integrated. We hope this dissertation would promote the awareness of this fascinating area and motivate researchers to investigate related questions

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

Reddit: a novel data source for cultural ecosystem service studies

Social media sites have been gaining traction as a source of novel data for environmental research, particularly for cultural ecosystem service (CES) assessments. However, Reddit, a discussion-based site, has yet to establish itself as an important source of data for CES research, possibly due to researchers not being aware of its potential applications or because Reddit posts lack georeferencing information. Here, we demonstrate how researchers can search Reddit for CES datasets related to recreation and how specific pages on Reddit may provide data for other CES such as aesthetics. Using named-entity recognition, we developed an automated method of geocoding the approximate location of where images in Reddit posts were taken. Furthermore, we compare posts from Reddit and Flickr for a range of recreational activities and compare the content and textual metadata of images relating to hiking. Though there is potential for Reddit data to be used in spatial analysis, we highlight the limitations associated with georeferencing posts. We recommend that data from Reddit is best suited to assessing general trends in CES, either for a given service or place. By demonstrating the value of big data from Reddit we hope to encourage its inclusion in future CES and environmental research