Geospatial Semantics

Geospatial semantics is a broad field that involves a variety of research areas. The term semantics refers to the meaning of things, and is in contrast with the term syntactics. Accordingly, studies on geospatial semantics usually focus on understanding the meaning of geographic entities as well as their counterparts in the cognitive and digital world, such as cognitive geographic concepts and digital gazetteers. Geospatial semantics can also facilitate the design of geographic information systems (GIS) by enhancing the interoperability of distributed systems and developing more intelligent interfaces for user interactions. During the past years, a lot of research has been conducted, approaching geospatial semantics from different perspectives, using a variety of methods, and targeting different problems. Meanwhile, the arrival of big geo data, especially the large amount of unstructured text data on the Web, and the fast development of natural language processing methods enable new research directions in geospatial semantics. This chapter, therefore, provides a systematic review on the existing geospatial semantic research. Six major research areas are identified and discussed, including semantic interoperability, digital gazetteers, geographic information retrieval, geospatial Semantic Web, place semantics, and cognitive geographic concepts.Comment: Yingjie Hu (2017). Geospatial Semantics. In Bo Huang, Thomas J. Cova, and Ming-Hsiang Tsou et al. (Eds): Comprehensive Geographic Information Systems, Elsevier. Oxford, U

A geo-service semantic integration in Spatial Data Infrastructures

In this paper we focus on the semantic heterogeneity problem as one of the main challenges in current Spatial Data Infrastructures (SDIs). We first report on the state of the art in reducing such a heterogeneity in SDIs. We then consider a particular geo-service integration scenario. We discuss an approach of how to semantically coordinate geographic services, which is based on a view of the semantics of web service coordination, implemented by using the Lightweight Coordination Calculus (LCC) language. In this approach, service providers share explicit knowledge of the interactions in which their services are engaged and these models of interaction are used operationally as the anchor for describing the semantics of the interaction. We achieve web service discovery and integration by using semantic matching between particular interactions and web service descriptions. For this purpose we introduce a specific solution, called structure preserving semantic matching. We present a real world application scenario to illustrate how semantic integration of geo web services can be performed by using this approach. Finally, we provide a preliminary evaluation of the solution discussed

Класифікація засобів та методів семантичного пошуку в Web

Розглянуто проблеми, пов’язані з удосконаленням пошуку інформації у відкритому середовищі, обґрунтована потреба в його семантизації. Проаналізовано сучасний стан та перспективи розвитку систем семантичного пошуку, орієнтованих на обробку інформаційних ресурсів Web, розглянуто критерії класифікації таких систем. В цьому аналізі значна увага приділяється використанню у семантичному пошуку онтологій, що містять знання щодо предметної області пошуку та користувача, для якого виконується пошук. На основі аналізу властивостей існуючих систем семантичного пошуку з точки зору цих критеріїв виділені області подальшого вдосконалення цих систем, запропоновано їх реалізацію у системі семантичного пошуку “МАІПС”.Рассмотрены проблемы, связанные с усовершенствованием поиска информации в открытой среде, обоснована потребность в ее семантизации. Проанализировано современное состояние и перспективы развития систем семантического поиска, ориентированных на обработку информационных ресурсов Web, рассмотрены критерии классификации таких систем. В этом анализе значительное внимание отводится использованию в семантическом поиске онтологий, которые содержат знания относительно предметной области поиска и относительно пользователя, для которого выполняется поиск. На основе анализа свойств существующих систем семантического поиска с точки зрения этих критериев выделенные области дальнейшего усовершенствования этих систем, предложена их реализация в системе семантического поиска "МАИПС".Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability

Similarity-Based Information Retrieval and its Role within Spatial Data Infrastructures

While similarity has gained in importance in research about information retrieval on the (geospatial) semantic Web, similarity-based search paradigms and their integration into existing spatial data infrastructures have not been examined in detail so far. In this paper, intensional and extensional paradigms for similarity-based information retrieval are introduced. The differences between these paradigms with respect to the query and results are pointed out. Web user interfaces implementing two of these paradigms are presented, and steps towards the integration of the SIM-DL similarity theory into a spatial data infrastructure are discussed. Remaining difficulties are highlighted and directions of further work are given.JRC.H.6-Spatial data infrastructure

A conceptual framework and a risk management approach for interoperability between geospatial datacubes

De nos jours, nous observons un intérêt grandissant pour les bases de données géospatiales multidimensionnelles. Ces bases de données sont développées pour faciliter la prise de décisions stratégiques des organisations, et plus spécifiquement lorsqu’il s’agit de données de différentes époques et de différents niveaux de granularité. Cependant, les utilisateurs peuvent avoir besoin d’utiliser plusieurs bases de données géospatiales multidimensionnelles. Ces bases de données peuvent être sémantiquement hétérogènes et caractérisées par différent degrés de pertinence par rapport au contexte d’utilisation. Résoudre les problèmes sémantiques liés à l’hétérogénéité et à la différence de pertinence d’une manière transparente aux utilisateurs a été l’objectif principal de l’interopérabilité au cours des quinze dernières années. Dans ce contexte, différentes solutions ont été proposées pour traiter l’interopérabilité. Cependant, ces solutions ont adopté une approche non systématique. De plus, aucune solution pour résoudre des problèmes sémantiques spécifiques liés à l’interopérabilité entre les bases de données géospatiales multidimensionnelles n’a été trouvée. Dans cette thèse, nous supposons qu’il est possible de définir une approche qui traite ces problèmes sémantiques pour assurer l’interopérabilité entre les bases de données géospatiales multidimensionnelles. Ainsi, nous définissons tout d’abord l’interopérabilité entre ces bases de données. Ensuite, nous définissons et classifions les problèmes d’hétérogénéité sémantique qui peuvent se produire au cours d’une telle interopérabilité de différentes bases de données géospatiales multidimensionnelles. Afin de résoudre ces problèmes d’hétérogénéité sémantique, nous proposons un cadre conceptuel qui se base sur la communication humaine. Dans ce cadre, une communication s’établit entre deux agents système représentant les bases de données géospatiales multidimensionnelles impliquées dans un processus d’interopérabilité. Cette communication vise à échanger de l’information sur le contenu de ces bases. Ensuite, dans l’intention d’aider les agents à prendre des décisions appropriées au cours du processus d’interopérabilité, nous évaluons un ensemble d’indicateurs de la qualité externe (fitness-for-use) des schémas et du contexte de production (ex., les métadonnées). Finalement, nous mettons en œuvre l’approche afin de montrer sa faisabilité.Today, we observe wide use of geospatial databases that are implemented in many forms (e.g., transactional centralized systems, distributed databases, multidimensional datacubes). Among those possibilities, the multidimensional datacube is more appropriate to support interactive analysis and to guide the organization’s strategic decisions, especially when different epochs and levels of information granularity are involved. However, one may need to use several geospatial multidimensional datacubes which may be semantically heterogeneous and having different degrees of appropriateness to the context of use. Overcoming the semantic problems related to the semantic heterogeneity and to the difference in the appropriateness to the context of use in a manner that is transparent to users has been the principal aim of interoperability for the last fifteen years. However, in spite of successful initiatives, today's solutions have evolved in a non systematic way. Moreover, no solution has been found to address specific semantic problems related to interoperability between geospatial datacubes. In this thesis, we suppose that it is possible to define an approach that addresses these semantic problems to support interoperability between geospatial datacubes. For that, we first describe interoperability between geospatial datacubes. Then, we define and categorize the semantic heterogeneity problems that may occur during the interoperability process of different geospatial datacubes. In order to resolve semantic heterogeneity between geospatial datacubes, we propose a conceptual framework that is essentially based on human communication. In this framework, software agents representing geospatial datacubes involved in the interoperability process communicate together. Such communication aims at exchanging information about the content of geospatial datacubes. Then, in order to help agents to make appropriate decisions during the interoperability process, we evaluate a set of indicators of the external quality (fitness-for-use) of geospatial datacube schemas and of production context (e.g., metadata). Finally, we implement the proposed approach to show its feasibility

Credibility assessment and labelling of map mashups

The Web 2.0 revolution has changed the culture of mapping by opening it up to a wider range of users and creators. Map mashups, in particular, are being widely used to map variety of information. There is, however, no gatekeeper to validate the correctness of the information presented. The purpose of this research was to understand better what it is that influence users’ perceived credibility and trust within a map mashup presentation and to support the future implementation of automated credibility assessment and labelling of map mashup applications. This research has been conducted in three stages using mixed method approaches. The objective of the first stage was to examine the influence of metadata related to sources, specifically the map producer and map supplier, on respondents’ assessment of the credibility of map mashup information. The findings indicate a low influence of the tested metadata and a high influence of visual cue elements on users’ credibility assessment. Only half of the respondents used the metadata whilst the other half did not include it in their assessment. These findings became the basis of stage two, which was to examine the influence of colour coded traffic light (CCTL) labelling on respondents’ assessment of credibility. From the findings, the probability of respondents making informed judgements by choosing a high credibility map based on this rating label (CCTL) was three times higher than where only the metadata was presented. The third stage was to propose a conceptual framework to support the implementation of automated credibility labelling for map mashup applications. The framework was proposed on the basis of thorough reviews from the literature. The suggested parameters and approaches are not limited to assess credibility of information in the map mashup context, but could be applied to other Web GIS applications

Credibility assessment and labelling of map mashups

The Web 2.0 revolution has changed the culture of mapping by opening it up to a wider range of users and creators. Map mashups, in particular, are being widely used to map variety of information. There is, however, no gatekeeper to validate the correctness of the information presented. The purpose of this research was to understand better what it is that influence users’ perceived credibility and trust within a map mashup presentation and to support the future implementation of automated credibility assessment and labelling of map mashup applications. This research has been conducted in three stages using mixed method approaches. The objective of the first stage was to examine the influence of metadata related to sources, specifically the map producer and map supplier, on respondents’ assessment of the credibility of map mashup information. The findings indicate a low influence of the tested metadata and a high influence of visual cue elements on users’ credibility assessment. Only half of the respondents used the metadata whilst the other half did not include it in their assessment. These findings became the basis of stage two, which was to examine the influence of colour coded traffic light (CCTL) labelling on respondents’ assessment of credibility. From the findings, the probability of respondents making informed judgements by choosing a high credibility map based on this rating label (CCTL) was three times higher than where only the metadata was presented. The third stage was to propose a conceptual framework to support the implementation of automated credibility labelling for map mashup applications. The framework was proposed on the basis of thorough reviews from the literature. The suggested parameters and approaches are not limited to assess credibility of information in the map mashup context, but could be applied to other Web GIS applications