We propose a novel module for computing all possible passages through an intersection by assigning indexes to entry and exit points extracted from textual narratives and computing relative directions between them. Our method relies on a contiguity condition that ensures every input record is connected and computes relative directions using predefined tables. The resulting passages serve as the basis for constructing reliable sketch maps with topological accuracy. This approach facilitates early error detection in spatial data and supports future extensions to cases where intersections are incomplete by retaining non-contiguous records until additional data become available.

This paper explores an outline of the application of AI in standardizing place names within urban narratives, addressing discrepancies caused by diverse agent terminologies. By leveraging AI chatbots for named entity recognition, coreference resolution, and entity linking, the study proposes an interactive methodology for homogenizing place names across different accounts. This innovative approach aims to enhance the accuracy of information extraction from narratives, demonstrating the potential of AI models over traditional linguistic methods in resolving place name inconsistencies.

Knowledge about the real world is often recorded in plain text, such as posts on social networks, descriptions in various guides, etc. These messages include spatial information that can be extracted using natural language processing methods. The extracted information can then be represented as a planar graph, which can be further transformed into a topological map using additional information describing the area. This paper outlines an algorithm that takes a given planar graph as input and uses a multi-agent system to place individual points in 2D space, creating a topological map respecting all edge directions given in the narratives.

Maps constructed in Euclidean space are commonly used to visually present information about the real world. However, their creation is resource intensive, be it financial, technical, human, or time-consuming, which can limit their timeliness and detail. A simpler form of visualization of data about the real world is represented by sketch maps, which mainly capture the topology and mutual features’ spatial location. By default, they are drawn by hand. This presupposes that the creator has a good knowledge of the depicted territory, can create a cognitive map, and is skilled in transforming it into a graphical form. Sketch maps can be detailed and up-to-date if these prerequisites are met. Our question was whether it is possible to meet these assumptions in another way: acquire knowledge of the territory by processing narratives related to the area of interest, create a suitable computer representation for further processing, and automatically generate the resulting sketch map. This article presents the last step – creating a sketch map based on spatial data acquired from narratives. The results show that even without metric data, it is possible to automatically generate a sketch map visually close to the actual situation.

A significant amount of real-world information is documented in simple text format, such as messages found on social networks. These messages include various types of data, including spatial details, which can be extracted through natural language processing. The extracted data can be represented as a plain topological graph, stored as tuples that describe individual edges. This paper outlines an algorithm that utilizes these tuples to generate a simplified map.

Navigation and an agent’s map representation in a multi-agent system become problematic when agents are situated in complex environments such as the real world. Challenging modifiability of maps, long updating period, resource-demanding data collection makes it difficult for agents to keep pace with rather quickly expanding cities. This study presents the first steps to a possible solution by exploiting natural language processing and symbolic methods of supervised machine learning. An adjusted algorithm processes formalized descriptions of one’s journey to produce a description of the journey. The explication is represented employing Transparent Intensional Logic. A combination of several explications might be used as a representation of spatial data, which may help the agents to navigate. Results of the study showed that it is possible to obtain a topological representation of a map using natural language descriptions. Collecting spatial data from spoken language may accelerate updating and creation of maps, which would result in up-to-date information for the agents obtained at a rather low cost.

The Commission on Geoinformation Infrastructures and Standards of the International Cartographic Association (ICA) is working on defining models of spatial data infrastructures (SDIs). SDI models from the enterprise and information viewpoints of the Reference Model for Open Distributed Processing (RM-ODP) have already been presented. Our model from the computational viewpoint identifies the main computational objects of an SDI and their interfaces, which are modelled using Unified Modelling Language (UML) component diagrams. Presented here is the first comprehensive SDI model from the computational viewpoint, which enhances the understanding of the computational objects and their interactions in an SDI. This viewpoint complements the previous two and together, the three viewpoints contribute towards a more holistic interpretation of an SDI, which is independent of specific SDI legislation, technology and implementations. For the computational viewpoint, we identified six computational objects, SDI Registry, SDI Data, SDI Processing, SDI Application, SDI Portrayal and SDI Management, and their provided and required interfaces. We describe the interactions of the computational objects in stakeholder activities and the roles they play in the different processes of SDI development and use, which we identified as Initiation, Creation, Management, Manipulation, Access, Processing, Evaluation and Liaison. Two tables summarise the SDI services that are provided by computational objects for stakeholder activities and SDI processes.

The Commission on Spatial Data Standards of the International Cartographic Association is working to define formal models and technical characteristics of Spatial Data Infrastructures (SDI). To date, this work has been restricted to the Enterprise and Information Viewpoints from the ISO Reference Model for Open Distributed Processing standard. The Commission has developed models for these two viewpoints. These models describe how the different parts of an SDI fit together in the viewpoints in question. These models should be seen as a contribution towards the overall model of the SDI and its technical characteristics. During the model development process, the roles of the different Actors in an SDI in the Enterprise and Information Viewpoints have also been identified in Use Case diagrams of an SDI. All the models have been developed using the Unified Modeling Language. ✠ This author passed away in September 2007.