The transcription of historical documents written in Latin in XV and XVI centuries has special challenges as it must maintain the characters and special symbols that have distinct meanings to ensure that historical texts retain their original style and significance. This work proposes a pipeline for the transcription of historical documents preserving these special features. We propose to extend an existing text line recognition method with a layout analysis model. We analyze historical text images using a layout analysis model to extract text lines, which are then processed by an OCR model to generate a fully digitized page. We evaluated our approach on multiple datasets and demonstrated that the masked autoencoder effectively processes different types of text, including handwritten, printed, and multi-language. In addition, we demonstrated that our pipeline facilitates the processing of full pages and achieves a CER of 1.14% and a WER of 4.85% on medieval Latin manuscript recognition, preserving also original special characters and orthographic forms present in the historical texts.

Voluntary Geographic Information initiatives are transforming the disaster response landscape. Our research provides insights into how the concept of collective intelligence is accomplished in humanitarian mapping initiatives. The main source originates from the data obtained in 746 mapping projects organised by the Humanitarian OpenStreetMap Team between December 2021 and November 2023, where 38,893 contributors completed 312,289 mapping tasks. These data include detailed attributes of the contributors and the states the tasks go through. The methodology adopts a quantitative approach, including descriptive and inferential statistics, and standard process mining techniques. Our results indicate that, in general terms, in humanitarian mapping, a group of contributors from outside the area of interest perform straightforward mapping tasks with limited collaboration among them. The ‘wisdom’ of advanced contributors is the cornerstone that sustains the system. The discussion section elaborates on (1) how these findings suggest that humanitarian mapping projects effectively meet their short-term mapping objectives but fall short if more sustainable mapping objectives are sought and (2) possible strategies for better harnessing the collective intelligence of these efforts.

A Minimum Bounding Box (MBB) is a rectangle which bounds a geographic feature or dataset. It is commonly used in spatial information systems as a simplified way of describing the spatial extent of a resource. MBBs are typically indexed for searching and discovering resources relevant to a given geographic area of interest. However, this simplification leads to a loss of precision in the description of the extent and can affect the overall precision of the search results. We propose an alternative technique for describing the spatial extent based on the use of DGGS tiles. To measure the precision improvements offered by our method, we designed and implemented an empirical method for evaluating the average precision, and applied it to three different systems: one based on MBB, another on Convex Hull, and ours based on DGGS. The three methods were evaluated with the same test collection obtained from some of the main European geospatial data catalogues compliant with the INSPIRE directive. The results showed that our method outperformed the other two. Where the catalogue average precision of the MBB search scenarios is between 73% and 97%, the DGGS is between 96% and 99%. Additionally, we propose a realistic method of transitioning from the current technologies to the technology we are proposing, considering the current state of the spatial data infrastructures.

Abstract Incunabulaare the texts printed mainly during the second half of 15th century that are a key cultural element in a revolutionary period of the history and evolution of the book and the printing. In these books, the identification of their origin largely affects its academic, cultural, patrimonial, and economical value. This paper proposes a process to automate the identification of the origin of a digitised incunable document using the Proctor/Haebler method, a commonly established procedure in the field. This process has been validated with a selected dataset obtained from the incunabula collection at the digital repository of the University of Zaragoza.

With recent advances in remote sensing, location-based services and other related technologies, the production of geospatial information has exponentially increased in the last decades. Furthermore, to facilitate discovery and efficient access to such information, spatial data infrastructures were promoted and standardized, with a consideration that metadata are essential to describing data and services. Standardization bodies such as the International Organization for Standardization have defined well-known metadata models such as ISO 19115. However, current metadata assets exhibit heterogeneous quality levels because they are created by different producers with different perspectives. To address quality-related concerns, several initiatives attempted to define a common framework and test the suitability of metadata through automatic controls. Nevertheless, these controls are focused on interoperability by testing the format of metadata and a set of controlled elements. In this paper, we propose a methodology of testing the quality of metadata by considering aspects other than interoperability. The proposal adapts ISO 19157 to the metadata case and has been applied to a corpus of the Spanish Spatial Data Infrastructure. The results demonstrate that our quality check helps determine different types of errors for all metadata elements and can be almost completely automated to enhance the significance of metadata.

Geospatial data catalogs enable users to discover and access geographical information. Prevailing solutions are document oriented and fragment the spatial continuum of the geospatial data into independent and disconnected resources described through metadata. Due to this, the complete answer for a query may be scattered across multiple resources, making its discovery and access more difficult. This paper proposes an improved information retrieval process for geospatial data catalogs that aggregates the search results by identifying the implicit spatial/thematic relations between the metadata records of the resources. These aggregations are constructed in such a way that they match better the user query than each resource individually.

Considerable amounts of geographical data are still collected not in form of GIS data but just as natural language texts. This paper proposes an approach for the automatic geocoding of itineraries described in natural language. This approach needs as an input a text annotated with part-of-speech and geo-semantic tags. The proposed method is divided into three main steps. First, we build a complete graph where vertices represent locations, and all vertices are connected to each other by undirected edges. We assign a weight to all the edges of the complete graph using a multi-criteria analysis approach. Then we compute a minimum spanning tree to obtain an undirected acyclic graph connecting all vertices. And finally, we transform this graph into a partially directed acyclic graph in order to identify the sequence of waypoints and build an approximation of a plausible footprint of the itinerary described. Additionally, the rationale of the proposed approach has been verified with a set of experiments on a corpus of hiking descriptions.

Geoparsing and geocoding are two essential middleware services to facilitate final user applications such as location-aware searching or different types of location-based services. The objective of this work is to propose a method for establishing a processing chain to support the geoparsing and geocoding of text documents describing events strongly linked with space and with a frequent use of fine-grain toponyms. The geoparsing part is a Natural Language Processing approach which combines the use of part of speech and syntactico-semantic combined patterns (cascade of transducers). However, the real novelty of this work lies in the geocoding method. The geocoding algorithm is unsupervised and takes profit of clustering techniques to provide a solution for disambiguating the toponyms found in gazetteers, and at the same time estimating the spatial footprint of those other fine-grain toponyms not found in gazetteers. The feasibility of the proposal has been tested with a corpus of hiking descriptions in French, Spanish and Italian.

Jurisdictional domains are legal divisions of the Earth’s surface frequently used in classification and search systems for location-based queries. However, there are few compilations of jurisdictional domains that include their evolution. One of the causes is the complexity of their generation. As an advance in this area, this paper describes a process that facilitates the creation of knowledge bases containing the evolution of jurisdictional domains. As application example, this paper presents the creation of a jurisdictional knowledge base of Spain with its evolution between 1830 and 2011.

Jurisdictional domains are generally accepted political divisions of the earth surface that cover specific territorial and functional scopes over time. They are frequently used in information retrieval (IR) to classify and locate resources by means of their geographical location. However, the changes they suffer over time reduce their applicability in historical collections. In this context, and with the objective of improving the use of jurisdictional domains, this article proposes an ontology schema that combines in a single model the administrative structure, the spatial components, and the temporal evolution of jurisdictional domains. This ontology schema has been used to create the Spanish jurisdictional model. Additionally, as an example of its applicability in the IR context, the Spanish model has been used as part of a location-based query component for the Spanish Official State Gazette.