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Small-scale spatial abilities that involve the mental representation and transformation of two- and three-dimensional images and manipulation of objects at table-top have been studied extensively and are considered predictive of both interest and success in STEM disciplines. However, research investigating the relation of large-scale spatial abilities to STEM disciplines is sparse. The paper describes the design and implementation of a study for assessing individual differences (if any) in spatial abilities in both figural and environmental spaces between STEM experts (with over 10 years of experience) and non-experts (individuals without any studies in STEM fields). Participants' performance in 16 small-, 10 large-scale tasks, and one self-assessment questionnaire at environmental scale was evaluated to assess their corresponding abilities. Results indicate differences between experts and non-experts, which are mostly highlighted for small-scale abilities where experts outperform non-experts. At large scale, some significant differences are identified, which also favor experts. Correlations among the variables tested provide evidence that different abilities are prominent between experts and non-experts. [ABSTRACT FROM AUTHOR]

Successfully performing a task using a web mapping application may not only depend on the application itself and how well it meets users' needs but also on users' spatial skills. Spatial ability is comprised of different spatial skills and high performance in one skill does not entail similar performance in another. Hence, we explored how university students' performance in seven spatial skills (three small- and four large-scale skills) affects their performance in four tasks (such as finding the closest point of interest or finding the shortest path) using Google Maps, considering three groups of participants based on high, medium, and low spatial skills performance. Beyond exploring this relation for each spatial skill separately, we introduce a composite index for performance in spatial skills, considering them as either two separate clusters of small- and large-scale skills or as an amalgam of both. Results indicate that participants with higher small-scale, but not with higher large-scale, spatial skills, when these are separately assessed, perform better on Google Maps than the other two groups, especially the low spatial-skilled group. This also holds when small-scale skills are considered as a cluster and when all skills are considered as a whole. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) is a rapidly advancing technology that enhances users' perception of the real world by overlaying virtual elements. The geospatial community has been gradually focusing on AR because of its ability to create immersive spatial experiences and facilitate spatial learning. However, designing effective AR interfaces poses several challenges, including managing information overload, providing intuitive user interaction, and optimizing system performance. The management of the Level of Detail (LoD) is a crucial part of an AR-enhanced cartographic representations as it can greatly impact the quantity, accuracy, and usefulness of the information being conveyed and enhance the readability and usability of an application. In this paper, we present a systematic review of published research on the management of LoD for AR cartographic representations based on various dimensions that focus on the types of data that are visualized, the techniques used, and the user actions that trigger LoD change. A corpus of fifteen scientific papers involving different LoD management techniques within AR environments have been analyzed. The limited number of papers implies that this kind of applications is in its infancy. The review provides a synthesis of existing knowledge and identifies challenges for future research in this exciting and dynamic field. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the idea of documenting operational chains for land degradation assessment using ontologies. We believe that this process will help end users better understand the application domain characteristics and evaluate the results of the assessment process. Since the application domain is wide, various operational chains for land degradation assessment and their associated documentation exist, according to different options. This parameterization process causes the development of different ontologies, which nonetheless are, to a certain extent, linked because of the common software components of the corresponding operational chains. We therefore propose a hierarchical structure of these ontologies; so that several requirements such as understanding of expert knowledge interconnections and of application domain variety, documentation and assimilation of new expert knowledge, and reusability of software components become feasible. [ABSTRACT FROM AUTHOR]

This paper presents ongoing research in the field of extensional mappings between ontologies. Hitherto, the task of generating mappings between ontologies has focused on the intensional level of ontologies. The term intensional level herein, refers to the set of concepts that are included in an ontology. However, an ontology that has been created for a specific task or application needs to be populated with instances. These comprise the extensional level of an ontology. This particular level is generally neglected during the ontologies’ integration procedure. Thus, although methodologies of geographic ontologies integration, ranging from alignment to true integration, have, in the course of years, presented a solid ground for information exchange, little has been done in exploring the relationships between the data. In this context, this research strives to set a framework for extensional mappings between ontologies using Information Flow Theory by presenting a case study of interoperability between the thematic content of maps. [ABSTRACT FROM AUTHOR]

Definitions of categories in existent geospatial ontologies are an invaluable source of information because they provide us with essential knowledge about concepts and their properties. A closer examination reveals that definitions also contain supplementary linguistic items, which are mainly qualitative expressions, such as quantifiers. This inclusion of modifiers in definitions affects the way values are assigned to the categories’ properties (semantic properties and relations). This paper introduces a methodology for: (1) representing the essence of qualitative information to clarify the identity relations among categories; and (2) assessing their semantic similarity in order to disambiguate the taxonomic structure of existent geospatial ontologies. [ABSTRACT FROM AUTHOR]

An important issue in geographic ontological research is the ability to design new ontologies. In this context, we first explore the desiderata of domain ontologies in terms of their constituting elements: i.e., the lexicon, concepts, relations, and axioms. Furthermore, we touch upon several characteristics of geographic concepts, which have puzzled geographic information scientists, and present critical topics of geographic ontological research. Based on the previous aspects of the problem, and guided by prior work of analyzing existent geographic ontologies, we have identified their qualities and deficiencies with regard to completeness and adequacy. This “meta-ontological” approach has guided us in presenting herein, a framework for generating robust geographic ontologies, which will comply with the semantics of the concepts of the specific domain. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) is a technology that has been used extensively in the field of cartography, with one particular application being that of navigation. However even now, AR in navigation is still at an active exploratory stage with multiple different approaches regarding the techniques, methodologies, and development processes. In this work, we present a systematic review of application development in AR navigation research, aiming to fill the gap in the literature by identifying trends in aspects such as hardware, software, and methodologies in AR navigation. We review 107 publications from the past 25 years that present AR navigation software for real-world environments, and analyze their main characteristics regarding intended environments and users, hardware, development platforms, and AR methodologies. We note a rise in AR navigation research interest from 2010 onward, driven in large part by smartphone and mobile device ubiquity, supported further by significant advances and streamlined processes in AR application development. Furthermore, we highlight a rise in the use of increasingly more complex AR methodologies in recent years, signaling that the field is steadily evolving and maturing. At the same time, we also identify significant inconsistencies and omissions regarding the reporting of technical details, with nearly half of reviewed works not reporting one or more of the aspects of interest. After identifying the level of maturity and complexity in the field AR navigation, we provide a list of recommendations and future directions for researchers aiming to develop AR navigation applications. [ABSTRACT FROM AUTHOR]

Abstract: Numerous attempts have been made to generate semantic “mappings” between different ontologies, or create aligned/integrated ones. An essential step towards their success is the ability to compare the categories involved. This paper introduces a systematic methodology for comparing categories met in geographic ontologies. The methodology explores/extracts semantic information provided by categories’ definitions. The first step towards this goal is the recognition of syntactic and lexical patterns in definitions, which help to identify (a) semantic properties such as purpose, location, cover, and (b) semantic relations such as hypernym, part of, has-parts, etc. At the second step, a similarity measure among categories is applied, in order to explore how (the) extracted properties and relations interrelate. This framework enables us to (a) better understand the impact of context in cross-ontology “mappings”, (b) evaluate the “quality” of definitions as to whether they respect mere ontological aspects (such as unambiguous taxonomies), and (c) deal more effectively with the problem of semantic translation among geographic ontologies. [Copyright &y& Elsevier]