MINOR HISTORICAL CENTRES ONTOLOGY ENRICHMENT AND POPULATION: AN HAMLET CASE STUDY

The main topic of this work focuses on the semantic, historical and spatial documentation of Minor Historical Centres (MHC) with a focus on (semi-abandoned alpine) hamlets. The key point is the possibility to standardise spatial information in the domain of MHC and their related cultural, architectural, built and landscape heritage. This work analyses the notions of historical centre and ancient area, which took different meanings and evolved over the centuries. MHC are historical part of cities, villages and hamlets (urban, rural, minor or abandoned) with cultural, social and economic values. Thus, MHC need to be preserved, documented and safeguarded. The spatial and semantic documentation is a fundamental tool for increasing their knowledge. In these places, many actors and stakeholders are involved in different activities, and for this reason, they need to share common knowledge and use a unique language. In this regard, spatial ontology is of relevant interest and usability. Ontologies are conceptual structures that formalise specific knowledge and create a unique and standard thesaurus that ensures semantic interoperability. This paper is part of a PhD research targeted at developing an ontology containing helpful information to manage, share and collect data on MHC due to the lack of an interoperable structure to formalise such knowledge. The main aim is to populate and enrich the already developed ontological structure with data of a mountain semi-abandoned hamlet: Pomieri. The methodological workflow is validated, enriching and populating the ontology, adding classes and instances with information and unstructured data of a real data case study

Expansão de consulta semântica aplicadas a Sistemas de Recuperação de Informação de contexto Geográfico

O objetivo desta pesquisa é desenvolver uma ontologia que pudesse promover melhorias no desempenho de sistemas de recuperação de informação de contexto geográfico. A metodologia de desenvolvimento seguiu os parâmetros do Método 101. Para validação da ontologia propõe-se aplicar a técnica de expansão semântica (manual) das consultas e submetê-las ao sistema Lemur para verificação

ONTOLOGIE GEOGRAFICHE NEL DOMINIO SPAZIALE URBANO E DEL PATRIMONIO COSTRUITO

Il presente lavoro ha lo scopo di presentare un’articolata ricognizione della letteratura passata e attuale, inerente le ontologie informatiche, con particolare attenzione a quelle connesse al dominio spaziale urbano e del patrimonio culturale architettonico costruito. Da un punto di vista generale, il documento offre una descrizione di definizioni, classificazioni e approcci e metodi per la creazione di ontologie nel campo del Web Semantico, dalle prime nozioni emerse negli anni Novanta alla loro evoluzione negli ultimi due decenni. Nel settore del patrimonio costruito, l'interesse, il bisogno di conoscenza e l'uso di ontologie sono cresciuti per rispondere alle necessità di condivisione e scambio di dati spaziali e alla crescente adozione di infrastrutture geografiche. Queste stanno infatti riscontrando problemi di interoperabilità tecnica, geometrica e semantica nell'integrazione di database geografici e urbani multi-scala che richiedono pertanto l'adozione di standard condivisi e linguaggi comuni. ------ This paper aims to report a review in the past literature about computer science ontologies, with a special view on the ones connected to the spatial domain of urban data and built heritage. From a general point of view the paper offers a write up of definitions, classifications and design approaches and methods for ontologies as they have emerged since the nineties and evolved in the last two decades. In the built heritage domain, the interest, the need of knowledge and the use of ontologies have grown to face the wide exchange of digital spatial data and the extensive adoption of spatial data infrastructures, which faced problems related to the interoperability among spatial databases, and specifically the integration of geographical and urban databases involving the adoption of standards

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

Une approche pour supporter l'analyse qualitative des suites d'actions dans un environnement géographique virtuel et dynamique : l'analyse " What-if " comme exemple

Nous proposons une approche basée sur la géosimulation multi-agent et un outil d’aide à la décision pour supporter l’analyse « What-if » durant la planification des suites d’actions (plans) dans un environnement géographique dynamique. Nous présentons les caractéristiques du raisonnement « What-if » en tant 1) que simulation mentale 2) suivant un processus en trois étapes et 3) basé sur du raisonnement causal qualitatif. Nous soulignons les limites de la cognition humaine pour appliquer ce raisonnement dans le cadre de la planification des suites d’actions dans un environnement géographique dynamique et nous identifions les motivations de notre recherche. Ensuite, nous présentons notre approche basée sur la géosimulation multi-agent et nous identifions ses caractéristiques. Nous traitons en particulier trois problématiques majeures. La première problématique concerne la modélisation des phénomènes géographiques dynamiques. Nous soulignons les limites des approches existantes et nous présentons notre modèle basé sur le concept de situation spatio-temporelle que nous représentons en utilisant le formalisme de graphes conceptuels. En particulier, nous présentons comment nous avons défini ce concept en nous basant sur les archétypes cognitifs du linguiste J-P. Desclés. La deuxième problématique concerne la transformation des résultats d’une géosimulation multi-agent en une représentation qualitative exprimée en termes de situations spatio-temporelles. Nous présentons les étapes de traitement de données nécessaires pour effectuer cette transformation. La troisième problématique concerne l’inférence des relations causales entre des situations spatio-temporelles. En nous basant sur divers travaux traitant du raisonnement causal et de ses caractéristiques, nous proposons une solution basée sur des contraintes causales spatio-temporelles et de causalité pour établir des relations de causation entre des situations spatio-temporelles. Finalement, nous présentons MAGS-COA, une preuve de concept que nous avons implémentée pour évaluer l’adéquation de notre approche comme support à la résolution de problèmes réels. Ainsi, les principales contributions de notre travail sont: 1- Une approche basée sur la géosimulation multi-agent pour supporter l’analyse « What-if » des suites d’actions dans des environnements géographiques virtuels. 2- L’application d’un modèle issu de recherches en linguistique à un problème d’intérêt pour la recherche en raisonnement spatial. 3- Un modèle qualitatif basé sur les archétypes cognitifs pour modéliser des situations dynamiques dans un environnement géographique virtuel. 4- MAGS-COA, une plateforme de simulation et d’analyse qualitative des situations spatio-temporelles. 5- Un algorithme pour l’identification des relations causales entre des situations spatio-temporelles.We propose an approach and a tool based on multi-agent geosimulation techniques in order to support courses of action’s (COAs) “What if” analysis in the context of dynamic geographical environments. We present the characteristics of “What if” thinking as a three-step mental simulation process based on qualitative causal reasoning. We stress humans’ cognition limits of such a process in dynamic geographical contexts and we introduce our research motivations. Then we present our multi-agent geosimulation-based approach and we identify its characteristics. We address next three main problems. The first problem concerns modeling of dynamic geographical phenomena. We stress the limits of existing models and we present our model which is based on the concept of spatio-temporal situations. Particularly, we explain how we define our spatio-temporal situations based on the concept of cognitive archetypes proposed by the linguist J-P. Desclés. The second problem consists in transforming the results of multi-agent geosimulations into a qualitative representation expressed in terms of spatio-temporal situations and represented using the conceptual graphs formalism. We present the different steps required for such a transformation. The third problem concerns causal reasoning about spatio-temporal situations. In order to address this problem, we were inspired by works of causal reasoning research community to identify the constraints that must hold to identify causal relationships between spatio-temporal situations. These constraints are 1) knowledge about causality, 2) temporal causal constraints and 3) spatial causal constraints. These constraints are used to infer causal relationships among the results of multi-agent geosimulations. Finally, we present MAGS-COA, a proof on concept that we implemented in order to evaluate the suitability of our approach as a support to real problem solving. The main contributions of this thesis are: 1- An approach based on multi-agent geosimulation to support COA’s “What if” analysis in the context of virtual geographic environments. 2- The application of a model proposed in the linguistic research community to a problem of interest to spatial reasoning research community. 3- A qualitative model based on cognitive archetypes to model spatio-temporal situations. 4- MAGS-COA, a platform of simulation and qualitative analysis of spatio-temporal situations. 5- An algorithm to identify causal relationships between spatio-temporal situations