Ontology-Driven Geographic Information Systems

Information integration is the combination of different types of information in a framework so that it can be queried, retrieved, and manipulated. Integration of geographic data has gained in importance because of the new possibilities arising from the interconnected world and the increasing availability of geographic information. Many times the need for information is so pressing that it does not matter if some details are lost, as long as integration is achieved. To integrate information across computerized information systems it is necessary first to have explicit formalizations of the mental concepts that people have about the real world. Furthermore, these concepts need to be grouped by communities in order to capture the basic agreements that exist within different communities. The explicit formalization of the mental models within a community is an ontology. This thesis introduces a framework for the integration of geographic information. We use ontologies as the foundation of this framework. By integrating ontologies that are linked to sources of geographic information we allow for the integration of geographic information based primarily on its meaning. Since the integration may occurs across different levels, we also create the basic mechanisms for enabling integration across different levels of detail. The use of an ontology, translated into an active, information-system component, leads Ontology-Driven Geographic Information Systems. The results of this thesis show that a model that incorporates hierarchies and roles has the potential to integrate more information than models that do not incorporate these concepts. We developed a methodology to evaluate the influence of the use of roles and of hierarchical structures for representing ontologies on the potential for information integration. The use of a hierarchical structure increases the potential for information integration. The use of roles also improves the potential for information integration, although to a much lesser extent than did the use of hierarchies. The combined effect of roles and hierarchies had a more positive effect in the potential for information integration than the use of roles alone or hierarchies alone. These three combinations (hierarchies, roles, roles and hierarchies) gave better results than the results using neither roles nor hierarchies

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Scientometric analysis of BIM-based research in construction engineering and management

The purpose of this paper is to summarize the latest research of BIM adoption in construction engineering and management (CEM) and propose research directions for future scholarly work. During the recent decade, building information modeling (BIM) has gained increasing applications and research interest in the construction industry. Although there have been review-based studies that summarized BIM-based research in the overall architecture, engineering and construction (AEC) area, there is limited review that evaluates the current stage of BIM-based research specifically in the CEM sub-area. Design/methodology/approach CEM falls into the scope of AEC. It involves construction-related tasks, activities and processes (e.g. scheduling and cost estimates), issues (e.g. constructability), as well as human factors (e.g. collaboration). This study adopted a holistic literature review approach that incorporates bibliometric search and scientometric analysis. A total of 276 articles related to BIM applied in CEM were selected from Scopus as the literature sample for the scientometric analysis. Findings Some key CEM research areas (e.g. CEM pedagogy, integrated project delivery, lean and off-site construction) were identified and evaluated. Research trends in these areas were identified, and analyses were carried out with regard to how they could be integrated with BIM. For example, BIM, as a data repository for ACE facilities, has substantial potential to be integrated with a variety of other digital technologies, project delivery methods and innovative construction techniques throughout the whole process of CEM. Practical implications As BIM is one of the key technologies and digital platforms to improve the construction productivity and collaboration, it is important for industry practitioners to be updated of the latest movement and progress of the academic research. The industry, academics and governmental authorities should work with joint effort to fill the gap by first recognizing the current needs, limitations and trends of applying BIM in the construction industry. For example, it needs more understanding about how to address technical interoperability issues and how to introduce the integrated design and construction delivery approach for BIM implementation under the UK BIM Level 2/3 framework. This study contributed to the body of knowledge in BIM by proposing a framework leading to research directions including the differences of BIM effects between design-bid-build and other fast-track project delivery methods; the integration of BIM with off-site construction; and BIM pedagogy in CEM. It also addressed the need to investigate the similarities and differences between academia and industry toward perceiving the movement of BIM in construction field work

GeoAI-enhanced Techniques to Support Geographical Knowledge Discovery from Big Geospatial Data

abstract: Big data that contain geo-referenced attributes have significantly reformed the way that I process and analyze geospatial data. Compared with the expected benefits received in the data-rich environment, more data have not always contributed to more accurate analysis. “Big but valueless” has becoming a critical concern to the community of GIScience and data-driven geography. As a highly-utilized function of GeoAI technique, deep learning models designed for processing geospatial data integrate powerful computing hardware and deep neural networks into various dimensions of geography to effectively discover the representation of data. However, limitations of these deep learning models have also been reported when People may have to spend much time on preparing training data for implementing a deep learning model. The objective of this dissertation research is to promote state-of-the-art deep learning models in discovering the representation, value and hidden knowledge of GIS and remote sensing data, through three research approaches. The first methodological framework aims to unify varied shadow into limited number of patterns, with the convolutional neural network (CNNs)-powered shape classification, multifarious shadow shapes with a limited number of representative shadow patterns for efficient shadow-based building height estimation. The second research focus integrates semantic analysis into a framework of various state-of-the-art CNNs to support human-level understanding of map content. The final research approach of this dissertation focuses on normalizing geospatial domain knowledge to promote the transferability of a CNN’s model to land-use/land-cover classification. This research reports a method designed to discover detailed land-use/land-cover types that might be challenging for a state-of-the-art CNN’s model that previously performed well on land-cover classification only.Dissertation/ThesisDoctoral Dissertation Geography 201

Definitions in ontologies

Definitions vary according to context of use and target audience. They must be made relevant for each context to fulfill their cognitive and linguistic goals. This involves adapting their logical structure, type of content, and form to each context of use. We examine from these perspectives the case of definitions in ontologies

Production of spatial representations through collaborative mapping. An experiment

This paper focuses on the theme of the spatial representation of cities and the territory, reflecting on the prospects for innovation in the expressive means that serve the study of the city. The described research concerns project “Mappe di Comunità 3.0” (http://ontomap.dyndns.org/), funded by the Fondazione CRT. The project focuses on the definition of a methodology that implements a synergistic exchange between institutional territorial knowledge and the knowledge of the citizens, achievable thanks to the mediation of communication provided by a semantic representation of territorial knowledge. That type of representation supports the description of data and of its properties in a unified language. Moreover, it enables the sharing of information on the Web by providing an integrated perspective on territorial data

Integration of Legacy Appliances into Home Energy Management Systems

The progressive installation of renewable energy sources requires the coordination of energy consuming devices. At consumer level, this coordination can be done by a home energy management system (HEMS). Interoperability issues need to be solved among smart appliances as well as between smart and non-smart, i.e., legacy devices. We expect current standardization efforts to soon provide technologies to design smart appliances in order to cope with the current interoperability issues. Nevertheless, common electrical devices affect energy consumption significantly and therefore deserve consideration within energy management applications. This paper discusses the integration of smart and legacy devices into a generic system architecture and, subsequently, elaborates the requirements and components which are necessary to realize such an architecture including an application of load detection for the identification of running loads and their integration into existing HEM systems. We assess the feasibility of such an approach with a case study based on a measurement campaign on real households. We show how the information of detected appliances can be extracted in order to create device profiles allowing for their integration and management within a HEMS