Challenges of the Anthropocene epoch – supporting multi-focus research

International audienceWork on multiscale issues presents countless challenges that have been long attacked by GIScience researchers. Most results either concentrate on modeling or on data structures/database aspects. Solutions go either towards generalization (and/or virtualization of distinct scales) or towards linking entities of interest across scales. However, researchers seldom take into account the fact that multiscale scenarios are increasingly constructed cooperatively, and require distinct perspectives of the world. The combination of multiscale and multiple perspectives per scale constitutes what we call multifocus research. This paper presents our solution to these issues. It builds upon a specific database version model – the multiversion MVBD – which has already been successfully implemented in several geospatial scenarios, being extended here to support multi-focus research

Gerenciamento de restrições de integridade para dados geoespaciais multi-escala

Orientador: Claudia Maria Bauzer MedeirosDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Trabalhar em questões relativas a dados geoespaciais presentes em múltiplas escalas apresenta inúmeros desafios que têm sido atacados pelos pesquisadores da área de GIS (Sistemas de Informação Geográfica). De fato, um dado problema do mundo real deve frequentemente ser estudado em escalas distintas para ser resolvido. Outro fator a ser considerado é a possibilidade de manter o histórico de mudanças em cada escala. Além disso, uma das principais metas de ambientes multi-escala _e garantir a manipulação de informações sem qualquer contradição entre suas diferentes representações. A noção de escala extrapola inclusive a questão espacial, pois se aplica também, por exemplo, _a escala temporal. Estes problemas serão analisados nesta dissertação, resultando nas seguintes contribuições: (a) proposta do modelo DBV (Database Version) multi-escala para gerenciar de forma transparente dados de múltiplas escalas sob a perspectiva de bancos de dados; (b) especificação de restrições de integridade multi-escala; (c) implementação de uma plataforma que suporte o modelo e as restrições, testados com dados reais multi-escalaAbstract: Work on multi-scale issues concerning geospatial data presents countless challenges that have been long attacked by GIScience (Geographic Information Science) researchers. Indeed, a given real world problem must often be studied at distinct scales in order to be solved. Another factor to be considered is the possibility of maintaining the history of changes at each scale. Moreover, one of the main goals of multi-scale environments is to guarantee the manipulation of information without any contradiction among the different representations. The concept of scale goes beyond issues of space, since it also applies, for instance, to time. These problems will be analyzed in this thesis, resulting in the following contributions: (a) the proposal of the DBV (Database Version) multi-scale model to handle data at multiple scales from a database perspective; (b) the specification of multi-scale integrity constraints; (c) the implementation of a platform to support model and constraints, tested with real multi-scale dataMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

Interoperability of Traffic Infrastructure Planning and Geospatial Information Systems

Building Information Modelling (BIM) as a Model-based design facilitates to investigate multiple solutions in the infrastructure planning process. The most important reason for implementing model-based design is to help designers and to increase communication between different design parties. It decentralizes and coordinates team collaboration and facilitates faster and lossless project data exchange and management across extended teams and external partners in project lifecycle. Infrastructure are fundamental facilities, services, and installations needed for the functioning of a community or society, such as transportation, roads, communication systems, water and power networks, as well as power plants. Geospatial Information Systems (GIS) as the digital representation of the world are systems for maintaining, managing, modelling, analyzing, and visualizing of the world data including infrastructure. High level infrastructure suits mostly facilitate to analyze the infrastructure design based on the international or user defined standards. Called regulation1-based design, this minimizes errors, reduces costly design conflicts, increases time savings and provides consistent project quality, yet mostly in standalone solutions. Tasks of infrastructure usually require both model based and regulation based design packages. Infrastructure tasks deal with cross-domain information. However, the corresponding data is split in several domain models. Besides infrastructure projects demand a lot of decision makings on governmental as well as on private level considering different data models. Therefore lossless flow of project data as well as documents like regulations across project team, stakeholders, governmental and private level is highly important. Yet infrastructure projects have largely been absent from product modelling discourses for a long time. Thus, as will be explained in chapter 2 interoperability is needed in infrastructure processes. Multimodel (MM) is one of the interoperability methods which enable heterogeneous data models from various domains get bundled together into a container keeping their original format. Existing interoperability methods including existing MM solutions can’t satisfactorily fulfill the typical demands of infrastructure information processes like dynamic data resources and a huge amount of inter model relations. Therefore chapter 3 concept of infrastructure information modelling investigates a method for loose and rule based coupling of exchangeable heterogeneous information spaces. This hypothesis is an extension for the existing MM to a rule-based Multimodel named extended Multimodel (eMM) with semantic rules – instead of static links. The semantic rules will be used to describe relations between data elements of various models dynamically in a link-database. Most of the confusion about geospatial data models arises from their diversity. In some of these data models spatial IDs are the basic identities of entities and in some other data models there are no IDs. That is why in the geospatial data, data structure is more important than data models. There are always spatial indexes that enable accessing to the geodata. The most important unification of data models involved in infrastructure projects is the spatiality. Explained in chapter 4 the method of infrastructure information modelling for interoperation in spatial domains generate interlinks through spatial identity of entities. Match finding through spatial links enables any kind of data models sharing spatial property get interlinked. Through such spatial links each entity receives the spatial information from other data models which is related to the target entity due to sharing equivalent spatial index. This information will be the virtual properties for the object. The thesis uses Nearest Neighborhood algorithm for spatial match finding and performs filtering and refining approaches. For the abstraction of the spatial matching results hierarchical filtering techniques are used for refining the virtual properties. These approaches focus on two main application areas which are product model and Level of Detail (LoD). For the eMM suggested in this thesis a rule based interoperability method between arbitrary data models of spatial domain has been developed. The implementation of this method enables transaction of data in spatial domains run loss less. The system architecture and the implementation which has been applied on the case study of this thesis namely infrastructure and geospatial data models are described in chapter 5. Achieving afore mentioned aims results in reducing the whole project lifecycle costs, increasing reliability of the comprehensive fundamental information, and consequently in independent, cost-effective, aesthetically pleasing, and environmentally sensitive infrastructure design.:ABSTRACT 4 KEYWORDS 7 TABLE OF CONTENT 8 LIST OF FIGURES 9 LIST OF TABLES 11 LIST OF ABBREVIATION 12 INTRODUCTION 13 1.1. A GENERAL VIEW 14 1.2. PROBLEM STATEMENT 15 1.3. OBJECTIVES 17 1.4. APPROACH 18 1.5. STRUCTURE OF THESIS 18 INTEROPERABILITY IN INFRASTRUCTURE ENGINEERING 20 2.1. STATE OF INTEROPERABILITY 21 2.1.1. Interoperability of GIS and BIM 23 2.1.2. Interoperability of GIS and Infrastructure 25 2.2. MAIN CHALLENGES AND RELATED WORK 27 2.3. INFRASTRUCTURE MODELING IN GEOSPATIAL CONTEXT 29 2.3.1. LamdXML: Infrastructure Data Standards 32 2.3.2. CityGML: Geospatial Data Standards 33 2.3.3. LandXML and CityGML 36 2.4. INTEROPERABILITY AND MULTIMODEL TECHNOLOGY 39 2.5. LIMITATIONS OF EXISTING APPROACHES 41 INFRASTRUCTURE INFORMATION MODELLING 44 3.1. MULTI MODEL FOR GEOSPATIAL AND INFRASTRUCTURE DATA MODELS 45 3.2. LINKING APPROACH, QUERYING AND FILTERING 48 3.2.1. Virtual Properties via Link Model 49 3.3. MULTI MODEL AS AN INTERDISCIPLINARY METHOD 52 3.4. USING LEVEL OF DETAIL (LOD) FOR FILTERING 53 SPATIAL MODELLING AND PROCESSING 58 4.1. SPATIAL IDENTIFIERS 59 4.1.1. Spatial Indexes 60 4.1.2. Tree-Based Spatial Indexes 61 4.2. NEAREST NEIGHBORHOOD AS A BASIC LINK METHOD 63 4.3. HIERARCHICAL FILTERING 70 4.4. OTHER FUNCTIONAL LINK METHODS 75 4.5. ADVANCES AND LIMITATIONS OF FUNCTIONAL LINK METHODS 76 IMPLEMENTATION OF THE PROPOSED IIM METHOD 77 5.1. IMPLEMENTATION 78 5.2. CASE STUDY 83 CONCLUSION 89 6.1. SUMMERY 90 6.2. DISCUSSION OF RESULTS 92 6.3. FUTURE WORK 93 BIBLIOGRAPHY 94 7.1. BOOKS AND PAPERS 95 7.2. WEBSITES 10

From geospatial data capture to the delivery of GIS-ready information : improved management within a GIS environment

This thesis presents the research undertaken to investigate how geospatial data handling techniques and technology can be potentially used to enhance the existing management of entire survey datasets from their captured stage to a GIS-ready state and the delivery of this to the user. Discovery of the current systems for managing survey data and information in the Survey and Mapping Department Malaysia (JUPEM) has been presented. In addition, the surveying practice and processes carried out have been examined, especially the different type of data and information existed within the raw data capture right through to the production of GIS-ready information. The current GIS technology and techniques for managing geospatial data have been inspected to gain an in-depth understanding of them. Geospatial object as an approach to model reality of the world has been discovered and used to model the raw, processed, the GIS-ready information. To implement the management, a prototype Database Management System (DBMS) has been implemented, and a trial data population and processing steps have been carried out. An enhancement of the managemenot f the datasetsf rom geospatiald ata capturet o the GIS-ready infori-nation has beend emonstratedT. o deliver online the final product, demonstrationo f available methods were illustrated, and then contrasted. A range of datasets around Malaysian context were used in the research. The investigation revealed that raw, processed and GIS-ready information can be successfully modelled as object in an object-relational spatial database. Using inherent GIS tools, survey datasets management and processing steps within the same system are evidently achieved in a prototype implemented DBMS. An improved management showing the capability of 'drill-down search' and 'two-way traceability' to access and search spatial and non-spatial information in the system is effectively illustrated. Demonstration of the vendor specific and open source technology for the GIS-ready information delivery leads to the comparison between them. The thesis concludes by recognising that a management for raw captured data, processed set of data and GIS-ready information, and the delivery of this, within GIS environment is possible. The inherent GIS tools and DBMS have presented a single-view system for geospatial data management providing superior interfaces that are easy to learn and use, and users are able to specify and perform the desired tasks efficiently. Delivery of data has some constraints that need to be considered before embarking into either vendor specific application or open source technology. In JUPEM, time and cost can be reduced by applying and implementing the suggested GIS application for cadastral and topographic surveys right up to the creation of GIS-ready information, as detailed in the thesis. The research also finds that the in-depth understanding and experience, practically and theoretically, of all aspects of current GIS technologies and techniques gained through this research has achieved an overarching inspiration: equalisation of a high level of awareness and ability of staff in handling GIS project development within currently developing countries with those in the developed countries, and within the national survey and mapping department with those of other government departments and commercial GIS contractors.EThOS - Electronic Theses Online ServicePublic Service Department of Malaysia : Department of Survey and Mapping Malaysia : University of Newcastle upon TyneGBUnited Kingdo

Automated web-based analysis and visualization of spatiotemporal data

Most data are associated with a place, and many are also associated with a moment in time, a time interval, or another linked temporal component. Spatiotemporal data (i.e., data with elements of both space and time) can be used to assess movement or change over time in a particular location, an approach that is useful across many disciplines. However, spatiotemporal data structures can be quite complex, and the datasets very large. Although GIS software programs are capable of processing and analyzing spatial information, most contain no (or minimal) features for handling temporal information and have limited capability to deal with large, complex multidimensional spatiotemporal data. A related problem is how to best represent spatiotemporal data to support efficient processing, analysis, and visualization. In the era of "big data," efficient methods for analyzing and visualizing large quantities of spatiotemporal data have become increasingly necessary. Automated processing approaches, when made scalable and generalizable, can result in much greater efficiency in spatiotemporal data analysis. The growing popularity of web services and server-side processing methods can be leveraged to create systems for processing spatiotemporal data on the server, with delivery of output products to the client. In many cases, the client can be a standard web browser, providing a common platform from which users can interact with complex server-side processing systems to produce specific output data and visualizations. The rise of complex JavaScript libraries for creating interactive client-side tools has enabled the development of rich internet applications (RIA) that provide interactive data exploration capabilities and an enhanced user experience within the web browser. Three projects involving time-series tsunami simulation data, potential human response in a tsunami evacuation scenario, and large sets of modeled time-series climate grids were conducted to explore automated web-based analysis, processing, and visualization of spatiotemporal data. Methods were developed for efficient handling of spatiotemporal data on the server side, as well as for interactive animation and visualization tools on the client side. The common web browser, particularly when combined with specialized server side code and client side RIA libraries, was found to be an effective platform for analysis and visualization tools that quickly interact with complex spatiotemporal data. Although specialized methods were developed to for each project, in most cases those methods can be generalized to other disciplines or computational domains where similar problem sets exist

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa

Deep learning for internet of underwater things and ocean data analytics

The Internet of Underwater Things (IoUT) is an emerging technological ecosystem developed for connecting objects in maritime and underwater environments. IoUT technologies are empowered by an extreme number of deployed sensors and actuators. In this thesis, multiple IoUT sensory data are augmented with machine intelligence for forecasting purposes

Assessment of user needs of primary biodiversity data: Analysis, concerns, and challenges

A Content Needs Assessment (CNA) survey has been conducted in order to determine what GBIF-mediated data users may be using, what they would be using if available, and what they need in terms of primary biodiversity data records. The survey was launched in 2009 in six languages, and collected more than 700 individual responses. Analysis of the responses showed some lack of awareness about the availability of accessible primary data, and pointed out some types of data in high demand for linking to distribution and taxonomical data now derived from the GBIF cache. A notable example was linkages to molecular data. Also, the CNA survey uncovered some biases in the design of user needs surveys, by showing demographic and linguistic effects that may have influenced the distribution of responses received in analogous surveys conducted at the global scale

Using The Dbv Model To Maintain Versions Of Multi-scale Geospatial Data

Work on multi-scale issues concerning geospatial data presents countless challenges that have been long attacked by GIScience researchers. Indeed, a given real world problem must often be studied at distinct scales in order to be solved. Most implementation solutions go either towards generalization (and/or virtualization of distinct scales) or towards linking entities of interest across scales. In this context, the possibility of maintaining the history of changes at each scale is another factor to be considered. This paper presents our solution to these issues, which accommodates all previous research on handling multiple scales into a unifying framework. Our solution builds upon a specific database version model - the multiversion MVDB - which has already been successfully implemented in several geospatial scenarios, being extended here to support multi-scale research. The paper also presents our implementation of of a framework based on the model to handle and keep track of multi-scale data evolution. © 2012 Springer-Verlag.7518 LNCS284293Bédard, Y., Bernier, E., Badard, T., Multiple representation spatial databases and the concept of vuel (2007) Encyclopaedia in Geoinformatics, , Idea Group Publishing, HersheyBurghardt, D., Petzold, I., Bobzien, M., Relation modelling within multiple representation databases and generalisation services (2010) The Cartographic Journal, 47 (3), pp. 238-249Cellary, W., Jomier, G., Consistency of versions in object-oriented databases (1990) Proc. of the 16th Int. Conference on Very Large Databases, pp. 432-441. , Morgan KaufmannDeng, X., Wu, H., Li, D., Mrdb approach for geospatial data revision (2008) Proc. of SPIE, , the Int. Society for Optical EngineeringFriis-Christensen, A., Jensen, C., Object-relational management of multiply represented geographic entities Proc. 15th Int. Conference on Scientific and Statistical Database Management SSDBM (2003)Gançarski, S., Jomier, G., A framework for programming multiversion databases (2001) Data Knowl. Eng., 36, pp. 29-53Gao, H., Zhang, H., Hu, D., Tian, R., Guo, D., Multi-scale features of urban planning spatial data (2010) 18th Int. Conference on Geoinformatics, pp. 1-7Van Oosterom, P., Research and development in geo-information generalisation and multiple representation (2009) Computers, Environment and Urban Systems, 33 (5), pp. 303-310Van Oosterom, P., Stoter, J., 5D Data Modelling: Full Integration of 2D/3D Space, Time and Scale Dimensions (2010) LNCS, 6292, pp. 310-324. , Fabrikant, S.I., Reichenbacher, T., van Kreveld, M., Schlieder, C. (eds.) GIScience 2010. Springer, HeidelbergParent, C., Spaccapietra, S., Vangenot, C., Zimányi, E., Multiple representation modeling (2009) Encyclopedia of Database Systems, pp. 1844-1849. , Springer USParent, C., Spaccapietra, S., Zimányi, E., The murmur project: Modeling and querying multi-representation spatio-temporal databases (2006) Information Systems, 31 (8), pp. 733-769Ruas, A., Duchêne, C., Chapter 14 - A prototype generalisation system based on the multi-agent system paradigm (2007) Generalisation of Geographic Information, pp. 269-284. , Elsevier Science B.VSarjakoski, L.T., Chapter 2 - Conceptual models of generalisation and multiple representation (2007) Generalisation of Geographic Information, pp. 11-35. , Elsevier Science B.VSpaccapietra, S., Parent, C., Vangenot, C., GIS Databases: From Multiscale to MultiRepresentation (2000) LNCS (LNAI), 1864, pp. 57-70. , Choueiry, B.Y., Walsh, T. (eds.) SARA 2000. Springer, HeidelbergStoter, J., Visser, T., Van Oosterom, P., Quak, W., Bakker, N., A semantic-rich multi-scale information model for topography (2011) Int. Journal of Geographical Information Science, 25 (5), pp. 739-763Zhou, S., Jones, C.B., A Multirepresentation Spatial Data Model (2003) LNCS, 2750, pp. 394-411. , Hadzilacos, T., Manolopoulos, Y., Roddick, J., Theodoridis, Y. (eds.) SSTD 2003. Springer, Heidelber