Geospatial Data Management Research: Progress and Future Directions

Without geospatial data management, today´s challenges in big data applications such as earth observation, geographic information system/building information modeling (GIS/BIM) integration, and 3D/4D city planning cannot be solved. Furthermore, geospatial data management plays a connecting role between data acquisition, data modelling, data visualization, and data analysis. It enables the continuous availability of geospatial data and the replicability of geospatial data analysis. In the first part of this article, five milestones of geospatial data management research are presented that were achieved during the last decade. The first one reflects advancements in BIM/GIS integration at data, process, and application levels. The second milestone presents theoretical progress by introducing topology as a key concept of geospatial data management. In the third milestone, 3D/4D geospatial data management is described as a key concept for city modelling, including subsurface models. Progress in modelling and visualization of massive geospatial features on web platforms is the fourth milestone which includes discrete global grid systems as an alternative geospatial reference framework. The intensive use of geosensor data sources is the fifth milestone which opens the way to parallel data storage platforms supporting data analysis on geosensors. In the second part of this article, five future directions of geospatial data management research are presented that have the potential to become key research fields of geospatial data management in the next decade. Geo-data science will have the task to extract knowledge from unstructured and structured geospatial data and to bridge the gap between modern information technology concepts and the geo-related sciences. Topology is presented as a powerful and general concept to analyze GIS and BIM data structures and spatial relations that will be of great importance in emerging applications such as smart cities and digital twins. Data-streaming libraries and “in-situ” geo-computing on objects executed directly on the sensors will revolutionize geo-information science and bridge geo-computing with geospatial data management. Advanced geospatial data visualization on web platforms will enable the representation of dynamically changing geospatial features or moving objects’ trajectories. Finally, geospatial data management will support big geospatial data analysis, and graph databases are expected to experience a revival on top of parallel and distributed data stores supporting big geospatial data analysis

On systematic approaches for interpreted information transfer of inspection data from bridge models to structural analysis

In conjunction with the improved methods of monitoring damage and degradation processes, the interest in reliability assessment of reinforced concrete bridges is increasing in recent years. Automated imagebased inspections of the structural surface provide valuable data to extract quantitative information about deteriorations, such as crack patterns. However, the knowledge gain results from processing this information in a structural context, i.e. relating the damage artifacts to building components. This way, transformation to structural analysis is enabled. This approach sets two further requirements: availability of structural bridge information and a standardized storage for interoperability with subsequent analysis tools. Since the involved large datasets are only efficiently processed in an automated manner, the implementation of the complete workflow from damage and building data to structural analysis is targeted in this work. First, domain concepts are derived from the back-end tasks: structural analysis, damage modeling, and life-cycle assessment. The common interoperability format, the Industry Foundation Class (IFC), and processes in these domains are further assessed. The need for usercontrolled interpretation steps is identified and the developed prototype thus allows interaction at subsequent model stages. The latter has the advantage that interpretation steps can be individually separated into either a structural analysis or a damage information model or a combination of both. This approach to damage information processing from the perspective of structural analysis is then validated in different case studies

Automatic Reconstruction of Parametric, Volumetric Building Models from 3D Point Clouds

Planning, construction, modification, and analysis of buildings requires means of representing a building's physical structure and related semantics in a meaningful way. With the rise of novel technologies and increasing requirements in the architecture, engineering and construction (AEC) domain, two general concepts for representing buildings have gained particular attention in recent years. First, the concept of Building Information Modeling (BIM) is increasingly used as a modern means for representing and managing a building's as-planned state digitally, including not only a geometric model but also various additional semantic properties. Second, point cloud measurements are now widely used for capturing a building's as-built condition by means of laser scanning techniques. A particular challenge and topic of current research are methods for combining the strengths of both point cloud measurements and Building Information Modeling concepts to quickly obtain accurate building models from measured data. In this thesis, we present our recent approaches to tackle the intermeshed challenges of automated indoor point cloud interpretation using targeted segmentation methods, and the automatic reconstruction of high-level, parametric and volumetric building models as the basis for further usage in BIM scenarios. In contrast to most reconstruction methods available at the time, we fundamentally base our approaches on BIM principles and standards, and overcome critical limitations of previous approaches in order to reconstruct globally plausible, volumetric, and parametric models.Automatische Rekonstruktion von parametrischen, volumetrischen Gebäudemodellen aus 3D Punktwolken Für die Planung, Konstruktion, Modifikation und Analyse von Gebäuden werden Möglichkeiten zur sinnvollen Repräsentation der physischen Gebäudestruktur sowie dazugehöriger Semantik benötigt. Mit dem Aufkommen neuer Technologien und steigenden Anforderungen im Bereich von Architecture, Engineering and Construction (AEC) haben zwei Konzepte für die Repräsentation von Gebäuden in den letzten Jahren besondere Aufmerksamkeit erlangt. Erstens wird das Konzept des Building Information Modeling (BIM) zunehmend als ein modernes Mittel zur digitalen Abbildung und Verwaltung "As-Planned"-Zustands von Gebäuden verwendet, welches nicht nur ein geometrisches Modell sondern auch verschiedene zusätzliche semantische Eigenschaften beinhaltet. Zweitens werden Punktwolkenmessungen inzwischen häufig zur Aufnahme des "As-Built"-Zustands mittels Laser-Scan-Techniken eingesetzt. Eine besondere Herausforderung und Thema aktueller Forschung ist die Entwicklung von Methoden zur Vereinigung der Stärken von Punktwolken und Konzepten des Building Information Modeling um schnell akkurate Gebäudemodelle aus den gemessenen Daten zu erzeugen. In dieser Dissertation präsentieren wir unsere aktuellen Ansätze um die miteinander verwobenen Herausforderungen anzugehen, Punktwolken mithilfe geeigneter Segmentierungsmethoden automatisiert zu interpretieren, sowie hochwertige, parametrische und volumetrische Gebäudemodelle als Basis für die Verwendung im BIM-Umfeld zu rekonstruieren. Im Gegensatz zu den meisten derzeit verfügbaren Rekonstruktionsverfahren basieren unsere Ansätze grundlegend auf Prinzipien und Standards aus dem BIM-Umfeld und überwinden kritische Einschränkungen bisheriger Ansätze um vollständig plausible, volumetrische und parametrische Modelle zu erzeugen.</p

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

Three-dimensional information retrieval (3DIR): A graph theoretic formulation for exploiting 3D geometry and model topology in information retrieval

The 3DIR project investigated the use of 3D visualization to formulate queries, compute the relevance of information items, and visualize search results. Workshops identified the user needs. Based on these, a graph theoretic formulation was created to inform the emerging system architecture. A prototype was developed. This enabled relationships between 3D objects to be used to widen a search. An evaluation of the prototype demonstrated that a tight coupling between text-based retrieval and 3D models could enhance information retrieval but add an extra layer of complexity

An ontology-aided, natural language-based approach for multi-constraint BIM model querying

Being able to efficiently retrieve the required building information is critical for construction project stakeholders to carry out their engineering and management activities. Natural language interface (NLI) systems are emerging as a time and cost-effective way to query Building Information Models (BIMs). However, the existing methods cannot logically combine different constraints to perform fine-grained queries, dampening the usability of natural language (NL)-based BIM queries. This paper presents a novel ontology-aided semantic parser to automatically map natural language queries (NLQs) that contain different attribute and relational constraints into computer-readable codes for querying complex BIM models. First, a modular ontology was developed to represent NL expressions of Industry Foundation Classes (IFC) concepts and relationships, and was then populated with entities from target BIM models to assimilate project-specific information. Hereafter, the ontology-aided semantic parser progressively extracts concepts, relationships, and value restrictions from NLQs to fully identify constraint conditions, resulting in standard SPARQL queries with reasoning rules to successfully retrieve IFC-based BIM models. The approach was evaluated based on 225 NLQs collected from BIM users, with a 91% accuracy rate. Finally, a case study about the design-checking of a real-world residential building demonstrates the practical value of the proposed approach in the construction industry

A review of approaches to solving the problem of BIM search: towards intelligence-assisted design

Due to the growing adoption of BIM and the rising popularity of cloud computing, BIM models are increasingly stored in central cloud repositories or Common Data Environments. Effective management and exploitation of these models creates the requirement for BIM retrieval systems. Thus far, the BIM industry has utilized general-purpose, text-based search techniques that operate on BIM metadata. This paper highlights the need for a domain-specific BIM search engine and reviews various approaches to address the problem of BIM search. Three main approaches were identified as context-, geometry-, and content-based BIM retrieval. For a comprehensive BIM retrieval system, all three approaches need to be utilized. Literature about geometry- and content-based retrieval was scarce, and about context-based retrieval was almost non-existent. Context-based retrieval is a special approach that is relevant here due to the project-based and goal-oriented nature of architectural design and needs support from stakeholders in the AECO industry

Three-Dimensional Information Retrieval (3DIR): exploiting 3D geometry and model topology in information retrieval from BIM environments

In building modelling environments, more and more information is being crammed into 2D/3D building and product models. This is particularly true given the rise of Building Information Modelling (BIM, Eastman et al., 2011). The Three-Dimensional Information Retrieval (3DIR) project investigates information retrieval from these environments, where information or documents are linked to a 3D building model. In these situations, the 3D visualization or 3D geometry of the building can be exploited when formulating information retrieval queries, computing the relevance of information items to the query, or visualizing search results. Managing such building information repositories in this way would take advantage of human strengths in vision, spatial cognition and visual memory (Lansdale and Edmonds, 1992; Robertson et al., 1998). Information retrieval is associated with documents, and a critic might argue that documents are relics from the pre-BIM age that are no longer relevant in the era of BIM. However, the challenge of information retrieval is pertinent whether we are dealing with documents which are coarse grains of information or building object parameters/attributes as finer grains of information. Demian and Fruchter (2005) demonstrated that traditional retrieval computations can be applied with good results to 3D building models where textual or symbolic data are treated as very short documents. In this sense, it is almost a question of semantics whether the information being retrieved comes from object properties embedded in the BIM, or from external documents linked to the BIM. The challenge remains of retrieving non-geometric or textual information. This paper describes the findings of the 3DIR project whose aim was to improve information retrieval when retrieving information or documents linked to a 3D artefact, or non-geometric information embedded in the model of the artefact. The central objective was to develop an information retrieval toolset for documents/information linked to 3D building models which exploits 3D geometry and model visualisation. Such a toolset is essentially a search engine for retrieving information with a BIM platform. As a further objective, the toolset should leverage topological relationships in the 3D model to enhance information retrieval