OPENBIM VISUALIZER A VISUALIZATION TOOL FOR VIEWING THE IFC DATA MODEL

OPENBIM VISUALIZER A VISUALIZATION TOOL FOR VIEWING THE IFC DATA MODEL Yang-Hsiu Tong 1, Chih-Hsiung Chang 2, Yi-Wei Chen 3 and I-Chen Wu 4 1) Graduate Student, Department of Civil Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan. Email: tongyanghsiu@gmail.com 2) Undergraduate Student, Department of Civil Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan. Email: justin660302@gmail.com 3) Undergraduate Student, Department of Civil Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan. Email: a27913016@hotmail.com 4) Associate Professor, Department of Civil Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan. Email: kwu@kuas.edu.tw Abstract: The Industry Foundation Classes (IFC) data model is an open standard design to support the goals of Open BIM for data sharing and information integration in building information modeling (BIM). It is an object-oriented data model based on class definitions representing the items (elements, processes, shapes, and so on) that are used by software applications during a construction or facility management project. However, large volumes of IFC data are difficult to comprehend when displayed in text-views or tree-views. The project participants cannot know the project status completely if they do not have a good and user-friendly visualization tool to display the related project information. Therefore, this research develops OpenBIM Visualizer for facilitating IFC data model visualization. The design and implementation of these useful graphs employs HTML5 and JavaScript. HTML5 is a unified and multi-platform content enabler that is capable of realizing mobile applications and websites. JavaScript can support the creation of interactive elements and effects for expanding the manipulation ability of a graphical user interface (GUI). These graphs can provide multiple visualization styles for assisting project participants to obtain the required information from an IFC data model, as well as to consider a wide variety of information when controlling the project and making project decisions. Keywords: Building Information Modeling (BIM), Industry Foundation Classes (IFC), Data Visualization, Infographic. 1. INTRODUCTION Building information modeling (BIM) has been widely used in the construction industry owing to its benefits and capabilities for information integration, visualization, and parametric design. However, due to the variety of participants in engineering projects, the differences between data definition, data format, and data storage increase the difficulty of integrating data from diverse sources. Over the last decade, the construction industry has invested considerable effort into integrating project information. Therefore, buildingsmart proposed the concept of Open BIM and developed Industry Foundation Classes (IFC) to solve this problem. The IFC standard has already been accepted as the information standard for buildings (Fan, 2007). IFC is an open information model used to exchange and share information for buildings. IFC can integrate data that were generated from different BIM systems. The interoperability of the IFC data model has been studied in many research projects. Researchers such as Eastman et al. (2010) have said that the IFC standard building model schema is necessary for achieving full interoperability between BIM tools. Zhang et al. (2011) proposed a semantic web services framework utilizing IFC-based industry ontology to address the interoperability problem. Nevertheless, several papers have reported problems in data exchange using IFC. Some of the issues identified and discussed include the classification of objects, instances, geometry, relationships, and rules, which are supported in the IFC schema, and the complexities of exchanging such information accurately between applications (Venugopal et al., 2012). Most BIM systems can only display the 3D geometry of an IFC data model and suffer from incomplete data or data loss. Meanwhile, a general IFC data viewer can only view IFC data via a tree-view or a text-view. From the above-mentioned research, the shortcomings of IFC data deficiency in BIM systems, especially in the loss of non-graphical attributes, is clear. Although IFC files have rich data about construction projects, the data is not used efficiently, causing an Information Poor situation (Russell et al., 2011). Although IFC data models can fulfill the goals of information integration and interoperability, they still fall short of providing a good visualization tool for viewing the integrated data. Visualization is a major concern in a wide variety of applications, such as information visualization, interaction techniques and architectures, modeling techniques, multi-resolution methods, visualization algorithms and techniques, and volume visualization (Post, 2002). Some studies have focused on data visualization. For example, Saraiya et al. (2005) have discussed the visualization of graphs with associated time series data. Herman et al. (2000) investigated the hierarchical structure of the data type and demonstrated various graphs for hierarchical structures of data. Blanch & Lecolinet (2007) proposed browsing zoomable treemaps for

multi-scale dimensional data. A good visual representation of data can assist a people in efficiently acquiring required and relevant information. Vision is the most abundant of the human senses and d perception of the most influential sources (Yang, 2002). Data visualization allows users to quickly receive r large amounts of data. In recent years, there has been a renewal of interest in the application of the IFCC data model. Fu et al. (2006) presented a multi-dimensional data view using an IFC data model. Zhiliang Z et al.. (2011) applied an IFC data model to estimate the cost of constructions. The purpose of this paper is i to report onn an investigation of an application of large volumes of data in data visualization, i.e.,, data visualization appliedd to an IFC data model. This in-house software is designed for use in particular projects or firmss and can provide simple graphs of engineering e information for project management. For these reasons, this research develops the OpenBIM Visualizer, which can provide various useful graphs without requiring a 3D model to facilitate IFC data model visualization and to convey significant s engineering information. The use off visualizationn to present engineering information is ann effective and efficient method for the distribution of information and communication with project participants p during project meetings. 2. RELATED WORK 2.1 Industry Foundation Classes (IFC) Information Modeling is nowadays a widely accepted methodology for the development of f exchange protocol specificationss in engineering fields, suchh as architecture and construction. BuildingSMART,, formerly the International Association for Interoperability, published the platform-neutral dataa model called Industry Foundation Classes (IFC) in order to provide a common data representation and thereby enable easy exchange of model data. The schema of IFC has a complicated structure with Defined Types, Enumerations, Select Types, Entities, and Attributes. An example class diagram and its corresponding file f format are shown in Figure 1 to demonstrate the structure of the IFC Schedule&Task objects that are relatedd to generate the visualization graphs discussedd in this paper. For example, an IfcWorkSchedule includes a set of o elements (created through relating schedule time controls to tasks) with references too the resources used for the tasks included in the work schedule. Additionally, through the IfcWorkControl abstract supertype, the actors creating the schedule can bee specified and schedule time information such as the start t time, finish time, and total float of the schedule can also be specified. Figure 1. IFC example and data structure. 2.2 Visualization in Construction During the life cycle of a construction project, large volumes off data and information are generally created during the delivery processes of construction products. There iss always a need to visualize these engineering data and information for communication with related parties involved in the project. Much research has focused on visualization in construction. Wu and Hsieh (2008) developed a visual project management information system for facilitating project management. Kuo et al. (2011) proposed a framework that enables engineers to explore and interact with information visually. It is clear that t visualization has become more importantt for obtaining and conveying information in an engineering project. Recently, infographics have become widely used. Infographics are graphic visual representations of information, data, or knowledge intended to present complex information quickly and clearly (Smiciklas, 2012). Data visualizations are often used in infographics. Visualization categories may be divided into five f types: time-series data, statistical distributions, maps, hierarchies, and networking (Heer( et al., 2010). Different types of

engineering data will belong to the different visualization categories and will be represented in different charts. As shown in Table 1, there are many graphs that can be used to represent the same set of data. Therefore, it is crucial to identify the appropriate visualization for the data set and infographicic by taking graphical features, such as position, size, shape, and colorr into consideration. Table 1. The graphss for different data characteristics. Graph Statistical Distributions Characteristics Related work A line graph is used to display the relationship between (Shneiderman, 1996) two variables,, with a separate line for each category of o the (Ware, 2012) S-Curve independent variable. Thee horizontal axis indicatess the categories of the dependent variable. Line graphs aree best used when the independent variable has very few categories. Bar charts aree used to compare data using rectangularr bars (Shneiderman, 1996) to represent amounts a within a data set. Because the bars (Ware, 2012) are sized relative to the amounts they represent, these t (Palilonis, 2006) Bar Chart types of charts make comparisons between different variables very easy to see. Furthermore, they can potentially show trends in data by showing how one variable is affected as the other rises or falls. Pie charts are used to represent different parts of a whole. (Shneiderman, 1996) Data displayed in pie chartss must always be represented in (Ware, 2012) percentages, and a because the circle metaphor is associated (Palilonis, 2006) Pie Chart with a complete amount, 100 percent, the sections of a pie chart should always a equatee to this sum. In this way, it is possible to see how something is divided among different groups representing a whole. Time-Series Data In a Gantt chart, scheduled activities are represented as (Shneiderman, 1996) bars on a timeline and constraints are represented as lines (Ware, 2012) Gantt between the bars. (Russel et al., 2009) (Songer et al., 2004) (Kuo et al., 2011) Hierarchies Hierarchies orr tree structures are collections of items with (Shneiderman, 1996) each item having a link to one parent item (except the (Russel et al., 2009) Tree root). Items and a the links between parent and childd can have multiplee attributes. Basic tasks can be applied to items and links, and tasks related to structural properties become interesting. Networking A network is useful for items linked to an arbitrary (Shneiderman, 1996) number of other items. It is convenient to consider them (Ware, 2012) Network all as one data type. In addition to the basic tasks applied (Russel et al., 2009) to items and links, network users often want to know k (Songer et al., 2004) about the shortest or least costly paths connecting two items or traversing the entire network. 3. SYSTEM DESIGN AND IMPLEMENTATION As shown in Figure 2, thee system design can be divided into four f processes: data collection, data analysis, data processing, and data visualization; these are each described below w (1) Data Collection: Engineering data will be generated from different engineering systems, such as schedule data from Microsoft (MS) Project, cost data from MS Excel, 3D models from BIM software, and so on. This process will collect these dataa for integration. (2) Data Analysis: This system willl parse and analyze the engineering dataa that were collected from the first process, such as ifc, xml,, xls, and so on. (3) Data Processing: P This process will convert all of the data format to the IFC file format using the IFCsvr..300 library, and a then the system will retrieve the significant data to convert to a JSON file format via the Json.NET library for visualization. JSON (JavaScript

Object Notation) is a lightweight data-interchan nge format. It is easy for humans h to read and write. (4) Data Visualization: This system will generate useful and practical graphs via a D3.js D library. The implementation of the OpenBIM Visualizer is carried out in the MS ASP..NET environment. It cann provide information manipulation services for users located anywhere and at any time, efficientlyy and effectively. Networking BIM System.OleDb Network Project Data Schedule Data Document Cost Data 3D Model XLS XML IFC XLSconverter XMLconverter System.XML IFCsvr.R300 IFC D3.js OpenBIM Visualizer IFC2JSON Statistical Distributions Pie Chart Bar Chart S-Curve Hierarchies Tree Time-Series Data Gantt Figuree 2. System design of the OpenBIM Visualizer. 4. DEMONSTRATION A row house project in Kaohsiung City,, Taiwan, was used as an example e to test and demonstrate the functionality of the OpenBIM Visualizer. This paper focused on data integration and visualization for the cost and schedule of the construction project. For schedule data, a user can import an MS project file (xml)( into OpenBIM Visualizer directly, and the system will convert the xml file to ann ifc file for OpenBIM Visualizer for integration and visualization. As shown s in Figure 3, OpenBIM Visualizer will generate a Gantt chart for presenting schedule data. The Planned Schedule will appear in a deep blue color and the Actual Schedule in light blue. If a task is happening or completed earlierr than the planned time, then it will be shown as a green line. Otherwise, a task that is happening or completedd later than the planned time will be shown as a red line. The system will also show schedule data in detail via a table view and present the relationship between tasks via a network chart, as shown in Figure 4 and Figure 5. Figure 3. Gantt chart for presenting schedule data. Figure 4. Table view for schedules in detail. Figure 5. Network chart for presenting relationships between tasks.

Normally, a planner employs Excel to analyze and generate cost reports. Therefore, this research allows a planner import an xls file into OpenBIM Visualizer directly. As with schedule data processing, the xls file will be converted to an ifc file for dataa integration and visualization. As shown in Figure 6, this research uses an S-curve graph to describe the growth of cost over time. It is used to describe, and sometimes predict, the performance of a construction project over a period of time. The dashed line indicates the planned cost and the solid blue line indicates actual cost. With time, the dashed line and the solid line willl cross and generate an intersection zone. The magenta zone denotes a cost as being more than the amount allotted or budgeted. The green zone shows cost within the budget. As shown in Figure 7, OpenBIM Visualizer presented each cost itemm in detail via a bar chart, because a bar chart can be used for more complex comparisons of data via grouped bar charts and stacked bar charts. This novel visualization style for cost data efficientlyy displays comparisons between each cost item. These bars are color-coded to represent a particularr item. For example, a light blue bar represents the total cost of the main cost item and different colored bars represent breakdown cost items, such as Material, Labor, Equipment, and Misc. Figure 6. The S-curve graph for cost data. Figure 7. Bar chart forr presenting detailed cost breakdown.

5. CONCLUSIONS The Industry Foundation Classes (IFC) data model can integrate various types of engineering information from different project participants. However, common software or applications that are developed in-house can only show 3D models and attributes, and are not sufficient to convey project information for communication with others. Therefore, this research developed the OpenBIM Visualizer, which is a visualization tool for viewing the IFC data model. This tool can parse the IFC data model and visualize two-dimensional (2D) BIM information via different graphs such as Gantt charts, pie charts, bar charts, networks, S-curve graphs, and so on. Furthermore, it can view information and graphs over the Internet without the limitations of time or distance. This tool can facilitate communication and distribution of information between related participants, such as construction companies, building owners, and architectural companies in order to manage projects effectively and efficiently. ACKNOWLEDGMENTS The research presented in this paper was carried out within the Intelligent Monitoring and Green Facility Information Modeling (IM Green FIM) project, which was funded by Ministry of Economic Affairs, Taiwan. REFERENCES Blanch, R. and Lecolinet, É. (2007). Browsing Zoomable Treemaps: Structure-Aware Multi-Scale Navigation Techniques, Visualization and Computer Graphics, 13(6), 1248-1253. Eastman, C. M., Jeong, Y.-S., Sacks, R. and Kaner, I. (2010). Exchange Model and Exchange Object Concepts for Implementation of National BIM Standards. Journal of Computing in Civil Engineering, 24(1), 25-34. Fan, C.Y. (2007). Set Up and Retrieve Structural Information Based on IFC Model, National Chiao Tung University, Taiwan. Fu, C., Aouad, G., Lee, A. and Marshall-Ponting, A. (2006). IFC Model Viewer to Support nd Model Application, Automation in Construction, 15(2), 178-185. Herman, I., Melançon, G. and Marshall, M. S. (2000). Graph Visualization and Navigation in Information Visualization: A Survey, Visualization and Computer Graphics, 6(1), 24-43. Heer, J., Bostock, M., and Ogievetsky, V. (2010). A Tour through the Visualization Zoo. Communications of the ACM, 53(6), 59-67. Kuo, C. H., Tsai, M. H. and Kang, S. C., (2011). A framework of information visualization for multi-system construction, Automation in Construction, 20(3), 247-262. Palilonis, J.G. (2006). A Practical Guide to Graphics Reporting: Information Graphics for Print, Web & Broadcast. Taylor & Francis. Post, F.H. (2002). Data Visualization : the state of the art. Baker & Taylor. Russell, A.D., Chiu, C.Y. and Korde, T., (2009). Visual representation of construction management data, Automation in Construction, 18(8), 1045-1062. Saraiya, P., Lee, P. and North, C. (2005).Visualization of Graphs with Associated Timeseries Data, Information Visualization(Info Vis), Minnesota, USA, pp225-232. Shneiderman, B. (1996). The Eyes Have It : A Task by Data Type Taxonomy for Information Visualizations, Visual Languages, Proceedings of the 1996 IEEE Symposium on Visual Languages, Boulder, USA, pp.336-343. Smiciklas, M. (2012). Power of Infographics, The: Using Pictures to Communicate and Connect With Your Audiences. QUE. Songer, A., Hays, B. and North, C. (2004). Multi-dimensional Vsualization of Project Control Data, Construction Innovation. Information, Process, Management, 4(3), 173-190. Venugopal, M., Eastman, C. M., Sacks, R. and Teizer, J. (2012). Semantics of Model Views for Information Exchanges Using the Industry Foundation Class Schema. Advanced Engineering Informatics, 26(2), 411-428. Ware, C. (2012). Information Visualization Perception for Design (3rd ed.). Morgan Kaufmann. Wu, I. C. and Hsieh, S. S. (2008). VisPMIS:A Visual Project Management Information System. Proceedings of the 11th East Asia-Pacific Conference on Structural Engineering and Construction, November 19-21th, Taipei, Taiwan. Yang, C.Z. (2002). Development and Challenges of Visual Representation of Information, Proceedings of the Conference on Information Science and Technology in 21st Century, Taipei, Taiwan, pp.291-305. Zhang, L. and Issa, R. R. A.(2011). IFC-Based Construction Industry Ontology and Semantic Web Services Framework. Proceedings of the International Workshop on Computing in Civil Engineering, pp657-664. Zhiliang, M., Zhenhua, W., Wu S. and L. Zhe. (2011). Application and Extension of the IFC Standard in Construction Cost Estimating for Tendering in China, Automation in Construction, 20(2), 196-204.