BEKG: A Built Environment Knowledge Graph

Practices in the built environment have become more digitalized with the rapid development of modern design and construction technologies. However, the requirement of practitioners or scholars to gather complicated professional knowledge in the built environment has not been satisfied yet. In this paper, more than 80,000 paper abstracts in the built environment field were obtained to build a knowledge graph, a knowledge base storing entities and their connective relations in a graph-structured data model. To ensure the retrieval accuracy of the entities and relations in the knowledge graph, two well-annotated datasets have been created, containing 2,000 instances and 1,450 instances each in 29 relations for the named entity recognition task and relation extraction task respectively. These two tasks were solved by two BERT-based models trained on the proposed dataset. Both models attained an accuracy above 85% on these two tasks. More than 200,000 high-quality relations and entities were obtained using these models to extract all abstract data. Finally, this knowledge graph is presented as a self-developed visualization system to reveal relations between various entities in the domain. Both the source code and the annotated dataset can be found here: https://github.com/HKUST-KnowComp/BEKG

ElectroLens: Understanding Atomistic Simulations Through Spatially-resolved Visualization of High-dimensional Features

In recent years, machine learning (ML) has gained significant popularity in the field of chemical informatics and electronic structure theory. These techniques often require researchers to engineer abstract "features" that encode chemical concepts into a mathematical form compatible with the input to machine-learning models. However, there is no existing tool to connect these abstract features back to the actual chemical system, making it difficult to diagnose failures and to build intuition about the meaning of the features. We present ElectroLens, a new visualization tool for high-dimensional spatially-resolved features to tackle this problem. The tool visualizes high-dimensional data sets for atomistic and electron environment features by a series of linked 3D views and 2D plots. The tool is able to connect different derived features and their corresponding regions in 3D via interactive selection. It is built to be scalable, and integrate with existing infrastructure.Comment: accepted to IEEE visualization 2019 conferenc

Use of BIM at higher learning institutions : Evaluating the level of implementation and development of BIM at built environment schools in South Africa

Abstract: The introduction of Building Information Modelling (BIM) into the Architecture, Engineering and Construction industry (AEC) has completely revolutionized how we design and construct buildings. BIM shows significant positive changes for the consulting industry in terms of reducing errors, understanding buildings, realistic visualization, clash detection amongst other remarkable features. However, BIM is an ongoing course of complex processes and it is important that users are kept in the loop of new concepts, processes and workflows. Universities, the world over are making concerted efforts to introduce and implement BIM education for their built environment courses as it has become a component of a professionals practical training. However, it is necessary to determine at what level BIM education is being implemented at educational institutions. This research explores how South African built environment schools have implemented BIM in their teaching syllabus and level of implementation. Data was collected using questionnaires from representatives at built environment schools or departments in the public universities. Findings reveal that there is some usage of 2D and 3D CAD in design modules at some universities. However results suggest very little implementation of BIM methods and processes in many universities. This research will be useful for the AEC industry in terms of judging the level of education in the BIM spectrum and can assist with future training of professionals, regarding BIM

Diabetes and the socioeconomic and built environment: geovisualization of disease prevalence and potential contextual associations using ring maps

<p>Abstract</p> <p>Background</p> <p>Efforts to stem the diabetes epidemic in the United States and other countries must take into account a complex array of individual, social, economic, and built environmental factors. Increasingly, scientists use information visualization tools to "make sense" of large multivariate data sets. Recently, ring map visualization has been explored as a means of depicting spatially referenced, multivariate data in a single information graphic. A ring map shows multiple attribute data sets as separate rings of information surrounding a base map of a particular geographic region of interest. In this study, ring maps were used to evaluate diabetes prevalence among adult South Carolina Medicaid recipients. In particular, county-level ring maps were used to evaluate disparities in diabetes prevalence among adult African Americans and Whites and to explore potential county-level associations between diabetes prevalence among adult African Americans and five measures of the socioeconomic and built environment—persistent poverty, unemployment, rurality, number of fast food restaurants per capita, and number of convenience stores per capita. Although Medicaid pays for the health care of approximately 15 percent of all diabetics, few studies have examined diabetes in adult Medicaid recipients at the county level. The present study thus addresses a critical information gap, while illustrating the utility of ring maps in multivariate investigations of population health and environmental context.</p> <p>Results</p> <p>Ring maps showed substantial racial disparity in diabetes prevalence among adult Medicaid recipients and suggested an association between adult African American diabetes prevalence and rurality. Rurality was significantly positively associated with diabetes prevalence among adult African American Medicaid recipients in a multivariate statistical model.</p> <p>Conclusions</p> <p>Efforts to reduce diabetes among adult African American Medicaid recipients must extend to rural African Americans. Ring maps can be used to integrate diverse data sets, explore attribute associations, and achieve insights critical to the promotion of population health.</p

Visualization in spatial modeling

This chapter deals with issues arising from a central theme in contemporary computer modeling - visualization. We first tie visualization to varieties of modeling along the continuum from iconic to symbolic and then focus on the notion that our models are so intrinsically complex that there are many different types of visualization that might be developed in their understanding and implementation. This focuses the debate on the very way of 'doing science' in that patterns and processes of any complexity can be better understood through visualizing the data, the simulations, and the outcomes that such models generate. As we have grown more sensitive to the problem of complexity in all systems, we are more aware that the twin goals of parsimony and verifiability which have dominated scientific theory since the 'Enlightenment' are up for grabs: good theories and models must 'look right' despite what our statistics and causal logics tell us. Visualization is the cutting edge of this new way of thinking about science but its styles vary enormously with context. Here we define three varieties: visualization of complicated systems to make things simple or at least explicable, which is the role of pedagogy; visualization to explore unanticipated outcomes and to refine processes that interact in unanticipated ways; and visualization to enable end users with no prior understanding of the science but a deep understanding of the problem to engage in using models for prediction, prescription, and control. We illustrate these themes with a model of an agricultural market which is the basis of modern urban economics - the von Thünen model of land rent and density; a model of urban development based on interacting spatial and temporal processes of land development - the DUEM model; and a pedestrian model of human movement at the fine scale where control of such movements to meet standards of public safety is intrinsically part of the model about which the controllers know intimately. © Springer-Verlag Berlin Heidelberg 2006

Digital Urban - The Visual City

Nothing in the city is experienced by itself for a city’s perspicacity is the sum of its surroundings. To paraphrase Lynch (1960), at every instant, there is more than we can see and hear. This is the reality of the physical city, and thus in order to replicate the visual experience of the city within digital space, the space itself must convey to the user a sense of place. This is what we term the “Visual City”, a visually recognisable city built out of the digital equivalent of bricks and mortar, polygons, textures, and most importantly data. Recently there has been a revolution in the production and distribution of digital artefacts which represent the visual city. Digital city software that was once in the domain of high powered personal computers, research labs and professional software are now in the domain of the public-at-large through both the web and low-end home computing. These developments have gone hand in hand with the re-emergence of geography and geographic location as a way of tagging information to non-proprietary web-based software such as Google Maps, Google Earth, Microsoft’s Virtual Earth, ESRI’s ArcExplorer, and NASA’s World Wind, amongst others. The move towards ‘digital earths’ for the distribution of geographic information has, without doubt, opened up a widespread demand for the visualization of our environment where the emphasis is now on the third dimension. While the third dimension is central to the development of the digital or visual city, this is not the only way the city can be visualized for a number of emerging tools and ‘mashups’ are enabling visual data to be tagged geographically using a cornucopia of multimedia systems. We explore these social, textual, geographical, and visual technologies throughout this chapter