Stewart, Orion T.; Carlos, Heather A.; Lee, Chanam; Berke, Ethan M.; Hurvitz, Philip M.; Li, Li; Moudon, Anne Vernez; Doescher, Mark P. (2016). Secondary GIS Built Environment Data for Health Research: Guidance for Data Development. Journal Of Transport & Health, 3(4), 529 – 539.
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Abstract
Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the 9 BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Geographic Information-systems; Physical-activity; Land-use; Walking; Neighborhood; Associations; Density; Design; Adults; Travel; Active Travel; Pedestrian; Urban Design; Community Health; Rural
Kim, Jinyhup; Bae, Chang-Hee Christine. (2020). Do Home Buyers Value the New Urbanist Neighborhood? The Case of Issaquah Highlands, WA. Journal Of Urbanism, 13(3), 303 – 324.
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Abstract
This study compares Issaquah Highlands’ home prices with those of traditional suburban single-family homes in the city of Issaquah. Issaquah Highlands is a community that was developed using New Urbanism principles. The null hypothesis is that the sale prices of houses in Issaquah Highlands are not different from the conventional suburban neighborhood in the city of Issaquah. The principal database consists of US Census Washington State Geospatial Data Archive, and the King County Tax Assessments. The final dataset contains 1,780 single family homes over the seven-year period from 2012 to 2018 based on sale records throughout the city of Issaquah. This study uses the hedonic pricing technique to assess the impact of New Urbanism on the value of single-family residences. The findings suggest that people are willing to pay a $92,700–96,800 premium (approximately 7.1–12.0 percent of the sales prices) for houses in Issaquah Highlands.
Keywords
New Urbanism; Home Prices; Real Property; Sustainable Development; Spatial Analysis (statistics); Hedonic Pricing Model; Property Value; Smart Growth; Spatial Autocorrelation; Neighborhoods; Databases; Taxation; Spatial Data; Suburban Areas; Census; Prices; Housing Prices; Urbanism; Houses; Willingness To Pay; Residential Areas; Null Hypothesis; Cities; Buyers; Hedonism; Sales; Highlands; Tax Assessments
Hsieh, Shang-hsien; Lin, Hsien-tang; Chi, Nai-wen; Chou, Kuang-wu; Lin, Ken-yu. (2011). Enabling The Development Of Base Domain Ontology Through Extraction Of Knowledge From Engineering Domain Handbooks. Advanced Engineering Informatics, 25(2), 288 – 296.
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Abstract
Domain ontology, encompassing both concepts and instances, along with their relations and properties, is a new medium for the storage and propagation of domain specific knowledge. A significant problem remains the effort which must be expended during ontology construction. This involves collecting the domain-related vocabularies, developing the domain concept hierarchy, and defining the properties of each concept and the relationships between concepts. Recently several engineering handbooks have described detailed domain knowledge by organizing the knowledge into categories, sections, and chapters with indices in the appendix. This paper proposes the extraction of concepts, instances, and relationships from a handbook of a specific domain to quickly construct base domain ontology as a good starting point for expediting the development process of more comprehensive domain ontology. The extracted information can also be reorganized and converted into web ontology language format to represent the base domain ontology. The generation of a base domain ontology from an Earthquake Engineering Handbook is used to illustrate the proposed approach. In addition, quality evaluation of the extracted base ontology is performed and discussed. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords
Ontology; Earthquake Engineering; World Wide Web; Theory Of Knowledge; Vocabulary; Programming Languages; Domain Handbook; Domain Ontology; Owl; Web Ontology Language; Knowledge Representation Languages; Ontologies (artificial Intelligence); Base Domain Ontology; Knowledge Extraction; Engineering Domain Handbooks; Domain Specific Knowledge Storage; Domain Specific Knowledge Propagation; Domain-related Vocabularies; Domain Concept Hierarchy; Development Process; Web Ontology Language Format; Earthquake Engineering Handbook; Semantic Web; Management; Design
Neff, Gina; Tanweer, Anissa; Fiore-Gartland, Brittany; Osburn, Laura. (2017). Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies And Data Science. Big Data, 5(2), 85 – 97.
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Abstract
What would data science look like if its key critics were engaged to help improve it, and how might critiques of data science improve with an approach that considers the day-to-day practices of data science? This article argues for scholars to bridge the conversations that seek to critique data science and those that seek to advance data science practice to identify and create the social and organizational arrangements necessary for a more ethical data science. We summarize four critiques that are commonly made in critical data studies: data are inherently interpretive, data are inextricable from context, data are mediated through the sociomaterial arrangements that produce them, and data serve as a medium for the negotiation and communication of values. We present qualitative research with academic data scientists, data for good projects, and specialized cross-disciplinary engineering teams to show evidence of these critiques in the day-to-day experience of data scientists as they acknowledge and grapple with the complexities of their work. Using ethnographic vignettes from two large multiresearcher field sites, we develop a set of concepts for analyzing and advancing the practice of data science and improving critical data studies, including (1) communication is central to the data science endeavor; (2) making sense of data is a collective process; (3) data are starting, not end points, and (4) data are sets of stories. We conclude with two calls to action for researchers and practitioners in data science and critical data studies alike. First, creating opportunities for bringing social scientific and humanistic expertise into data science practice simultaneously will advance both data science and critical data studies. Second, practitioners should leverage the insights from critical data studies to build new kinds of organizational arrangements, which we argue will help advance a more ethical data science. Engaging the insights of critical data studies will improve data science. Careful attention to the practices of data science will improve scholarly critiques. Genuine collaborative conversations between these different communities will help push for more ethical, and better, ways of knowing in increasingly datum-saturated societies.
Keywords
Big; Communication; Politics; Critical Data Studies; Data For Good; Data Science; Ethics; Qualitative Methods; Theory
Lee, Wonil; Migliaccio, Giovanni C.; Lin, Ken-Yu; Seto, Edmund Y. W. (2020). Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers. Safety Science, 123.
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Abstract
This study examines how task demands and personal resources affect unskilled construction worker productivity and safety performance. It extends the job demands-resources (JD-R) burnout model to show how job characteristics interact with burnout to influence performance. A modified model was designed to measure burnout, with exhaustion and disengagement among unskilled construction workers taken into consideration. An observational study was conducted in a laboratory environment to test the research hypotheses and assess the prediction accuracies of outcome constructs. Twenty-two subjects participated in multiple experiments designed to expose them to varying levels of task-demands and to record their personal resources as they performed common construction material-handling tasks. Specifically, both surveys and physiological measurements using wearable sensors were used to operationalize the model constructs. Moreover, partial least squares structural equation modeling was applied to analyze data collected at the task and individual levels. Exhaustion and disengagement exhibited different relationships with productivity and safety performance outcomes as measured by unit rate productivity and ergonomic behavior, respectively. Subjects with high burnout and high engagement showed high productivity but low safety performance. Thus, exhausted workers stand a greater chance of failing to comply with safety. As the sample and the task performed in the experiment do not cover the experience and trade of all construction workers, our findings are limited in their application to entry-level and unskilled workers, whose work is mainly manual material-handling tasks.
Keywords
Construction Workers; Structural Equation Modeling; Job Descriptions; Labor Productivity; Labor Supply; Burnout; Job Demand-resources Model; Partial Least Squares Structural Equation Modeling; Productivity; Safety; Wearable Sensors; Biomechanics; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Occupational Stress; Personnel; Statistical Analysis; Workforce Development; Understanding Task-level Job Demands-resources; Unskilled Construction Workers; Task Demands; Personal Resources; Unskilled Construction Worker Productivity; Job Demands-resources Burnout Model; Job Characteristics Interact; Exhaustion; Disengagement; Outcome Constructs; Varying Levels; Task-demands; Common Construction Material-handling Tasks; Physiological Measurements; Model Constructs; Individual Levels; Unit Rate Productivity; High Burnout; Low Safety Performance; Exhausted Workers; Entry-level; Unskilled Workers; Manual Material-handling Tasks; Heart-rate-variability; Labor Productivity Trends; Physiological Demands; Emotional Exhaustion; Safety Climate; Role Stress; Engagement; Fatigue; Workload; Task Analysis; Workforce; Level (quantity); Construction Materials; Personnel Management; Materials Handling; Multivariate Statistical Analysis
Launching the Inspire Fund: An early step for CBE’s Office of Research “For a small college, CBE has a broad range of research paradigms, from history and arts, to social science and engineering.” — Carrie Sturts Dossick, Associate Dean of Research Upon taking on the role of Associate Dean of Research, Carrie Sturts Dossick, professor in the Department of Construction Management, undertook listening sessions to learn about the research needs of faculty, staff and students across the College of Built…
Julie Kriegh, researcher with the Carbon Leadership Forum and other CBE research centers, and owner of Kriegh Architecture Studios, collaborated with other CBE faculty and external partners to lead a UW CBE studio course in collaboration with Google that developed and delivered a design proposal for a sustainable data center. CBE collaborators included Hyun Woo “Chris” Lee, P.D. Koon Professorship in Construction Management; Jan Whittington, Associate Professor of the Department of Urban Design and Planning, and Director of the Urban…
Urban systems, system complexity, big data, artificial intelligence, smart cities, communities, and coupled human-built-environmental systems
Established in 1989 through two legislative programs, the WCRER compiles real estate sale transaction data, rental market statistics, and development metrics throughout the State of Washington. From this, the WCRER also develops affordable housing metrics for the state with data published in quarterly Washington State Housing Market Reports, a twice yearly Washington State Apartment Market Report, and the Washington Housing Market Data Toolkit. The WCRER also provides bespoke data driven research, educational outreach programs, and policy guidance to professional organizations consistent with its public service mandate.
The Washington Center for Real Estate Research (WCRER) was initially established by the Board of Regents at Washington State University (WSU) to provide a bridge between academic study and research on real estate topics and the professional real estate industries. It served that mission at WSU until merging with the Runstad Center at the beginning of 2012. WCRER works with faculty to ensure their rigorous research is accessible and easily usable by industry participants, the media and the general public, regardless of their statistical sophistication.
WCRER aims to provide credible research, value-added information, education services and project-oriented research to real estate licensees, real estate consumers, real estate service providers, institutional customers, public agencies, and communities in Washington state and the Pacific Northwest region.
The Washington Center for Real Estate Research is a key provider of real estate research and data across the State of Washington. The Center is primarily funded by the State, hence its central role in the provision of quality and robust data and market reports. Among its core activities are the Quarterly Washington State Housing Market Report and the semi-annual Apartment Market Survey for the State Department of Licensing.
The Center is active across a range of other research projects and works closely with stakeholders both across the University of Washington with the public and private sectors.
The Urban Form Lab (UFL) research aims to affect policy and to support approaches to the design and planning of more livable environments. The UFL specializes in geospatial analyses of the built environment using multiple micro-scale data in Geographic Information Systems (GIS). Current research includes the development of novel GIS routines for performing spatial inventories and analyses of the built environment, and of spatially explicit sampling techniques. Projects address such topics as land monitoring, neighborhood and street design, active transportation, non-motorized transportation safety, physical activity, and access to food environments.
Research at the UFL has been supported by the U.S. and Washington State Departments of Transportation, the Centers for Disease Control and Prevention, the Robert Wood Johnson Foundation, the National Institutes of Health, and local agencies.
The Urban Form Lab is directed by Anne Vernez Moudon, Dr es Sc, a leading researcher and educator in quantifying the properties of the built environment as related to health and transportation behaviors. Philip M. Hurvitz, PhD, a veteran of geographic information science and data processing, leads data management and GIS work.