Polis Center Works

Permanent URI for this collection

https://hdl.handle.net/1805/30409

Browse

Browsing Polis Center Works by Author "Colbert, Jay"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Digital Atlas of American Religion
    (2013-04-05) Bodenhamer, David; Kandris, Sharon; Devadasan, Neil; Colbert, Jay; Dowling, Jim; Danielson, Laura
    Our poster presentation will introduce DAAR, the Digital Atlas of American Religion (http://www.religionatlas.org). DAAR is a web-based research platform with innovative data exploration and visualization tools to support research in the humanities. Time and location are essential components of humanities exploratory research; however, GIS technology, especially in its web form, does not support the easy exploration and visualization of the complex spatio-temporal data manipulated by humanists. DAAR presents researchers with an integrated solution stemming from several fields including GIS, visualization, and classification theory. Researchers using DAAR are provided with the following exploration/visualization techniques: maps, cartograms, tree maps, pie charts, and motion charts. Using these tools and methods, researchers can explore patterns, trends, and relationships in the data that otherwise are not apparent with traditional GIS or statistical software. DAAR allows researchers to understand the multiple dimensions and diversity of religion across geographies, or within geographies. Paired with historic census data, it allows them to explore relationships to give better context and meaning to the patterns and trends. Maps provide the spatial patterns and relationships, tree maps show relative strength and relationships, charts show trends, cartograms reveal relative numbers of adherence, and motion charts animate trends over time.
  • Thumbnail Image
    Item
    SAVI Data Catalog
    (The Polis Center at IUPUI, 2011-04) Derr, Michelle; Colbert, Jay; Nalla, Goutami; Comer, Karen F.
    The SAVI Community Information System (SAVI) is the nation’s largest spatially-enabled system of its type, providing local organizations, researchers, and involved citizens with the detailed, geographically precise information needed to make well-informed decisions. This data catalog describes the wealth of free data provided by SAVI, including data about the social, physical, and economic conditions of Central Indiana communities from counties to neighborhoods and census tracts, as well as information on thousands of non-profit and community-based organizations and programs. SAVI exists as a Web-based, interactive system that allows users to create custom maps, graphs, charts, and data profiles of over 2,000 Central Indiana communities.
  • Thumbnail Image
    Item
    SAVI Public Health Needs Assessment: Final Report and Recommendations
    (The Polis Center, IUPUI, 2007-07) Comer, Karen F; Kandris, Sharon; Colbert, Jay; Devadasan, Neil; Bodenhamer, David J
    This report summaries the 2007 assessment of current and projected health sector uses of the SAVI Community Information System (SAVI) and recommends SAVI enhancements to meet the information needs of decision makers, practitioners, and researchers. Based on focus groups and key informant interviews, it was discovered that local decisionmakers and practitioners in Central Indiana currently used SAVI, or would like to use SAVI, to assess the relative spatial demand and supply of health and human services, select sites for new health and human service facilities, assess patient access to health and human service facilities, select locations for services and programs, and track characteristics of facility catchment areas. Health practitioners and public health professionals were interested in using geospatially-enabled indicators for more effective planning and interventions, including to track public health outcomes, understand the socio-economic and physical environment of individual patients and communities, locate target populations for existing and potential health programs and services, support grant applications, and inform the public about environmental risk factors and disease prevalence in their communities. Clinical translational and public health researchers are using, or would like to use, geospatially-enabled measures for the study of social and environmental determinants of health, health disparities, environmental exposure and health risk, predictors of health knowledge, ecological models of health behavior, health service access, quality, and cost, and efficacy of health interventions. Detailed recommendations are provided for both short- and long-term enhancements to SAVI based on the existing and potential SAVI users and uses identified via this study and toward assisting the local health sector improve health knowledge and ultimately the health and wellbeing of Central Indiana communities.