GIA Core Functions
The GIA Core provides support services to PRI faculty in the areas of expert advice, mapping/cartography (publications, websites, presentations), geocoding/address-matching, contextual database creation/ecological data sets, geospatial data archive/management, geospatial data acquisition, spatial statistics, custom programming, and GIS training. During the past three years 20+ PRI faculty have used the GIA Core.
Function 1: Provide expert advice. Matthews uses personal communication and the Research Activity Tracking System (RATS) to identify PRI researchers planning grant submissions. Thus, early in the proposal development process Matthews meets with researchers to discuss proposal-related scientific, personnel, workload, budget and timing issues. In addition, he provides faculty with a description of GIA Core services, emphasizing the recent contributions of GIA Core services to research (i.e., mapping, defining new variables, building contextual databases, integrating ecological databases, and constructing spatial weights and spatially lagged variables for spatial econometrics, data archiving, customized programming). We anticipate growth in the use of both spatial statistics and geostatistical methods by PRI faculty. Matthews will work closely with geographers and spatial statisticians to provide both appropriate methodological advice and access to state-of-the-art software (GeoDa, Geographically Weighted Regression, STARS) to PRI's faculty.
Function 2: Mapping/Cartography. Maps have been created for internal and external use for publications, posters, presentations, and websites for the following PRI projects: The Three City Welfare Project (Burton); Family Life Project (Crouter, Cox and Vernon-Feagans); Family Life Project Ethnography Component (Burton); NSF Geoethnography (Burton, Matthews, and Skinner); Dominicans in Reading, PA (Jensen, DeJong, Oropesa, Cohen); Firebaugh's research on Global Income Inequality; Welfare and Migration Project (DeJong and Graefe); Measuring Spatial Segregation (Reardon et al.); Homelessness (Lee); Religion in the Metropolis (Zelinsky); and PRI/Demography websites (DeJong). As one example of the GIA Core work, consider the website designed by Zeiders and colleagues for the Family Life Project (http://www.pop.psu.edu/gia-core/flp/index.htm). Over the next funding cycle we anticipate even closer partnership with the Penn State's GeoVISTA Center and we will pass on our experience in both static and dynamic geovisualization techniques to PRI projects, and include any new developments in future GIS and Population Science workshops.
Function 3: Geocoding/Address-Matching. Geocoding remains an integral step in the development of contextual databases. Geocoding activities have been completed for the following PRI faculty projects: The Three City Welfare Project (Burton); Family Life Project (Crouter, Cox and Vernon-Feagans); Family Life Project Ethnography Component (Burton); NSF Geoethnography (Burton, Matthews, and Skinner); Religion in the Metropolis (Zelinsky); Substance Abuse in Schools (Gallay and Flanagan); and Recidivism in Georgia (Ruback). As one example of the GIA Core's geocoding efforts consider the work for the Family Life Project where thousands of neighborhood resources (i.e., grocery stores, gas stations) and anchor institutions (i.e., houses of worship, clinics, schools) have been geocoded for the Pennsylvania and North Carolina study areas. The GIA Core has partnered with the University GIS Council on a user contract that provides easy access to TeleAtlas's updated geospatial street file databases. Such contracts and cost-sharing arrangements ensure that the GIA Core has access to the highest quality geospatial data facilitating tasks such as geocoding. In addition, over the next funding cycle, we plan to place more emphasis on exploring the challenges associated with maintaining privacy for individuals and institutions when specific information is present in a GIS database. Matthews has worked with individual faculty and Penn State's IRB to help all parties better understand relevant issues. It is important to focus on both the representation of data and the spatial data systems (GIS and secure data servers) that store and integrate these data. The GIA Core has gained a lot of experience in dealing with sensitive data through the geoethnography projects, employing several mapping and data representation strategies to avoid privacy violations but we need to be ever vigilant in this area.
Function 4: Contextual Database Creation/Ecological Data Sets. Many demographers with individual-level data that includes a geocode (i.e., an address or any zonal reference identifier such as a FIPS code) are interested in ecological data for use in contextual models. Some demographers are also interested in ecological data for ecological modeling. The GIA Core regularly creates ecological and contextual data; for example, Family Life Project (Crouter, Cox and Vernon-Feagans); Adolescent Smoking in Cape Town (G. King); Measuring Spatial Segregation (Reardon et al.); and Religion in the Metropolis (Zelinsky). As an example of contextual data being generated consider the use of ArcGIS spatial analyst to create unique geographic isolation scores for 1,200+ FLP respondents. As an example of creating an ecological data set consider the creation of a customized database for census wards in Cape Town, South Africa for G. King. Over the next funding cycle we anticipate exploring creative uses of non-census data and non-census definitions of context to construct unique contextual databases. The GIA Core has gained experience in compiling and using data on community assets and resources (and risks); experience gained in but not limited to work for the Three City Study and the Family Life Project. Such non-census data are increasingly seen as providing alternative and objective measures of context, particularly in the urban built environment.
Function 5: Geospatial Data Archive/Management. The GIA Core manages all geospatial data for all PRI projects using its services. Geospatial data are unique and thus unlike the demographic databases stored in PRI's data archive. All geospatial data are stored on a secure, firewall protected server. Projects that draw on the geospatial data archive and management services include but are not limited to: Latin American Cities Spatial Inequality project (Jensen); The Three City Welfare Project (Burton); Family Life Project (Crouter, Cox, and Vernon-Feagans); Family Life Project Ethnography Component (Burton); Adolescent Smoking in Cape Town (G. King); Public Opinion and Policy Responsiveness in Small Electorates (Plutzer and Berkman); Measuring Spatial Segregation (Reardon et al.); Religion in the Metropolis (Zelinsky); and the Orkney Historical Project (Wood, P-Johnson, Matthews, and Murtha). In Summer 2005 as part of a research request from Reardon et al. the GIA Core generated up to 2 Gigabytes of stored data per analytical run to calculate pycnophylactic surfaces, store and then map measures of spatial segregation per city. Over the next funding cycle we will enhance in-house knowledge of National Spatial Data Infrastructure (NSDI) policies, standards, and procedures for the production and sharing of geographic data.
Function 6: Geospatial Data Acquisition. The GIA Core regularly updates its holdings of public domain and/or commercial geospatial data pertaining to the U.S. Census (current and historical) as well as data on education (National Center for Education Statistics), health (including SEER data), crime (FBI Uniform Crime Report data), and transportation (TeleAtlas). Similarly, we update our holdings of international geospatial data relevant to PRI researchers. As one example of data acquisition Matthews acquired from the Cape Town Metropolitan Council detailed geospatial data for the city and purchased the South African 2001 Census data. Together with McManus, Matthews has used these data to generate maps, ecological data sets, and contextual data sets that will be used in planned papers with G. King's research on adolescent risk-taking behaviors in Cape Town. In another project, McManus secured data on Business Privilege Licenses for the City of Philadelphia that will be used in a study of food availability in the city (Matthews). During the next funding cycle we plan to pilot-test data tablets, PDAs, and wireless technologies that may provide efficiencies in demographic fieldwork. Matthews has begun discussions on data collection needs with experts in mobile computing, sensor networks, and wireless networks in Computer Science and Engineering. The GIA Core supports fieldwork by ethnographers in the U.S. (Burton, Matthews) as well as international field research by faculty in Anthropology (Johnson, Wood) and Human Development and Family Studies (Jayakody).
Function 7: Spatial Statistics and Customized Programming. The development of customized GIS scripts or programs can greatly facilitate PRI research. While not relevant to all projects this service is used by some computationally intensive data projects, including the Family Life Project (Crouter, Cox and Vernon-Feagans) where ArcGIS spatial analyst was used to generate geographic isolation scores for 1,200 respondents (see earlier reference). One project that has seen use of customized programming and/or spatial statistics is: Reardon et al.'s measuring spatial segregation, which includes programs to generate complex population surfaces based on pycnophylactic smoothing algorithms for large U.S. metropolitan areas. Matthews has used specialized tools embedded in GeoDa (local indicators of spatial association [LISA] statistics), SpaceStat (spatial regression), and CrimeStat (point pattern analysis options) in projects with Zelinsky on religion in the metropolis, with Ruback on crime and victimization in Seattle, and in analyzing some of the data from the Three City Welfare ethnography (Burton). As mentioned earlier, we anticipate continued growth in the use of both geostatistics and spatial statistics and through the next funding cycle will remain up-to-date on methodological and software developments. Matthews will continue to work closely with faculty in the Statistics Core, the Department of Statistics, and other GIS centers on campus (e.g., GeoVISTA).
Function 8: Training. Since its establishment the GIA Core has emphasized GIS training for population scientists at Penn State and elsewhere. Matthews has coordinated GIS workshops at national conferences (e.g., Population Association of America, 1998-2003; Family Research Consortium IV, 2004) and locally at Penn State (e.g., Burton's Family Research Consortium III postdoctoral fellows summer workshop). In addition, in June 2004 Matthews organized a GIS training workshop for tobacco researchers in Cape Town, South Africa (support from G. King's Fogarty International Center grant for capacity building in tobacco research). In 2004 Matthews received an R25 grant for GIS training for population scientists that involves a collaboration with the Center for Spatially Integrated Social Science (UC Santa Barbara) and Geography and GeoVISTA at Penn State. During summer 2005 the GIA Core hosted a two-week workshop at Penn State and facilitated another in Santa Barbara. These two GIS workshops received over 130 applications for 40 places. The GIA Core has offered targeted workshops for PRI faculty interested in both substantive demographic and methodological issues. The graduate students in the Demography Training Program are exposed to GIS, spatial analysis and statistical methods through a course taught by Matthews (Demography 597: Spatial Demography) and the GIA Core regularly offers workshops and/or software demonstrations. GIA Core workshops continue to be offered on average five times each semester, focusing on both basic and practical use of ArcGIS 9.x (e.g., building geodatabases, geocoding, joining/relating tables, editing features/attributes, map design and export options for saving maps and/or images in digital formats for use in PowerPoint presentations or MSWord/WordPerfect documents) as well as the specialized extraction of census data and boundary files, and the use of packages such as GeoDa, Geographically Weighted Regression, STARS, and CrimeStat. A goal for the next funding cycle is the development of on-line instructional resources that will include lecture notes, presentations, exercises, and data sets explicitly focused on GIS applications in spatial demography. Our hope is that these instructional resources will become a resource for the field.
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