The Florida Geographic Data Library: Lessons Learned and Workflows for Geospatial Data Management

The University of Florida GeoPlan Center has been organizing, standardizing, and distributing geospatial data since 1998 through the Florida Geographic Data Library (FGDL), a collection of Florida geospatial data from various agencies, as well as data developed in-house. With funding from the Florida Department of Transportation (FDOT), FGDL serves as a public distribution mechanism for hundreds of Florida geospatial data layers. Since 2004, FGDL layers have formed the data foundation for FDOT's interagency application known as efficient transportation decision making (ETDM), which facilitates the review and permitting process for proposed transportation projects. Data layers are standardized and inspected to ensure that the data are adequate for use in analysis and decision making. To efficiently manage the geospatial data and workflows, a quality assurance/quality control (QAQC) process and relational database schema was developed to track the standardization procedures, lineage, versioning, and archiving of the data layers. This article details the history of the Florida Geographic Data Library, challenges of managing a large geospatial data repository, development of a QAQC process and database schema, and lessons learned.     

THE ACHIEVEMENT GOALS ORIENTATION OF SOUTH AFRICAN FIRST YEAR UNIVERSITY PHYSICS STUDENTS

This paper is concerned with organizational principles of a pool of familiar problems of expert problem posers and the ways by which they are utilized for creating new problems. The presented case of Leo is part of a multiple-case study with expert problem posers for mathematics competitions. We present and inductively analyze the data collected in a reflective interview and in a clinical task-based interview with Leo. In the first interview, Leo was asked to share with us the stories behind some problems posed by him in the past. In the second interview, he was asked to pose a new competition problem in a thinking-aloud mode. We found that Leo’s pool of familiar problems is organized in classes according to certain nesting ideas. Furthermore, these nesting ideas serve him in posing problems that, ideally, are perceived by Leo as novel and surprising not only to potential solvers, but also to himself. Because of the lack of empirical research on experts in mathematical problem posing, the findings are discussed in light of research on experts in problem solving and on novices in mathematical problem posing.