GIS collection development within an academic library.

ABSTRACT

Locating usable spatial data is essential for the application and use of Geographic Information Systems (GIS). GIS data collection development constitutes a core element of GIS services within academic libraries. Managers of geospatial resources require a fundamental understanding of the nature and use of GIS data. In the creation of a GIS collection development policy, library professionals should consider the established collection development policy, needs of the GIS user community, campus GIS services, and library infrastructure. Library professionals also need to employ a variety of online resource guides and spatial search engines and navigate a network of government agencies, academic institutions, commercial enterprises, and GIS professionals to locate, select, and acquire spatial datasets. When making decisions regarding GIS data acquisition, the selector should consider cost, availability, license agreements and distribution policies, documentation, data structures, and software and hardware.

INTRODUCTION

Since the late 1990s much has changed in the world of Geographic Information Systems (GIS): computer memory has become more accessible, the fields of geographic information science and spatial analysis have spread across disciplines, government agencies and commercial enterprises have developed massive spatial databases, high-resolution satellite imagery has become publicly available, a suite of software has been developed to meet the specialized needs of industry, and the Internet has emerged as a tool for data dissemination and visualization. There has also been a significant increase in new GIS positions within academic libraries as they struggle to develop, maintain, and expand their GIS services. These positions include GIS specialists, GIS/data librarians, GIS/map librarians, digital cartographers, spatial data specialists, and GIS coordinators. Nevertheless, the principles of GIS have not changed all that much over the past few years. Tomlin defines GIS as "a configuration of computer hardware and software [and personnel] specifically designed for the acquisition, maintenance, and use of geographically referenced data" (1990, p. xi). When developing GIS services, three core components must be addressed: computer hardware and software, personnel, and data management (Longstreth, 1995). While all GIS service elements are equally important, a particular emphasis exists regarding the GIS data (Jablonski, 2004; Lamont, 1997, van Loenen & Onsrud, 2004), especially since data development or conversion can be extremely labor intensive (Goodchild & Longley, 1999). As a result, the availability of preexisting data often determines the feasibility and geographic area of a research project. This article examines the development of a spatial data collection within an academic setting and addresses the selection, acquisition, and source of spatial data.

THE NATURE OF GIS DATA

A fundamental understanding of the nature of GIS data is required before one can locate and use spatial data. The terms spatial data, geospatial data, and GIS data--that is, digital, geographically referenced data will be used interchangeably in this article. GIS data are generally used to represent or model both physical and administrative geography. Physical features encompass both anthropogenic and natural features on or below the surface of the earth. Anthropogenic features typically include cultural phenomena, such as roads, railways, trails, buildings, and bridges. Natural features include rivers, lakes, shorelines, soils, elevations, etc. Abstract or administrative features are generally cultural divisions or boundaries created and used by organizations and agencies to administer their affairs and resources. These typically include national, state, county, election district, school district, municipal, zoning, zip code, neighborhood, census tract, and parcel or property boundaries. The Committee on Licensing Geographic Data and Services provides a detailed synthesis of geographic data types available in the United States (2004, Appendix C).

Two basic methods exist for representing geographic features within a GIS (DeMers, 1997, pp. 97-101). The vector data structure is composed of an ordered list of points and represented by points, lines, and polygons. Vector graphics model discrete geographic features such as administrative boundaries, roads, buildings, and rivers. A graphic vector object is usually combined or linked with attribute information stored in a separate spreadsheet or database. The raster data structure is composed of a grid of cells or pixels used to model continuous data. The resolution is a measure of the dimension on the ground represented by each pixel. Typical raster datasets include digital elevation models (DEMs), satellite imagery, digital orthophotography, land use/cover, and georeferenced digital images of maps.

GIS data are scaled models or abstractions of reality (Goodchild & Longley, 1999). Understanding the scale and precision of spatial data is essential for both locating and using GIS data. The scale of data is described as a representative fraction such as 1:100,000 (Chrisman, 2002, p. 98; Clarke, 2003, p. 120). The representative fraction is a ratio of units measured on the map to units measured on the surface of the earth. In the example above, one inch on the map equals 100,000 inches on the surface of the earth. The smaller the ratio is, the larger the scale is. For example, a scale of 1:1,200 is considerably larger than a scale of 1:24,000. Datasets of larger scale usually possess more detail and a higher…